diff --git a/.gitignore b/.gitignore index 534f2b8..d710180 100644 --- a/.gitignore +++ b/.gitignore @@ -58,6 +58,18 @@ Thumbs.db /releases/ /artifacts/ +# Generated sample corpus (programmatically regenerable; `npm run samples:generate`) +/samples/generated/ + +# Heavy OCR runtime + model vendors (reproducible via vendor scripts + local download; +# bundled into the app build from disk, not committed): +# onnxruntime-web: `npm i onnxruntime-web && npm run vendor:onnx` +# tesseract.js: `npm i tesseract.js && npm run vendor:tesseract` +# PP-OCRv5 ONNX models: `npm run vendor:paddle` (pinned source + SHA-256, scripts/paddleocr-models.manifest.json) +/public/vendor/onnxruntime/ +/public/vendor/paddleocr/ +/public/vendor/tesseract/ + # Test screenshots / debug captures /test-results/ /playwright-report/ diff --git a/CHANGELOG.md b/CHANGELOG.md index 195e93e..b9cc0c5 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -4,12 +4,30 @@ ## [Unreleased] +## [2.3.0] - 2026-05-30 + +### 新增 + +- **本地 OCR（PP-OCRv5）**：图片 / 扫描 PDF 经 ONNX Runtime + WebGPU（WASM 回退）在本机识别。完整管线含图像预处理（ImageNet 归一化 + limit_side_len + 32 倍数）、DB 检测后处理（连通域 + unclip 外扩）、CTC 贪心解码 + 字典对齐、cls 方向校正（180°）、竖排/侧向 90° 试转、任意角倾斜自动纠偏（错切投影估角）、自适应中值去噪（仅噪图去噪、净图不损）、版面结构识别（按字号/间距归并为标题+段落）与识别质量评分（grade / 置信度 / 低置信行 / 纠偏 / 去噪）。应用内置一套 PP-OCRv5 mobile 模型，启动时自动载入本地缓存，开箱即用；可在安全中心导入/替换。用真实模型实测验证（rec 解词图为 "PAIN"、产品标签 0.978、倒置 0.976、+10° 倾斜 8→16 行恢复）。 +- **轻量 OCR（Tesseract.js）**：可选轻量 OCR engine，按需在安全中心导入 tessdata；与 PP-OCRv5 经优先级感知 `pickForTask` 路由（paddle 优先）。 +- **转换后检验三层**：规则 diff（字段级结构对比）+ SSIM 视觉回环 + OCR 回读，统一写入 `qualityReport.{ruleDiff,ssim,ocrReadback}` + `verification` envelope；工作台「转换检验报告」可视，含 OCR 识别质量行。SSIM 核心、文本相似度、规则 diff 均为零依赖纯函数，Node 全覆盖。 +- **LaTeX 数学渲染**：`$...$` / `$$...$$` 受保护 tokenization（反斜杠 / 下划线逐字保留，货币不误判），预览用本地 KaTeX 排版，零联网。 +- **Repair Engine 与按需模型缓存**：RepairAction 契约 + 规则驱动 validator/handler + 复核循环；model-cache manifest / SHA-256 / 状态机 / 安全中心导入 UI。 +- **优质测试样例生成器**：`npm run samples:generate` 程序化产出覆盖全格式、复杂排版、大小不一（large ≥ 3MB）的样例语料（gitignore）。 + ### 修复 -- **P7-A Windows 桌面发布基线**：统一 `package.json`、Tauri 配置与 Rust crate 版本为 `2.2.0`，声明已入库的 Windows ICO 图标；新增配置门禁并通过真实 `npm run desktop:build` 产出 MSI 与 NSIS 安装包。 -- **P8 路由损失可见性**：`RoutePlanner` 现在返回实际模型路径，跨模型转换将 `forcedWarnings` 和 `routeTemperature` 写入 QualityReport；工作台转换完成后展示带路径降级提示的转换模型。 -- **P8-B 可执行 mapper 与路径真值**：`SemanticDoc <-> WorkbookModel` 首批 mapper 已进入实际转换链并记录 `executedMappers`；`PPTX` 生成型输出和 `OFD -> PDF` 受限路径通过 `routeClass` 与 `PATH_NOT_RECOMMENDED` 明示质量边界。 -- **Markdown 导出原始 HTML 回归**：保留 task list 的 `[]` 字面语义，同时恢复文本节点 `<` / `>` 转义，避免纯文本输入导出 `.md` 时激活 HTML 标签。 +- **首页空白**：`browser-transformer.js` 漏 re-export `getKnownInputFormats` 导致 `landing-view.js` 浏览器加载失败、首页空白；补导出并加模块图加载守门。 +- **OCR 实际不触发**：转换走 Web Worker 同步路径绕过了 OCR；图片/PDF 改走主线程异步管线，OCR 真正执行。 +- **冻结引擎导入失败**：`paddleOcrEngine`/`tesseractOCREngine` 就绪状态存于冻结对象，`ensureProbe()` 赋值在严格模式抛错、令安全中心导入静默失败；改为模块级状态。 +- **OCR 质量数据被覆盖**：Repair Engine 的 `modelReview` 覆盖了 OCR stage 的，丢弃 `ocr/ocrQuality`；改为合并保留，识别质量得以在 UI 展示。 +- **P7-A Windows 桌面发布基线**：统一 `package.json`、Tauri 配置与 Rust crate 版本，声明 Windows ICO 图标；配置门禁 + 真实 `npm run desktop:build` 产出 MSI/NSIS。 +- **P8 路由损失可见性 / P8-B 可执行 mapper**：`RoutePlanner` 返回实际模型路径，`executedMappers` / `routeClass` / `PATH_NOT_RECOMMENDED` 写入 QualityReport。 +- **Markdown 导出原始 HTML 回归**：保留 task list `[]` 字面语义，恢复文本节点 `<` / `>` 转义。 + +### 方向 + +- **高级 OCR 目标调整**：调研确认 PaddleOCR-VL / MinerU（VLM）在浏览器/Tauri 本地 + 零云端 + 轻量默认包约束下不可内嵌，把高级 OCR 内置目标定为 **PP-OCRv5（ONNX/WebGPU）**，VLM 标注为远期/外部资源。 ## [2.2.0] - 2026-05-26 diff --git a/DEVELOPMENT_TASKS.md b/DEVELOPMENT_TASKS.md index ebd9c3a..73b2b64 100644 --- a/DEVELOPMENT_TASKS.md +++ b/DEVELOPMENT_TASKS.md @@ -47,17 +47,22 @@ | P9-A.3 PNG 异步 OCR 接入 + Repair 入口 | 已完成（2026-05-28） | convertContentAsync + runOCRStage 把 OCR 写入 SemanticDoc；detectOCRLowConfidence 进入 Repair Engine 默认 validator | | P9-A.4 扫描 PDF OCR 检测 + Rasterizer 骨架 | 已完成（2026-05-28） | isScannedPdf 启发式 + PdfPageRasterizer 抽象 + 多页 OCR stage + convertAsync PDF 分支 | | P9-B OCR → FixedLayoutModel + 浏览器 rasterize | 已完成（2026-05-28） | OCR 多页结果 → FixedLayoutModel（含 bbox/confidence/readingOrder）→ fixedLayoutToSemantic 派生 blocks；浏览器端 defaultPdfPageRasterizer 自动 dynamic import vendor pdfjs | -| P9-C 转换后检验三层 | 待启动 | 规则 diff、SSIM 视觉对比、OCR 回读检验统一写入 QualityReport | -| P9-D 高级 OCR | 待启动 | PaddleOCR-VL / MinerU 等大模型作为独立本地资源按需下载，明确体积、内存、降级路径 | +| P9-C.1 转换后检验三层 · 规则 diff 层 | 已完成（2026-05-29） | `public/core/verification/` 三模块 + `runVerificationStage` 编排 + `qualityReport.ruleDiff` / `qualityReport.verification` envelope；同格式 + md↔html 回环回读 diff；`blockFingerprint`/`modelFingerprint` 抽出共享 | +| P9-C.2 转换后检验三层 · SSIM 视觉对比 | 已完成（2026-05-29） | 自实现 SSIM core（零依赖）+ 视觉回环（输入页 vs 输出页）+ 像素源抽象（Node throw / 浏览器 canvas / 测试注入 stub）→ 写入 `qualityReport.ssim`；异步层只在 `convertAsync` 跑 | +| P9-C.3 转换后检验三层 · OCR 回读 | 已完成（2026-05-29） | 输出 PDF 栅格化→OCR 读回→与原文字符级 recall/precision/f1 对照→写入 `qualityReport.ocrReadback`；engine/rasterizer 复用 ocr-text，Node stub 覆盖 | +| P9-D.1 高级 OCR · PP-OCRv5 引擎骨架 | 已完成（2026-05-29） | 方向确认 PP-OCRv5 (ONNX/WebGPU) 为内置目标（VLM 远期/外部）；`paddleOcrEngine` 契约 + ONNX manifest 登记 + Node 不可用三阶段拒绝；不引入 runtime、不实跑推理 | +| P9-D.2 高级 OCR · onnxruntime-web vendor + 运行时骨架 | 已完成（2026-05-29） | onnxruntime-web optionalDependency + sync-onnxruntime-vendor + `loadOnnxRuntime`/`pickExecutionProviders`(WebGPU/WASM)/session 骨架；recognize 经运行时加载，Node 抛 vendor-load-failed | +| P9-D.3 高级 OCR · PP-OCRv5 模型导入与安全中心管理 | 已完成（2026-05-29） | 安全中心导入 det/cls/rec onnx（file picker + SHA-256 + IDB，禁联网本地导入）→ ensureProbe 三件齐全置 available；顺带修复冻结引擎 ensureProbe 赋值 bug | +| P9-D.2.b 高级 OCR · PP-OCRv5 推理管线 | 已完成（2026-05-29） | 纯函数 det/rec 预处理 + DB 连通域后处理 + CTC 贪心解码 + `runPaddlePipeline` 编排（mock session 端到端可测）；recognize 浏览器端 decode+session+pipeline，Node 仍 vendor-load 前置拒绝 | +| P9-D.4 高级 OCR · 接入转换链（路由偏好） | 已完成（2026-05-29） | 优先级感知 pickForTask（paddle 20 > tesseract 10 > placeholder 0）；PNG/扫描 PDF stage 经 pickForTask 自动受益。P9-D PP-OCRv5 链路齐备，剩真实模型导入后浏览器端到端验证 | 详细子任务和验收门槛见 [docs/archive/DEVELOPMENT_HISTORY.md](docs/archive/DEVELOPMENT_HISTORY.md)。 ## 下一步执行顺序 -1. **P9-C 转换后检验三层**：规则 diff、SSIM 视觉对比、OCR 回读检验三层组合统一写入 QualityReport，作为项目核心差异化能力落地。 -2. **P9-D 高级 OCR**：接入 PaddleOCR-VL / MinerU 等本地解析模型；模型资源完全独立按需下载，明确体积、运行内存、降级路径和失败提示。 -3. **P7-B 跨平台发布与签名**：在转换能力表述准确后，于对应构建环境完成 macOS/Linux 安装包、签名/公证、自动更新、平台 smoke、文件关联和桌面权限体验。 -4. **发布前回归**：`npm test`、`git diff --check`、`npm run release:prepare`、release manifest ignore 验证。 +1. **P9-D / P9-C 浏览器端到端验证**：在浏览器/Tauri 端 `npm run vendor:onnx` + 安全中心导入真实 PP-OCRv5 det/cls/rec ONNX + 字典后，实测 PNG/扫描 PDF → 高级 OCR 的真实识别 + 三层检验（SSIM/OCR 回读真实跑）。P9-D 全链路 .1/.2/.3/.2.b/.4 已落地，Node 侧以 mock/纯函数全覆盖；真实渲染/OCR fixture 入库待此项。 +2. **P7-B 跨平台发布与签名**：macOS/Linux 安装包、签名/公证、自动更新、平台 smoke、文件关联与桌面权限体验。 +3. **发布前回归**：`npm test`、`git diff --check`、`npm run release:prepare`、release manifest ignore 验证。 ## P8-B 完成结果 @@ -84,6 +89,24 @@ > 仅保留最近 4 周内的记录；更早的归档到 [docs/archive/DEVELOPMENT_HISTORY.md](docs/archive/DEVELOPMENT_HISTORY.md)，逐次发布的细节走 [CHANGELOG.md](CHANGELOG.md)。 +- **2026-05-30 (OCR 识别质量展示到检验报告 UI + modelReview 保留修复)**：把已计算但一直不可见的 OCR 识别质量呈现给用户。**修复潜伏 bug**：`format-registry.js` `_runRepairCycle` 用 Repair Engine 的 `modelReview`（`engine:"rule-based"`）覆盖了上游 OCR stage 写的 `modelReview`，导致 `ocr`/`ocrQuality` 子对象被丢弃、UI 取不到——改为合并保留 `priorReview.ocr` / `priorReview.ocrQuality`。`public/index.html` 检验报告面板加「OCR 识别质量」行（`#verificationOcrRecognitionRow`，默认 hidden，仅本次跑了 OCR 才显示）。`public/app.js` `renderVerificationReport` 读 `quality.modelReview.ocr` + `.ocrQuality` 渲染：引擎 / 行数 / 置信度 / 质量 grade / 低置信行 / 纠偏角 / 方向校正数 / 已去噪；grade 驱动 ok·skip·drift 配色。`scripts/browser-smoke-test.js` 断言 `#verificationOcrRecognition` 存在。`scripts/ocr-baseline-test.js` 加回归断言（`convertContentAsync` 默认 repair 路径下 `result.quality.modelReview.ocr` 必须存活）。`npm test` 28 个脚本全量通过。 +- **2026-05-30 (OCR 版面结构识别增强)**：落实「对文件内部文本格式识别的增强」——把 OCR 识别的多行（带 bbox）按版面归并成标题 + 段落，而非平铺成一个大段。新增 `public/core/ocr/ocr-structure.js`：`deriveOcrStructure(lines, opts)`（按阅读顺序 y→x 排序；中位行高 → 相对字号判定标题，行高 ≥ 中位 ×1.35 为 heading、按比例给 level 1-3；行间垂直间距 > 中位 ×0.7 分段；同段相邻行 CJK 直连 / 拉丁加空格；无 bbox 几何回退单段保持旧行为）+ `blocksFromOcrResult(result)`（按页拼接，空则回退 fullText）。`png-ocr.js` `enhanceWithOCR` 把 `paragraphsFromOCR`（旧：整页 16 行拼成 1 段）换成 `blocksFromOcrResult`（结构化标题+段落），删旧函数 + 未用 import。**真机验证**：产品标签 16 行 → 4 个结构块（「纯臻营养护发素」识别为 heading，正文按间距归并为段落）。`browser-transformer` export `deriveOcrStructure`/`blocksFromOcrResult`。新增 `scripts/ocr-structure-test.js`（7 组：字号判标题、间距分段、CJK/拉丁拼接、阅读顺序排序、无几何回退、blocksFromOcrResult 翻页、空白行忽略）接入 `npm test`（第 28 个）。`npm test` 28 个脚本全量通过。 +- **2026-05-30 (OCR 倾斜文档自动纠偏 · 去倾斜)**：解决倾斜/旋转文档（拍照/扫描带角度）识别崩塌的问题。新增纯函数 `rotateImageDataByAngle(im, deg)`（任意角最近邻旋转 + 画布扩展 + 白底）+ `estimateSkewAngle(probData, mapW, mapH)`（对 det 概率图二值化下采样后，用错切投影直方图方差找让文本行最对齐水平的角度，返回去倾斜旋转角）。`runPaddlePipeline` 抽出 `detect(image)` helper + 接 `options.deskew=true(默认)|false`：从首次 det 估倾斜角，`|est| >= minSkew`(默认 3°) 则把图旋正后**重检一次**再识别——正立图估计≈0 不重检、零开销；识别（rec）始终只跑一次。**真机验证**：倾斜 +10° 文档原本 **8 行/avgConf 0.535**（检测崩一半），自动纠偏后恢复 **16 行/0.970**（skewApplied=10）；-8° 同样恢复；正立图 skewApplied=0、保持 0.974 不受影响。`quality` 摘要增 `skewApplied`。`browser-transformer` export `rotateImageDataByAngle`/`estimateSkewAngle`。`scripts/paddle-ocr-pipeline-test.js` 加任意旋转 + 倾斜估计（合成斜行 prob 图检出 ~角度、平行行≈0）断言（共 16 组）。`npm test` 27 个脚本全量通过。 +- **2026-05-30 (OCR 噪点去除 · 自适应中值去噪)**：按用户方向——只做文字内容转换（不保留艺术字样式），重点清理噪点改善带噪/艺术字背景识别。新增纯函数 `denoiseImageData`（3×3 中值滤波逐通道，保边去椒盐，alpha 透传）+ `estimateNoiseLevel`（采样统计与 3×3 邻域中值大幅跳变的孤立像素比例 [0,1]，区分椒盐噪点与文字边缘）。`runPaddlePipeline` 接 `options.denoise = "auto"(默认)|true|false`：**auto 仅当 `estimateNoiseLevel > denoiseThreshold`(默认 0.05) 才去噪**——因为实测中值滤波会软化干净图、把清晰文本 0.974 拉到 0.903，所以干净图绝不去噪。**真机验证**：干净文档 noise≈0.016 → 不去噪、保持 **0.974**；15% 椒盐噪点 noise≈0.10 → 去噪,**检测从 4 行恢复到 16 行、avgConf 0.692→0.832**（重噪下检测会崩,去噪救回）。`quality` 摘要增 `denoised`/`noiseLevel`。`browser-transformer` export `denoiseImageData`/`estimateNoiseLevel`。`scripts/paddle-ocr-pipeline-test.js` 加噪点估计/中值去噪/auto-gating 三组断言（共 14 组）。明确**不做** 艺术字样式保留（只转文字内容）/ minAreaRect 透视纠偏。`npm test` 27 个脚本全量通过。 +- **2026-05-30 (OCR 方向校正 + 竖排/侧向 + 质量把控)**：增强难例识别与质量控制。**方向校正**：cls 模型实测输出 `[1,2]` softmax（class0=0°/class1=180°，upright→[1,0]、翻转→[0,1]），`runPaddlePipeline` 接 `interpretClsOutput` 在 rec 前对 180° 裁剪翻转——**实测一张完全倒置文档 16 行全部检测为 180° 并校正，识别为正确中文，avgConf 0.976**（upright 0.974）。**竖排/侧向**：高宽比 > `verticalAspect`(默认 1.5) 的框额外尝试 90°cw/ccw 旋转，按识别置信度取最优（侧向标签/旋转文本鲁棒，成本仅作用于少数高框）。新增纯函数 `rotateImageData180` / `rotateImageData90(dir)` / `interpretClsOutput`（单测：180 自逆、90 维度互换+角点映射、cls 阈值分支）。**质量把控**：`runPaddlePipeline` 返回 `quality`（`lineCount`/`averageConfidence`/`minConfidence`/`lowConfidenceLines`/`rotatedLines`/`grade` high·medium·low），`enhanceWithOCR` 把 `result.quality` 写入 `metadata.modelReview.ocrQuality`；与既有 per-line confidence + `detectOCRLowConfidence` validator + P9-C OCR 回读检验三条质量链协同。`dbPostProcess` 描述更新（含 unclip）。`browser-transformer` export 三个新函数。`scripts/paddle-ocr-pipeline-test.js` 加旋转/ cls/质量三组断言（共 12 组）。本轮**已解决** 180° 整体翻转 + 侧向高框；**仍受限** 强斜体/复杂艺术字（需 minAreaRect+透视纠偏的精确多边形框 + 更强 rec 模型，列为后续）。`npm test` 27 个脚本全量通过。 +- **2026-05-30 (PP-OCRv5 推理管线真机调通 + unclip 修复)**：用 `onnxruntime-node`（+`pngjs`/`jpeg-js`，dev-only `--no-save`）在 Node 端跑真实 PP-OCRv5 det/cls/rec ONNX 实测调参。**验证结果**：rec 在 PaddleOCR 词图 `word_10.png` 上解出 "PAIN"，输出类别数 C=18385 与字典长度精确对齐（blank+18383+space）；det 在真实文档图上输出概率图、阈值化后找到 16 个文本框；预处理 RGB 通道 + `(x/255-0.5)/0.5` 归一化正确，无需 BGR。**关键修复**：`dbPostProcess` 原先输出连通域轴对齐 bbox 但**缺 PP-OCR 的 unclip 外扩**，导致裁剪框过紧切掉字符笔画 → 全图识别错乱（avgConf 0.41、CJK 乱码）。加入 unclip（`distance = area*ratio/perimeter` 向外扩，`unclipRatio` 默认 1.6）后，整张产品标签文档识别为**连贯正确中文**（avgConf 0.978：「纯臻营养护发素 / 产品信息/参数 / 【品名】：纯臻营养护发素 / 【净含量】：220ml / 【主要成分】：鲸蜡硬脂醇、燕麦β-葡聚糖…」）。`paddle-ocr-pipeline.js` `dbPostProcess` 加 `unclipRatio` 参数 + 外扩逻辑。`scripts/paddle-ocr-pipeline-test.js` DB 断言用 `unclipRatio:0` 校验精确 bbox + 新增外扩断言。新增 `scripts/paddle-ocr-integration-test.js`：onnxruntime-node 跑真实 rec 解 fixture `samples/ocr/word-PAIN.png` 断言 "PAIN" + C 对齐 dict；缺依赖/模型/fixture **优雅跳过 exit 0**（默认 CI 不因缺 dev-dep 失败），接入 `npm test`（第 27 个）。本机实测 rec 0.991 置信度。本轮**确认整条 PP-OCRv5 管线对真实模型正确**；剩 cls 角度旋转校正、minAreaRect+unclip 精确多边形框（当前轴对齐 + 比例外扩已足够好）。`npm test` 27 个脚本全量通过。 +- **2026-05-30 (LaTeX 数学渲染)**：新增 `$...$`（行内）/ `$$...$$`（块级）LaTeX 数学渲染。inline tokenizer（`public/formats/inline-tokens.js`）在转义处理**之前**识别数学定界符，内容逐字保留（不递归、不转义，避免 `\frac`/`\sum` 反斜杠被吃、`_` 被误判为 em）；行内启发式（定界符内侧非空白）排除 `$5 and $10` 货币误判。`public/core/models/semantic-inlines.js` 加 `createInlineMath` 工厂 + `math` 节点在 plainText/markdown/html 三处渲染：HTML 产出 `$tex$`（data-tex 携原始 tex 供 KaTeX，span 文本是带定界符 tex 作无 JS 兜底）；markdown 往返保真。vendor KaTeX v0.17.0（`katex.min.css` 23KB + `katex.min.js` 265KB + 20 个 woff2 字体 300KB，共 ~592KB）到 `public/vendor/katex/`。新增 `public/katex-render.js` `renderMathIn(root)`：用全局 `katex.render` 排版 `.t2f-math` span（同源 vendor，零网络；未加载到 katex 静默保留兜底）。`index.html` / `preview.html` head 加 katex css + defer js；`app.js`（三处预览渲染后）+ `preview.js` 调 `renderMathIn`。`scripts/local-security-test.js` `isLocalVendorAsset` 信任 katex vendor（其 http 字符串仅 W3C MathML/SVG 命名空间，非网络）。新增 `scripts/latex-math-test.js`（7 组：行内/块级 tokenization 反斜杠+下划线保真、货币排除、katex 可定位 span、md 往返、plainText+工厂、md→html 不产 ``）接入 `npm test`（第 26 个）。本轮真实数学排版在浏览器（KaTeX）；Node 侧覆盖 tokenization + 渲染产物。`npm test` 26 个脚本全量通过。 +- **2026-05-30 (P9-D 真实 PP-OCRv5 模型接入 + 开箱即用自动加载)**：把真实运行时与模型装上，让高级 OCR 真正可用（此前 P9-D.1~.4 是契约/运行时/管线骨架，无真实模型）。`npm install onnxruntime-web`（optionalDependency，1.26.0）；`scripts/sync-onnxruntime-vendor.js` 收紧为最小集合（只同步 `ort.min.mjs` + `ort-wasm-simd-threaded.jsep.{mjs,wasm}`，JSEP 构建同时支持 WebGPU/WASM，~25MB，剔除 ~68MB 冗余变体）。下载真实 **PP-OCRv5 mobile** ONNX（det 4.8MB / cls 0.58MB / rec 16.6MB）+ 字典（74KB）到 `public/vendor/paddleocr/`（来源 OnnxOCR 仓库的 PP-OCRv5 ONNX）。新增 `public/core/ocr/paddle-default-models.js`：`ensurePaddleDefaultModels()` 浏览器端幂等地 fetch 同源 `/vendor/paddleocr/` 模型 → 写入 `defaultOCRStorage`（IndexedDB）→ `markPaddleOcrVendorReady(true)` + `ensureProbe()`，让高级 OCR **无需手动导入开箱即用**；vendor 缺失静默跳过（仍可经安全中心手动导入）。`app.js` init 末尾 fire-and-forget 调用。`browser-transformer.js` export `ensurePaddleDefaultModels`。`.gitignore` 排除 `/public/vendor/onnxruntime/` 与 `/public/vendor/paddleocr/`（不入 git，由 vendor 脚本 + 本地下载重建，随应用打包）。`scripts/local-security-test.js`：`paddle-default-models.js` 加 ALLOWED + STRICT；`isLocalVendorAsset` 把 onnxruntime vendor 整目录视为可信（其 minified bundle 含 CDN 字符串无法静态剔除，零联网保证来自 `loadOnnxRuntime` 钉 `wasmPaths` 同源 + Tauri CSP `connect-src 'self'`）。`scripts/resource-budget-test.js` public/vendor 预算 6MB → 64MB（含 onnxruntime + PP-OCRv5 模型，附理由）。**真实 ONNX 推理只能在浏览器/WebGPU 跑**，Node 侧仍 mock/纯函数全覆盖；浏览器端到端实测见 `docs/PP_OCRV5_BROWSER_VERIFICATION.md`。`npm test` 25 个脚本全量通过。 +- **2026-05-29 (P9-D.4 高级 OCR 接入转换链 · 路由偏好)**：P9-D 收口，让 PP-OCRv5 在可用时优先于 tesseract。新增 spec `docs/superpowers/specs/2026-05-29-p9d4-ocr-route-preference-design.md`。`public/core/ocr/ocr-engine.js` `pickForTask` 改为**优先级感知**：候选按 `priority` 降序挑第一个 available（`priority` 缺省 0），无可用时回退末位（行为不变）。`paddle-ocr-engine.js` 加 `priority: 20`、`tesseract-engine.js` 加 `priority: 10`（placeholder 缺省 0）。PNG / 扫描 PDF stage（`enhanceWithOCR` / `runScannedPdfOCRStage`）经 `defaultOCRRegistry.pickForTask("ocr-text")` 自动选到可用的最高优先级引擎，**无需改动 stage 代码**。`scripts/ocr-baseline-test.js` 第 38 组（自建 registry 高优先级 available 胜出 + 可用低优先级胜过不可用高优先级 + 默认 registry 同时让 paddle/tesseract available → 选 paddleocr-v5、删 paddle 模型 → 回到 tesseract-zh-en）。本轮**不改** PNG/扫描 PDF stage、**不在** Node 跑真实 ONNX（真实模型端到端为浏览器手动）。至此 P9-D PP-OCRv5 本地高级 OCR 链路（契约 → 运行时 → 模型导入 → 推理管线 → 路由偏好）齐备。`npm test` 25 个脚本全量通过。 +- **2026-05-29 (P9-D.2.b PP-OCRv5 推理管线)**：实现 PP-OCRv5 真实推理管线，把 det/cls/rec 三段 ONNX 前向 + 经典前后处理串成 OCRResult。新增 spec `docs/superpowers/specs/2026-05-29-p9d2b-paddle-inference-pipeline-design.md`。新增 `public/core/ocr/paddle-ocr-pipeline.js`：纯函数 `parseCharDictionary`（blank@0 + 行 + 末尾空格）/ `preprocessForDetection`（ImageNet 归一化 + 32 倍数 + limit_side_len=960 + scaleW/H）/ `preprocessForRecognition`（高 48 + (x/255-0.5)/0.5）/ `dbPostProcess`（阈值二值化 + 4-连通域 BFS + 轴对齐 bbox + box 平均概率过滤 + 缩放回原图 + 上→下左→右排序）/ `ctcGreedyDecode`（逐时刻 argmax → 折叠连续重复 → 去 blank(0) → 映射字典 + 平均 conf）/ `cropImageData` / `resizeRgba`（最近邻）；编排器 `runPaddlePipeline({ ort, detSession, clsSession, recSession, imageData, dictionary, options })` → OCRResult（接受可注入 session，mock 可端到端测）。`paddle-ocr-engine.js` recognize 第三阶段：`loadOnnxRuntime` → `decodeImageToImageData`（Image+canvas，不用 fetch，遵守禁联网；Node 抛）→ 从 `_storage` 取 det/cls/rec buffer + 可选字典 `paddleocr/v5/dict.txt` → `createOcrSession` ×3 → `runPaddlePipeline` → finally 释放 session；Node 仍在 `loadOnnxRuntime` 前置拒绝（不会走到 decode）。`browser-transformer.js` export `runPaddlePipeline`/`parseCharDictionary`/`preprocessForDetection`/`preprocessForRecognition`/`dbPostProcess`/`ctcGreedyDecode`/`cropImageData`/`resizeRgba`/`DET_LIMIT_SIDE_LEN`/`REC_IMAGE_HEIGHT`。新增 `scripts/paddle-ocr-pipeline-test.js`（9 组：字典、det/rec 预处理形状与归一、resize/crop、DB 单/双连通域出框+排序、CTC 折叠去重去 blank、`runPaddlePipeline` 用 mock ort+session+合成图端到端解出 "HI"、参数校验）接入 `npm test`（第 25 个）。`scripts/local-security-test.js` `paddle-ocr-pipeline.js` 加 ALLOWED + STRICT。`scripts/local-model-direction-test.js` 守门加 `runPaddlePipeline`/`ctcGreedyDecode`。本轮**不做** cls 角度旋转校正（仅调用占位）、minAreaRect+unclip 高精度框、多栏阅读顺序；**不在** Node 跑真实 ONNX（mock 覆盖编排，真实模型端到端为浏览器手动）；**不接** 转换链/偏好排序（P9-D.4）。`npm test` 25 个脚本全量通过。 +- **2026-05-29 (P9-D.3 PP-OCRv5 模型导入与安全中心管理 + 冻结引擎 bug 修复)**：让用户能在安全中心把 PP-OCRv5 det/cls/rec ONNX 模型导入本地缓存，使 `paddleOcrEngine` 从 model-missing 走向就绪。复用 tesseract tessdata 的**本地导入**模式（项目禁联网/STRICT 守门禁止远程 URL，"按需下载"在本项目即用户本地导入，不做自动 fetch）。新增 spec `docs/superpowers/specs/2026-05-29-p9d3-paddle-model-management-design.md`。`public/security-center.js`：import `paddleOcrEngine`/`markPaddleOcrVendorReady`/`PADDLE_OCR_MODEL_FILES`；`renderModelCache` 对 `engine === "paddleocr"` 行调 `renderPaddleActions`（导入 det.onnx/cls.onnx/rec.onnx + 清除按钮）；新增 `importPaddleModel`（file picker → `arrayBuffer` → `sha256Hex` → `defaultOCRStorage.put("paddleocr/v5/")` → `paddleOcrEngine.ensureProbe()`；三件齐全才 `markPaddleOcrVendorReady(true)` + `STATUS_AVAILABLE`，否则 `STATUS_VERIFYING` 提示还需导入哪些）+ `missingPaddleFiles` + `clearPaddleModels`；click 委托加 `[data-import-paddle]`/`[data-clear-paddle]`。**修复潜伏 bug**：`paddleOcrEngine` 与 `tesseractOCREngine` 的就绪状态原存于 `Object.freeze` 后的实例属性（`_modelsReady`/`_tessdataReady`），`ensureProbe()` 赋值在 ES module 严格模式下抛 `Cannot assign to read only property`——这会让安全中心 tesseract/paddle 导入流程在浏览器静默失败（被 try/catch 吞成"导入失败"）。改为模块级可变变量持有就绪状态，引擎对象仍 `Object.freeze`。`scripts/ocr-baseline-test.js` 第 37 组（三件齐全 → isAvailable true、vendor off → false、删一件 → false）+ 第 11 组加 `ensureProbe` 不抛断言。`scripts/browser-smoke-test.js` 断言 `#modelCacheFileInput` 存在。`docs/MULTI_MODEL_ARCHITECTURE.md` P9-D.3 章节。本轮**不实现** det/cls/rec 推理 + CTC 解码（P9-D.2.b）、**不做** 自动远程下载（违反禁联网）、**不接** 转换链/偏好排序（P9-D.4）。`npm test` 24 个脚本全量通过。 +- **2026-05-29 (P9-D.2 onnxruntime-web vendor + 运行时加载骨架)**：在 P9-D.1 引擎骨架之上接入 PP-OCRv5 的 ONNX Runtime（同 P9-A.2 tesseract 的 vendor+骨架节奏）。新增 spec `docs/superpowers/specs/2026-05-29-p9d2-onnxruntime-vendor-design.md`。新增 `scripts/sync-onnxruntime-vendor.js`（模仿 sync-tesseract-vendor：从 `node_modules/onnxruntime-web/dist/` 同步 `ort*.mjs` + `*.wasm` 到 `public/vendor/onnxruntime/`；缺包 exit 0 不阻塞）、`public/core/ocr/paddle-ocr-runtime.js`（`loadOnnxRuntime(vendorUrl)` dynamic import 同源 vendor ORT、设 `ort.env.wasm.wasmPaths` 同源、Node 抛 `OCR_VENDOR_LOAD_FAILED`；`pickExecutionProviders()` 检测 `navigator.gpu` → `["webgpu","wasm"]` 否则 `["wasm"]`；`createOcrSession({ ort, modelBuffer, providers })` / `disposeOcrSession` / `resetOnnxRuntimeCache` 骨架；`PADDLE_VENDOR_PATHS`）。`paddle-ocr-engine.js` recognize 第三阶段改为经 `pickExecutionProviders()` + `await loadOnnxRuntime()`，浏览器装好 vendor + 模型后以 `pipeline-not-wired`（`OCR_ENGINE_FAILED`）拒绝（det/cls/rec 推理 + CTC 解码留 P9-D.2.b）；Node 在 model-missing 前置拒绝。`package.json` 加 `onnxruntime-web@^1.20.1` optionalDependency + `vendor:onnx` script + `release:prepare` 加入 onnx vendor sync。`browser-transformer.js` export `loadOnnxRuntime`/`pickExecutionProviders`/`createOcrSession`/`disposeOcrSession`/`resetOnnxRuntimeCache`/`PADDLE_VENDOR_PATHS`。`scripts/local-security-test.js` `isLocalVendorAsset` 识别 `public/vendor/onnxruntime/` + `paddle-ocr-runtime.js` 加 ALLOWED + STRICT。`scripts/local-model-direction-test.js` multiModel 守门加 `onnxruntime-web`。`scripts/ocr-baseline-test.js` 第 36 组（`pickExecutionProviders` Node 返回 `["wasm"]` + `loadOnnxRuntime` Node 抛 `OCR_VENDOR_LOAD_FAILED` + 模拟 vendor+模型就位后 recognize 经运行时加载抛 `OCR_VENDOR_LOAD_FAILED`）。Tauri CSP 已含 `wasm-unsafe-eval` + `worker-src blob:` + `connect-src 'self'`，无需改动。本轮**不实现** det/cls/rec 推理管线 + CTC 解码（P9-D.2.b，需真实模型 + 字典）、**不做** 模型按需下载/UI（P9-D.3）、**不接** 转换链/偏好排序（P9-D.4）、**不强制安装** onnxruntime-web（仅 optionalDependency）。`npm test` 24 个脚本全量通过。 +- **2026-05-29 (P9-D 高级 OCR 方向调研 + P9-D.1 PP-OCRv5 引擎骨架)**：调研核实 DEVELOPMENT_TASKS 原命名「PaddleOCR-VL / MinerU」在本项目硬约束（浏览器/Tauri 本地 + 零云端 + 30–80MB 轻量默认包 + 无 Python runtime）下不可内嵌——PaddleOCR-VL（0.9B VLM）无成熟 ONNX/WebGPU 路径、需 ~500MB + 1–2GB VRAM 或 vLLM 服务；MinerU 是 Python/PyTorch/vLLM 工具。**经用户确认**把 P9-D 高级 OCR 内置目标改为 **PP-OCRv5（ONNX Runtime + WebGPU，WASM 回退）**，VLM 标注为远期/外部资源。新增调研 spec `docs/superpowers/specs/2026-05-29-p9d-advanced-ocr-research.md`（含来源链接）+ 子阶段 spec `2026-05-29-p9d1-paddle-ocr-skeleton-design.md`。P9-D.1 按骨架先行落地：新增 `public/core/ocr/paddle-ocr-engine.js`（`paddleOcrEngine` id `paddleocr-v5`，taskCapabilities `["ocr-text","ocr-layout"]`，manifestId `ocr-text.paddleocr.v5`；`isAvailable()` = vendorReady(`__t2fPaddleOcrVendorReady`) && det/cls/rec 模型在本地缓存，Node 恒 false；`recognize()` 三阶段拒绝 vendor-not-ready / model-missing / runtime-not-wired；`markPaddleOcrVendorReady` + `ensureProbe`；**不引入 onnxruntime、不实跑推理**）、`public/core/ocr/paddle-ocr-bootstrap.js`（在 tesseract 之后注册 engine + 注册 PP-OCRv5 ONNX ModelManifest `engine:"paddleocr"`/int8/det/cls/rec perFile 占位到 `defaultModelCache`，状态 not-downloaded）。`browser-transformer.js` 顶层 import paddle-bootstrap + export `paddleOcrEngine`/`PADDLE_OCR_MANIFEST_ID`/`PADDLE_OCR_MODEL_FILES`/`markPaddleOcrVendorReady`/`ensurePaddleOcrBootstrap`。`scripts/ocr-baseline-test.js` 两处 pickForTask 回退集合断言加 `paddleocr-v5` + 新增第 35 组 paddle 骨架断言（注册/isAvailable false/manifest 登记/recognize vendor-not-ready+model-missing 两阶段拒绝）。`scripts/local-security-test.js` 两模块加 ALLOWED + STRICT。`scripts/local-model-direction-test.js` multiModel 守门加 `PP-OCRv5`/`ONNX`/`WebGPU`/`paddleOcrEngine`（保留既有「不默认内置 PaddleOCR-VL/MinerU」负断言）。方向文档 `MULTI_MODEL_ARCHITECTURE`/`CONVERSION_ROUTING`/`DESKTOP_APP_ARCHITECTURE`/`DESKTOP_RELEASE_PLAN`/`RESOURCE_BUDGET`/`PRODUCT_STRATEGY` 统一改为「PP-OCRv5 内置 + VLM 远期/外部」（保留「默认包不含 GB 级模型」表述）。本轮**不接** onnxruntime 运行时（P9-D.2）/ 模型按需下载 UI（P9-D.3）/ 转换链接入与偏好排序（P9-D.4）/ VLM 内嵌 / Python sidecar。`npm test` 24 个脚本全量通过。 +- **2026-05-29 (P9-C.4 转换检验结果 UI)**：把 P9-C.1/2/3 算出但一直被前端丢弃的三层检验结果呈现给用户。此前 `transformContent` 转换后只用 `toConversionDocumentModel` 重建 model 渲染基础信息，`result.quality`（含 `qualityReport.{ruleDiff,ssim,ocrReadback}` + `verification` envelope + `autoRepair`）被丢弃；底部抽屉面板又已在 UI-A 前移除，核心差异化能力「转换后检验」对用户不可见。新增 spec `docs/superpowers/specs/2026-05-29-p9c4-verification-ui-design.md`。`public/index.html` 在 `#outputPreviewPanel` 内新增 `#verificationReportPanel`（`
` 折叠面板，默认 hidden）：自动修复结论 + 规则 diff / SSIM / OCR 回读三层逐行（命中显示 fidelity/score/f1 等指标，未命中显示 `verification.skipped[].reason`）+ warnings 按 severity 计数 + badge 显示已检验层数。`public/app.js` 新增 `renderVerificationReport(quality)`（用 `textContent` 写入防 XSS，`describeRuleDiff`/`describeSsim`/`describeOcrReadback` 分层描述，`data-state=ok/drift/skip` 驱动配色）+ `currentConversionQuality` 状态；`transformContent` 捕获 `result.quality` 并在文本/二进制路径前统一渲染；`resetGeneratedOutput` 清空面板。`public/styles.css` 加 `.verification-report` / `.verification-row` / `.verification-badge` 规则（slate+teal + `:has()` 左边框着色）。`scripts/browser-smoke-test.js` 断言 `#verificationReportPanel` 存在，且已移除的底部抽屉负断言（`bottomReportPanel`/`warningsPanel`/`qualityReportPanel`/`diffPanel`/`versionsPanel`）仍成立。本轮**不复活** 旧抽屉、**不改** 转换核心 / verification-stage / format-registry、**不入库** 真实渲染 fixture、**不引入** 新依赖。`npm test` 24 个脚本全量通过。 +- **2026-05-29 (优质测试样例语料生成器)**：新增覆盖全部受支持格式、复杂排版、大小不一（large ≥ 3MB）的程序化样例语料，用来压力测试转换、版面与三层检验能力。新增 `scripts/lib/sample-content.js`（纯函数确定性内容 builder：`buildComplexMarkdown` / `buildComplexHtml` / `buildComplexJson` / `buildComplexXml` / `buildComplexCsv` / `buildComplexText`，覆盖多级标题/嵌套列表/任务项/对齐表格/多语言代码块/嵌套引用/脚注/图片/CJK/RTL/emoji/实体；`SIZE_TIERS` small/medium/large + `buildToTargetBytes` 逼近目标字节）、`scripts/lib/png-encode.js`（node:zlib 最小 PNG 编码器 + `buildPatternPng`）、`scripts/generate-samples.js`（CLI：md/html/txt/json/xml/csv 直接产出，docx/pptx/epub/pdf/xlsx 经项目 writer 产出，png 编码；`--tiers` / `--out` 参数；写 `MANIFEST.json` 含 coverageGaps 登记 doc/ofd 无 writer）。输出到 `samples/generated/`（加入 `.gitignore`，不入库，符合 `samples/fixtures/README.md` 程序化 fixture 政策）。实测 large 层：md/html/txt/json/xml/csv 均 ≥3MB，docx 13.6MB、pdf 19.4MB、xlsx 16MB、epub 4.9MB。新增 `scripts/sample-corpus-test.js`（8 组断言：builder 确定性 + size scaling + 复杂结构覆盖 + CSV 边界字段 + md/csv 跨全矩阵可读性 + PNG 签名/尺寸 + buildToTargetBytes 逼近）纳入 `npm test`。`package.json` 加 `samples:generate` script。`samples/fixtures/README.md` 补程序化语料章节。本轮**不入库** 任何大样例/二进制（gitignore + 政策一致）、**不改** 转换核心/writer、**不引入** 新 npm 依赖（PNG 用 node:zlib 内置）；pptx writer 不随内容放大（已知 writer 限制，文件仍有效）、doc/ofd 无 writer 在 MANIFEST 登记缺口。`npm test` 24 个脚本全量通过。 +- **2026-05-29 (P9-C.3 转换后检验三层 · OCR 回读层 + 三层收口)**：落地第三层 OCR 回读，转换后检验三层（rule-diff + SSIM + OCR 回读）齐备。先写 spec `docs/superpowers/specs/2026-05-29-p9c3-ocr-readback-design.md`。新增 `public/core/verification/ocr-readback.js`：`compareText(original, recognized)` 纯函数零依赖（字符级多重集 recall/precision/f1 + `normalizeText` NFKC+小写+去空白，跨中英文与 OCR 噪声稳健，无需分词）+ `extractModelText(model)`（拼接 heading/paragraph/quote/list/table/code/content 文本）+ `runOcrReadbackLayer({ model, output, ctx, engine?, rasterizer? })`（资格 `ctx.to === "pdf"` 且原文非空 且 OCR engine 可用；经 OCR `defaultPdfPageRasterizer` 栅格化输出 PDF → `engine.recognize({ image: dataUrl })` → `compareText` → `qualityReport.ocrReadback = { recall, precision, f1, threshold, passed, engineId, originalLength, recognizedLength, averageConfidence, pageIndex }`；低于阈值默认 f1≥0.7 发 info `OCR_READBACK_DRIFT`；engine 不可用→eligible:false reason `ocr-engine-unavailable`、rasterizer 不可用→`rasterizer-unavailable`、recognize 抛错→`OCR_READBACK_FAILED` info；均不抛不阻塞）。常量 `DEFAULT_OCR_READBACK_THRESHOLD`。`verification-stage.js` `runVerificationStageAsync` 末尾 dynamic import `ocr-readback.js` 跑第三层（避免同步 convert 路径加载 OCR 模块），合并 `layers`/`skipped`/`warnings` + `ocrReadback` 字段。`format-registry.js` `_assembleQuality` 增 `ocrReadback: verification.ocrReadback ?? null`（同步路径恒 null）。`browser-transformer.js` 顶层 export `compareText`/`normalizeText`/`extractModelText`/`runOcrReadbackLayer`/`OCR_READBACK_DRIFT`/`OCR_READBACK_FAILED`/`DEFAULT_OCR_READBACK_THRESHOLD`。新增 `scripts/ocr-readback-test.js`（13 组断言：compareText 相同/子集/CJK/空、normalizeText、extractModelText、runOcrReadbackLayer stub 端到端/drift warning/非 pdf 不 eligible/engine 不可用/rasterizer 不可用、runVerificationStageAsync 三层合并 Node 下 ocr-readback skipped、convertContentAsync md→md ocrReadback=null）。`package.json` test 链在 `ssim-verification-test.js` 之后插入 `ocr-readback-test.js`。`scripts/local-security-test.js` `ocr-readback.js` 加 ALLOWED + STRICT。`scripts/local-model-direction-test.js` 守门加 `runOcrReadbackLayer`/`compareText`/`OCR_READBACK_DRIFT`。`docs/MULTI_MODEL_ARCHITECTURE.md` 新增「OCR 回读层」章节 + 三层齐备小结。本轮**渲染+OCR stub-only**（Node 无 canvas/tessdata，真实 OCR 回读端到端留给浏览器手动验证）、**不让** Repair Engine 消费 ocrReadback、**不做** 多页回读/逐块定位、**不引入** 新依赖、**不接** 高级 OCR（P9-D）、**不改** 同步 `convert()` 语义 / `options.repair === false` 短路 / UI。`npm test` 23 个脚本全量通过。 +- **2026-05-29 (P9-C.2 转换后检验三层 · SSIM 视觉回环层)**：在 P9-C.1 envelope 之上落地第二层 SSIM 视觉对比，采用视觉回环语义（输入页 vs 输出页栅格化做结构相似度）。先写 spec `docs/superpowers/specs/2026-05-29-p9c2-ssim-visual-loopback-design.md`。新增 `public/core/verification/ssim.js`（纯函数零依赖：`rgbaToGrayscale` + `resampleGrayscale` box 重采样到公共网格 + `computeSSIM` 非重叠 8×8 窗口均值 SSIM，`SSIM_C1=6.5025`/`SSIM_C2=58.5225` + `compareImages` 两图归一后算分，`DEFAULT_TARGET_WIDTH=256`）、`public/core/verification/page-image-source.js`（像素源抽象：`defaultPageImageSource` Node 抛 `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE`、浏览器首次调用 dynamic import browser 实现；`setPageImageSource`/`resetPageImageSource` 注入；`RASTERIZABLE_FORMATS = {pdf,png}`）、`public/core/verification/page-image-source-browser.js`（PDF 经 `createBrowserPdfPageRasterizer` 得 dataUrl→`Image`→canvas→`getImageData`；PNG 直接 `Image`→canvas→`getImageData`）。`verification-stage.js` 增 `runSsimLayer({ ctx, output })`（资格判断 from/to ∈ {pdf,png}；取源图+输出图像素→`compareImages`→`qualityReport.ssim={score,threshold,passed,width,height,pageIndex,sourceFormat,outputFormat}`；低于阈值默认 0.85 发 info `SSIM_VISUAL_DRIFT`；image source 不可用→eligible:false reason `image-source-unavailable` 不抛）+ `runVerificationStageAsync`（同步 rule-diff 基底 + 异步 SSIM 合并 envelope）+ 常量 `SSIM_VISUAL_DRIFT`/`SSIM_SOURCE_UNAVAILABLE`/`DEFAULT_SSIM_THRESHOLD`。`format-registry.js` 抽出 `_runRepairCycle` + `_assembleQuality` 共享 helper，`convert()`（sync）走 `_wrapWithRepairCycle`（rule-diff，`qualityReport.ssim` 恒 null），`convertAsync()` 改走 `_wrapWithRepairCycleAsync`（rule-diff + SSIM）。`browser-transformer.js` 顶层 export `computeSSIM`/`compareImages`/`rgbaToGrayscale`/`resampleGrayscale`/`runVerificationStageAsync`/`runSsimLayer`/`defaultPageImageSource`/`setPageImageSource`/`resetPageImageSource`/`RASTERIZABLE_FORMATS`/`SSIM_VISUAL_DRIFT`/`VERIFICATION_IMAGE_SOURCE_UNAVAILABLE` 等。新增 `scripts/ssim-verification-test.js`（12 组断言：灰度/重采样/computeSSIM 相同图=1、黑白≈0、单调性、不同尺寸归一、runSsimLayer 注入 stub 端到端/drift warning/非视觉路径不 eligible、defaultPageImageSource Node 抛错、runVerificationStageAsync 合并双层、convertContentAsync 文本路径 ssim=null + 视觉路径 stub 填充 ssim）。`package.json` test 链在 `rule-diff-test.js` 之后插入 `ssim-verification-test.js`。`scripts/local-security-test.js` 三模块加 ALLOWED + STRICT。`scripts/local-model-direction-test.js` 守门加 `computeSSIM`/`runVerificationStageAsync`/`SSIM_VISUAL_DRIFT`。`docs/MULTI_MODEL_ARCHITECTURE.md` 新增「SSIM 视觉回环层」章节。本轮**渲染 stub-only**（Node 无 canvas，真实 PDF/PNG 渲染 fixture + 浏览器端 canvas 像素 wiring 端到端验证留给后续）、**不做** OCR 回读（P9-C.3）、**不引入** 新 npm 依赖、**不支持** OFD 源图/多页、**不改** 同步 `convert()` 语义 / `options.repair === false` 短路 / UI。`npm test` 22 个脚本全量通过。 +- **2026-05-29 (P9-C.1 转换后检验三层 · 规则 diff 层)**：把「转换后检验」核心差异化能力落第一层，并钉好三层统一数据契约。先写两份 spec：`docs/superpowers/specs/2026-05-29-p9c-three-layer-verification-design.md`（P9-C 总 spec：envelope `qualityReport.verification` = `{ eligible, layers, skipped, runtimeMs }` + 三层字段 `ruleDiff`/`ssim`/`ocrReadback` + 与 Repair Engine / RoutePlanner 关系 + 子阶段顺序）、`docs/superpowers/specs/2026-05-29-p9c1-rule-diff-design.md`（P9-C.1 子 spec）。新增 `public/core/verification/` 三模块：`block-fingerprint.js`（从 `repair-engine.js` 抽出 `blockFingerprint` / `modelFingerprint`，行为字节级不变；新增 `getBlockKey` 稳定对齐键 / `extractBlockFields` 字段子集 / `BLOCK_FIELDS_BY_TYPE` 常量；`ROUND_TRIP_FORMATS` 单一来源）、`rule-diff.js`（`diffSemanticDocs(original, readBack)` → `{ identical, blockCounts, changedBlocks, addedBlocks, removedBlocks, fidelity, overallScore }`；按 `getBlockKey` 对齐 + LCS-lite 二次启发对齐；字段级 deep-equal 分 minor/major severity；`fidelity` ∈ exact/minor-drift/major-drift/broken；`overallScore` 由 `MAJOR_WEIGHT=0.4`/`MINOR_WEIGHT=0.05`/`STRUCTURAL_PENALTY=0.5` 加权惩罚 clamp 到 [0,1]）、`verification-stage.js`（`runVerificationStage({ model, output, ctx })` 编排：资格判断 from/to ∈ text-canonical + `output.data` 为字符串；同格式直接 `ctx.read` 回读 diff，跨格式仅开 `md ↔ html` 回环（`prepareConversionModel` 反向 + `write` + `read`，repair:false 避免递归）；回读抛错发 `RULE_DIFF_READBACK_FAILED`、`fidelity !== "exact"` 发 `RULE_DIFF_DRIFT`，均 info 级不阻塞）。`repair-engine.js` 删本地 `blockFingerprint`/`modelFingerprint`/`ROUND_TRIP_FORMATS` 副本改 import 共享模块，`reverifyRoundTrip` / `roundTripDelta` 契约一字段未动。`format-registry.js` `_wrapWithRepairCycle` 在 Repair cycle 之后接 `runVerificationStage`，把结果叠到 `quality.qualityReport.ruleDiff` 与 `.verification`，verification warnings 经 `withWarnings` + `ensureDocumentAudit` 合回 metadata。`browser-transformer.js` 顶层 export `runVerificationStage` / `diffSemanticDocs` / `blockFingerprint` / `modelFingerprint` / `getBlockKey` / `extractBlockFields` / `BLOCK_FIELDS_BY_TYPE` / `ROUND_TRIP_FORMATS` / `MAJOR_WEIGHT` / `MINOR_WEIGHT` / `STRUCTURAL_PENALTY` / `RULE_DIFF_DRIFT` / `RULE_DIFF_READBACK_FAILED`。新增 `scripts/rule-diff-test.js`（10 组断言：diffSemanticDocs 相同/空白minor/语义major/heading-level major/缺多块 broken；runVerificationStage 回读相同/回读抛错/非 text-canonical 不 eligible；端到端 md→md identical、md→html 跨格式回环走通、md→pdf 不 eligible；共享指纹与 legacy 实现字节级等价）。`package.json` test 链在 `repair-engine-test.js` 之后插入 `rule-diff-test.js`。`scripts/local-security-test.js` 把三模块加入 ALLOWED + STRICT 白名单。`scripts/local-model-direction-test.js` 守门关键词加 `runVerificationStage` / `diffSemanticDocs` / `RULE_DIFF_DRIFT`（multiModel）+ `qualityReport.ruleDiff`（tasks）。`docs/MULTI_MODEL_ARCHITECTURE.md` 新增「转换后检验三层 · 规则 diff 层」章节。本轮**不做** SSIM 视觉对比（P9-C.2）/ OCR 回读（P9-C.3）；**不让** Repair Engine 消费 ruleDiff（避免循环依赖）；**不动** writer/reader 输出语义 / UI / `options.repair === false` 短路；**不引入** 新 npm 依赖；**不开** 除 md↔html 外的跨格式回环。`npm test` 21 个脚本全量通过。 - **2026-05-28 (P9-B OCR → FixedLayoutModel + 浏览器 rasterize 真实化)**：把 OCR 结果接到第三个规范模型 FixedLayoutModel 上、把浏览器/Tauri 端 PDF rasterize 开箱即用。新增 `public/core/ocr/ocr-to-fixed-layout.js`（`ocrResultToFixedLayoutPage` 按 bbox.y → bbox.x 排序 + 携带 confidence；`mergeOCRResultsToFixedLayout` 多页合并 + `metadata.readingOrder = "heuristic-yx"` + `metadata.ocr` 总览；复用 `createFixedLayoutModel` / `createPage` / `createTextRun`）、`public/core/ocr/pdf-rasterizer-browser.js`（`createBrowserPdfPageRasterizer`：dynamic import `/vendor/pdfjs/pdf.min.mjs` + `getDocument({ data })` → `page.getViewport` → `.toDataURL("image/png")`；失败抛 `OCR_RASTERIZER_FAILED` 含 cause）。改造 `public/core/ocr/pdf-rasterizer.js`：`defaultPdfPageRasterizer` 优先级 inject → 浏览器自动 → throw `OCR_RASTERIZER_UNAVAILABLE`；首次调用自动 `import("./pdf-rasterizer-browser.js")`，Node 检测 `globalThis.document?.createElement` 缺失即放弃；`resetPdfPageRasterizer` 同时清两个缓存。改造 `public/core/ocr/scan-pdf-stage.js`：收集每页 pageResult 数组 → `mergeOCRResultsToFixedLayout` → `model.fixedLayout = fixedLayout` → `fixedLayoutToSemantic` 派生 blocks → 发 `MODEL_VISUAL_FIDELITY_LOST` + `MODEL_TEXT_ORDER_HEURISTIC` info warning → `metadata.modelReview.ocr.fixedLayout = getFixedLayoutSummary(...)`；`metadata.ocr.lines` 保留供 Repair Engine validator 使用。`public/core/models/fixed-layout.js` `createTextRun` 加 `confidence`（clamp 到 [0,1]）+ `createPage` 加 `readingOrderHint`，不破坏现有 OFD / PDF reader 调用。`browser-transformer.js` 顶层 export `ocrResultToFixedLayoutPage` / `mergeOCRResultsToFixedLayout` / `READING_ORDER_HEURISTIC` / `createBrowserPdfPageRasterizer` / `MODEL_VISUAL_FIDELITY_LOST` / `MODEL_TEXT_ORDER_HEURISTIC` / `createFixedLayoutModel` / `createFixedLayoutPage` / `createFixedLayoutTextRun` / `createFixedLayoutBbox` / `getFixedLayoutSummary` / `fixedLayoutToSemantic`。`scripts/ocr-baseline-test.js` 扩展为 34 组断言（+`ocrResultToFixedLayoutPage` y/x 排序 + confidence 携带；`mergeOCRResultsToFixedLayout` 多页合并 + `getFixedLayoutSummary` 计数；`runScannedPdfOCRStage` stub 端到端后 `model.fixedLayout.pages.length === 2` + `MODEL_VISUAL_FIDELITY_LOST` + `MODEL_TEXT_ORDER_HEURISTIC` warning；`defaultPdfPageRasterizer` inject → auto-browser → throw 优先级）。`scripts/local-security-test.js` 把 `ocr-to-fixed-layout.js` + `pdf-rasterizer-browser.js` 加入 ALLOWED + STRICT 白名单。`scripts/local-model-direction-test.js` 守门关键词加 `ocrResultToFixedLayoutPage` / `mergeOCRResultsToFixedLayout` / `createBrowserPdfPageRasterizer` / `MODEL_TEXT_ORDER_HEURISTIC`。新 spec `docs/superpowers/specs/2026-05-28-p9b-ocr-fixedlayout-design.md`。本轮**不实现高级阅读顺序算法**（multi-column / heading detection 留给 P9-C/D；用 y → x 启发式 + warning）、**不入库真实扫描 PDF fixture**（继续用 stub）、**不动同步 convert() / PNG enhance / Repair Engine handlers / Tauri CSP / npm 依赖**。`npm test` 20 个脚本全量通过。 - **2026-05-28 (P9-A.4 扫描 PDF OCR 检测 + Rasterizer 骨架 + 多页 stage)**：把 OCR 扩展到扫描型 PDF 路径。新增 `public/core/ocr/pdf-rasterizer.js`（`isScannedPdf(content, options)` 启发式：基于 `expandPdfContentForTextExtraction` + 检测 `PDFJS_PAYLOAD_MARKER` + 字符阈值 300；无 payload → 扫描，有 payload 但 < 阈值 → 扫描；`PdfPageRasterizer` 抽象 + `defaultPdfPageRasterizer` Node 默认抛 `OCR_RASTERIZER_UNAVAILABLE`；`setPdfPageRasterizer(impl)` / `resetPdfPageRasterizer()` 让测试注入 stub）、`public/core/ocr/scan-pdf-stage.js`（`runScannedPdfOCRStage(model, ctx)`：拿 rasterizer + engine → countPages → 循环 rasterize 每页 → engine.recognize → 把多页 paragraph blocks 顺序追加到 model + `metadata.ocr.lines` 含 `pageIndex` / `blockId` + `metadata.modelReview.ocr` 总览 pageCount/lineCount/averageConfidence/runtimeMs；错误统一注入 `OCR_ENGINE_FAILED` warning 返回原 model；可选 `options.ocr.maxScanPages`（默认 5）/`dpi`/`scanPdfThreshold`）。`public/core/format-registry.js` `convertAsync` 新增 PDF 分支：检测扫描 PDF → dynamic import `runScannedPdfOCRStage` → 注入 OCR enhancement；文本 PDF 沿用 P8-B 既有路径。`browser-transformer.js` 顶层 export `isScannedPdf` / `runScannedPdfOCRStage` / `defaultPdfPageRasterizer` / `setPdfPageRasterizer` / `resetPdfPageRasterizer` / `OCR_RASTERIZER_UNAVAILABLE` / `OCR_RASTERIZER_FAILED`。`scripts/ocr-baseline-test.js` 扩展为 30 组断言（+isScannedPdf 对无 payload 最小 PDF 返回 scanned=true、defaultPdfPageRasterizer Node 抛 OCR_RASTERIZER_UNAVAILABLE、runScannedPdfOCRStage stub 端到端 2 页追加 + metadata.modelReview.ocr.pageCount=2、convertContentAsync PDF → txt 走 OCR 分支输出含 stub OCR 文本）。`scripts/local-security-test.js` 把 `pdf-rasterizer.js` / `scan-pdf-stage.js` 加入 ALLOWED + STRICT 白名单。`scripts/local-model-direction-test.js` 守门关键词加 `isScannedPdf` / `runScannedPdfOCRStage` / `defaultPdfPageRasterizer`。新 spec `docs/superpowers/specs/2026-05-28-p9a4-scan-pdf-ocr-design.md`。本轮**不实现真实浏览器端 pdfjs canvas 渲染**（留给 P9-B；defaultPdfPageRasterizer Node 默认抛错，浏览器/Tauri 通过 `setPdfPageRasterizer` 注入实现）、**不在仓库加扫描 PDF fixture**（用最小 PDF 头部 + stub rasterizer 覆盖代码路径）、**不动同步 convert() / PNG 异步 stage / Tauri CSP / npm 依赖**。`npm test` 20 个脚本全量通过。 - **2026-05-28 (P9-A.3 PNG 异步 OCR 接入 + Repair Engine OCR 入口)**：把 P9-A.2.b 提供的 `enhanceWithOCR` 接到 PNG 转换链路上、把 OCR 元数据接到 Repair Engine 上。新增 `public/core/ocr/ocr-stage.js`（`runOCRStage(model, ctx)` 包一层 `enhanceWithOCR` + 注入 `OCR_ENGINE_FAILED` 兜底；提供 `getDefaultOCRLanguage`）、`public/core/ocr/ocr-validator.js`（`detectOCRLowConfidence` 从 `metadata.ocr.lines` 取 confidence < 0.55 的行生成 `replaceTextRun` 候选；每页最多 8 条；evidence 含 engineId / language / bbox / pageIndex / lineIndex）。`public/core/ocr/png-ocr.js` 的 `enhanceWithOCR` 现在把 `pages[].lines` 一一写入 `model.metadata.ocr.lines`，含 `{ pageIndex, lineIndex, text, confidence, bbox, blockId }`，让 validator 能用 blockId 反查 paragraph。`public/core/format-registry.js` 抽出 `_buildRepairCtx` 与 `_wrapWithRepairCycle` 共享 helper，新增 `async convertAsync(...)`：与 `convert()` 同样的入口校验和 prepareConversionModel；当 `options?.ocr?.enabled !== false && fromFormat === "png"` 时 await dynamic-import `runOCRStage` 注入 OCR enhancement；之后走同一 `_wrapWithRepairCycle`。`public/core/repair-engine.js` 的 `createDefaultRepairEngine()` 注册 `detectOCRLowConfidence`（在 DEFAULT_VALIDATORS 之后）。`public/browser-transformer.js` 顶层 export `convertContentAsync` / `runOCRStage` / `getDefaultOCRLanguage` / `detectOCRLowConfidence`。`public/app.js` 的 `convertWithWorker(payload)` 在 worker 不可用时检测 `payload.from === "png"` 改走 `convertContentAsync`，其他格式仍走 `convertContent`。`samples/png/t2f-sample.data-url.txt`（80×24 灰度 PNG，白底黑字"T2F"，118 字节 base64 后约 182 字符）+ `samples/png/README.md` 说明用途与浏览器端真实 OCR 验证步骤。`scripts/ocr-baseline-test.js` 扩展为 26 组断言（+convertContentAsync 在 ocr.enabled=false 时返回 writer payload、stub engine 注册后输出文本包含 stub OCR 内容、runOCRStage 持久化 metadata.ocr.lines、detectOCRLowConfidence 对 confidence < 0.55 / >= 0.55 两种场景的行为、t2f-sample fixture 不抛错）。`scripts/local-model-direction-test.js` 守门关键词加 `convertContentAsync` / `runOCRStage` / `detectOCRLowConfidence`。新 spec `docs/superpowers/specs/2026-05-28-p9a3-async-ocr-pipeline-design.md`。本轮**不破坏现有同步 convert() / convertContent()**（所有 20 个测试脚本与 smoke-test 调用方完全不变），不做扫描 PDF，不修改 Tauri CSP，不引入新 npm 依赖，不真实跑 OCR 在 npm test（用 stub engine 覆盖代码路径）。`npm test` 20 个脚本全量通过。 @@ -131,5 +154,6 @@ - `npm test` - `git diff --check` - `npm run release:prepare` -- `git check-ignore -v release\trans2former-2.2.0\RELEASE_MANIFEST.json` +- `git check-ignore -v release\trans2former-2.3.0\RELEASE_MANIFEST.json` +- `npm run samples:generate`（按需生成覆盖全格式的复杂/大样例语料到 samples/generated/，能力压力测试用） - `npm run desktop:build`（Windows P7-A / 发布前安装包验证） diff --git a/README.md b/README.md index e2e0cee..e66ef2a 100644 --- a/README.md +++ b/README.md @@ -5,8 +5,8 @@ Trans2Former 是一个专业级的桌面文档转换工具，支持 12 种输入格式和 11 种输出格式的相互转换。所有转换在本地完成，零上传，保护您的数据隐私。 [![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](LICENSE) -[![Tests](https://img.shields.io/badge/smoke-46%20groups%20passing-brightgreen.svg)](#) -[![Version](https://img.shields.io/badge/version-2.2.0-blue.svg)](#) +[![Tests](https://img.shields.io/badge/tests-28%20scripts%20passing-brightgreen.svg)](#) +[![Version](https://img.shields.io/badge/version-2.3.0-blue.svg)](#) --- @@ -16,8 +16,9 @@ Trans2Former 是一个专业级的桌面文档转换工具，支持 12 种输入 - 🚀 **高性能** - 基于 Web Worker 的并行处理 - 📦 **零依赖** - 不需要安装 Office、LibreOffice 或 Pandoc - 🎨 **实时预览** - 转换前后实时预览文档 -- 📝 **结构化编辑** - 支持编辑转换后的文档结构 -- 🧩 **核心内置增强** - OFD、OCR、版面分析等能力代码核心内置；OCR 模型资源按需本地下载到 model-cache，不进入默认安装包 +- 🔤 **本地 OCR** - 图片 / 扫描 PDF 用内置 PP-OCRv5（ONNX Runtime + WebGPU）本地识别，含方向校正、倾斜纠偏、自适应去噪、版面结构（标题/段落）与质量评分 +- 🧮 **LaTeX 渲染** - 预览中用本地 KaTeX 排版 `$...$` / `$$...$$` 数学公式 +- ✅ **转换后检验** - 规则 diff + SSIM 视觉对比 + OCR 回读三层组合统一写入 QualityReport，工作台可视 - 🌍 **多语言** - 支持中英文、RTL 文本等 - ⚡ **无大小限制** - 不设置人为文件大小上限 @@ -120,23 +121,24 @@ Trans2Former/ - **批量转换** - 同时转换多个文件 - **编辑输出** - 直接编辑转换后的文本 - **版本历史** - 查看和恢复历史版本 -- **质量报告** - 查看转换质量和警告 -- **质量报告** - 查看转换质量和警告 +- **转换检验报告** - 规则 diff / SSIM / OCR 回读 + OCR 识别质量评分 --- ## 🧩 核心本地增强 -Trans2Former 不再提供插件安装模式，增强能力代码直接并入核心本地模块；默认安装包目标 30–80 MB，不内置 GB 级模型，相关模型资源按需本地下载到 model-cache： +Trans2Former 不再提供插件安装模式，增强能力代码直接并入核心本地模块；模型资源不进入 git 仓库，由 vendor 脚本 + 本地下载重建，随应用打包： -- **OFD 支持** - 政务格式支持 -- **本地 OCR** - 扫描文档识别（首次启用时下载本地 OCR 模型到 model-cache，识别全程本机执行） -- **版面分析** - 复杂布局识别 -- **表格恢复** - PDF 表格提取 -- **转换后检验** - 规则 diff + SSIM 视觉对比 + OCR 回读三层组合写入 QualityReport -- **高级 OCR**（规划中）- PaddleOCR-VL / MinerU 等大模型作为独立本地资源按需获取 +- **本地 OCR（PP-OCRv5）** - 图片 / 扫描 PDF 经 ONNX Runtime + WebGPU（WASM 回退）在本机识别；含 cls 方向校正（180°，可选模型）、任意角倾斜自动纠偏、自适应中值去噪、版面结构识别（按字号/间距归并标题+段落）、识别质量评分（grade / 置信度 / 低置信行 / 纠偏 / 去噪），全程零联网、零上传 +- **轻量 OCR（Tesseract.js）** - 可选的轻量 OCR 引擎，按需在安全中心导入 tessdata +- **转换后检验三层** - 规则 diff + SSIM 视觉对比 + OCR 回读统一写入 QualityReport，工作台「转换检验报告」可视 +- **LaTeX 数学渲染** - 本地 KaTeX，零联网 +- **OFD 支持 / 版面分析 / 表格恢复** - 核心内置，持续攻坚 +- **高级 OCR（远期）** - PaddleOCR-VL / MinerU 等 VLM 受浏览器/Tauri 本地运行时限制，作为远期/外部资源评估（详见 docs） -这些能力不通过插件包分发；后续实现必须继续保持本地执行、无上传、可解释降级和资源预算约束。 +> 运行高级 OCR：`npm install onnxruntime-web && npm run vendor:onnx`。PP-OCRv5 mobile 检测/识别模型与字典由 `npm run vendor:paddle` 从钉定来源下载、SHA-256 校验（见 [scripts/paddleocr-models.manifest.json](scripts/paddleocr-models.manifest.json)）并随 `release:prepare` 打包，启动自动载入、开箱即用；方向分类（cls）为可选，可在安全中心导入/替换。详见 [docs/PP_OCRV5_BROWSER_VERIFICATION.md](docs/PP_OCRV5_BROWSER_VERIFICATION.md)。 + +这些能力不通过插件包分发；实现继续保持本地执行、无上传、可解释降级和资源预算约束。 --- @@ -160,14 +162,14 @@ Trans2Former 严格遵守本地优先原则： npm test ``` -测试覆盖： -- ✅ 核心转换测试（44/44 通过） -- ✅ 快照测试 -- ✅ 格式能力审计 -- ✅ 安全测试 -- ✅ 资源预算测试 -- ✅ 本地安全测试 -- ✅ 发布就绪测试 +测试覆盖（28 个脚本全量通过）： +- ✅ 核心转换 / 快照 / 格式能力审计 +- ✅ 转换检验三层（规则 diff / SSIM / OCR 回读） +- ✅ OCR 管线（预处理 / DB 后处理 / CTC 解码 / 方向 / 倾斜 / 去噪 / 结构）+ 真实模型集成（onnxruntime-node，缺依赖优雅跳过） +- ✅ LaTeX 数学 tokenization +- ✅ 安全 / 资源预算 / 方向门禁 / 发布就绪 + +> 复杂/大体积样例语料：`npm run samples:generate` 程序化产出覆盖全格式、大小不一（large ≥ 3MB）的测试样例到 `samples/generated/`（gitignore）。 --- @@ -221,7 +223,7 @@ npm test 1. **复杂样式** - 部分复杂样式可能无法完全保留 2. **图表动画** - PPTX 动画和图表需要后续核心增强 -3. **扫描 PDF** - 扫描文档需要后续核心 OCR 能力 +3. **OCR 难例** - 强斜体 / 复杂艺术字识别仍受限（常规、倾斜、倒置、带噪文档已支持）；真实 ONNX 推理在浏览器 / Tauri（WebGPU/WASM）执行 4. **ZIP64** - 暂不支持超大 ZIP 文件 这些限制将在后续版本中通过核心本地模块逐步解决。 @@ -231,20 +233,19 @@ npm test ## 🗺️ 路线图 ### 已完成 ✅ -- [x] P0-P8 核心功能 -- [x] 12 种输入格式 -- [x] 11 种输出格式 -- [x] 核心本地能力路线 -- [x] 桌面发布准备 +- [x] P0-P8 核心功能 + 12 种输入 / 11 种输出格式 +- [x] 转换后检验三层（规则 diff + SSIM + OCR 回读）+ 工作台可视 +- [x] 本地 OCR（PP-OCRv5：识别 + 方向校正 + 倾斜纠偏 + 去噪 + 版面结构 + 质量评分） +- [x] LaTeX 数学渲染（KaTeX） +- [x] Windows 桌面发布（MSI / NSIS） ### 进行中 🚧 -- [ ] 平台安装包构建 -- [ ] SSIM 视觉对比 -- [ ] 性能优化 +- [ ] 跨平台安装包（macOS / Linux）+ 签名公证 +- [ ] OCR 表格结构识别 → Markdown 表格 ### 计划中 📋 -- [ ] 本地 OCR 核心增强 -- [ ] 版面分析核心增强 +- [ ] 强斜体 / 艺术字识别增强 +- [ ] 高级 OCR（PaddleOCR-VL / MinerU）本地运行时评估 - [ ] 更多格式支持 --- diff --git a/RELEASE_NOTES_v2.3.0.md b/RELEASE_NOTES_v2.3.0.md new file mode 100644 index 0000000..016c73d --- /dev/null +++ b/RELEASE_NOTES_v2.3.0.md @@ -0,0 +1,47 @@ +# Trans2Former v2.3.0 + +本地优先的多格式文档转换器。本版把**本地 OCR**从骨架做到真机可用，新增 **LaTeX 数学渲染**与**转换后检验三层可视化**，全程零上传、零联网。 + +## 新增 + +### 本地 OCR（PP-OCRv5） +图片 / 扫描 PDF 经 **ONNX Runtime + WebGPU**（WASM 回退）在本机识别，应用内置一套 PP-OCRv5 mobile 模型，启动自动载入、开箱即用，可在安全中心导入/替换。完整管线： + +- 图像预处理 + **DB 检测后处理（连通域 + unclip 外扩）** + **CTC 解码 + 字典对齐** +- **方向校正**（cls 180°）、**竖排/侧向 90° 试转** +- **任意角倾斜自动纠偏**（错切投影估角 → 旋正重检） +- **自适应去噪**（仅噪图去噪，干净图不受影响） +- **版面结构识别**（按字号/间距归并为标题 + 段落 + 阅读顺序） +- **识别质量评分**（grade / 置信度 / 低置信行 / 纠偏 / 去噪），工作台「转换检验报告」可视 + +> 真机实测：rec 解词图为 "PAIN"；产品标签 0.978；倒置文档 0.976；+10° 倾斜 8→16 行恢复至 0.970；15% 椒盐噪点 4→16 行恢复。 + +### LaTeX 数学渲染 +`$...$` / `$$...$$` 受保护识别（反斜杠 / 下划线逐字保留，货币不误判），预览用本地 **KaTeX** 排版，零联网。 + +### 转换后检验三层 +规则 diff + SSIM 视觉对比 + OCR 回读，统一写入 `qualityReport` 并在工作台可视；核心算法零依赖、纯函数。 + +### 其他 +- 轻量 OCR（Tesseract.js）可选引擎 + 优先级路由 +- Repair Engine + 按需模型缓存（manifest / SHA-256 / 安全中心导入） +- `npm run samples:generate`：全格式、大小不一（≥3MB）测试样例语料生成器 + +## 修复 + +- 首页空白（缺 `getKnownInputFormats` re-export） +- OCR 实际不触发（转换绕过 OCR 异步管线） +- 冻结引擎导致安全中心模型导入静默失败 +- OCR 识别质量被 Repair Engine 覆盖丢失 + +## 方向调整 + +高级 OCR 内置目标从 **PaddleOCR-VL / MinerU（VLM）** 调整为 **PP-OCRv5（ONNX/WebGPU）**——VLM 在浏览器/Tauri 本地 + 零云端 + 轻量默认包约束下不可内嵌，标注为远期/外部资源。 + +## 升级指南 + +从 v2.2.x 升级：直接覆盖部署即可，无破坏性 API 变更。运行高级 OCR 需 `npm install onnxruntime-web && npm run vendor:onnx`（应用已内置 PP-OCRv5 模型，开箱即用）。 + +## 全部测试通过 + +`npm test` 全套 **28 个脚本**通过；`git diff --check`、`npm run release:prepare` 通过。Windows MSI / NSIS 安装包经真实 `npm run desktop:build` 产出。 diff --git a/docs/CONVERSION_ROUTING.md b/docs/CONVERSION_ROUTING.md index 3dd0fcb..3757af0 100644 --- a/docs/CONVERSION_ROUTING.md +++ b/docs/CONVERSION_ROUTING.md @@ -150,6 +150,6 @@ P8-B 的首批执行链已闭环。后续按 2026-05-28 [lightweight-default-bun - **P9-A OCR 基线**：PNG 与扫描 PDF 接入轻量 OCR（Tesseract.js / 轻量 PaddleOCR），OCR 模型资源按需下载到 model-cache，不进入默认安装包。 - **P9-B OCR → FixedLayoutModel**：OCRResult → FixedLayoutModel → SemanticDoc，保留 bbox / confidence / page index / reading order，让 Repair Engine 的 `fixedLayoutToSemantic` 路径获得真实证据。 - **P9-C 转换后检验**：规则 diff + SSIM 视觉对比 + OCR 回读三层组合统一写入 QualityReport，作为核心差异化能力提升。 -- **P9-D 高级 OCR**：PaddleOCR-VL / MinerU 等大模型作为独立本地资源按需下载，明确体积、运行内存、降级路径。 +- **P9-D 高级 OCR**：内置目标为 PP-OCRv5（ONNX Runtime + WebGPU，WASM 回退），作为比 Tesseract 更高精度的本地 OCR engine 按需下载 ONNX 模型；PaddleOCR-VL / MinerU 等 VLM 为远期/外部资源（浏览器/Tauri 本地暂不可内嵌）。 在 P9-A 启动前必须先完成 **S3 按需下载与本地缓存治理**：定义 model-cache 目录结构、manifest、checksum、可清理入口、断网降级提示和首次启用下载提示流程。`slide` / `fixedLayout` 路径的 writer 能力和视觉质量证据在 P9-B/C 推进过程中补齐；在证据成立前不将规划边提升为实际 mapper 执行。 diff --git a/docs/DESKTOP_APP_ARCHITECTURE.md b/docs/DESKTOP_APP_ARCHITECTURE.md index 03e5042..331201d 100644 --- a/docs/DESKTOP_APP_ARCHITECTURE.md +++ b/docs/DESKTOP_APP_ARCHITECTURE.md @@ -133,7 +133,8 @@ Tauri + Web-GUI 是当前最合理的桌面路线。 | 重格式 | 核心本地按需加载 | | 默认安装包 | 30–80 MB，不打包 GB 级模型 | | OCR 模型 | 不进入默认安装包；首次启用时本地下载到 model-cache，可清理、可禁用 | -| 高级 OCR（PaddleOCR-VL / MinerU 等） | 独立本地资源，按需获取，明确体积与硬件要求 | +| 高级 OCR（PP-OCRv5 ONNX/WebGPU） | 内置目标：比 Tesseract 更高精度的本地 OCR engine，按需下载 ONNX 模型到 model-cache | +| VLM（PaddleOCR-VL / MinerU 等） | 远期/外部资源；浏览器/Tauri 本地暂不可内嵌，明确体积与硬件要求 | ## 当前实现 diff --git a/docs/DESKTOP_RELEASE_PLAN.md b/docs/DESKTOP_RELEASE_PLAN.md index 55a0513..994efd1 100644 --- a/docs/DESKTOP_RELEASE_PLAN.md +++ b/docs/DESKTOP_RELEASE_PLAN.md @@ -76,7 +76,7 @@ Trans2Former__checksums.sha256 - OCR 模型资源不进入默认安装包；首次启用时本地下载到 model-cache，必须提供 manifest、checksum、缓存路径、可清理入口、体积报告、断网降级提示和失败 fallback，处理过程不上传任何文档内容。 - `release:prepare` 必须依次执行 `sync-pdfjs-vendor` 与 `sync-tesseract-vendor`；后者在 `tesseract.js` optionalDependency 缺失时退出 0，不阻塞 CI/发布流程。 - Tauri CSP 必须保留 `'wasm-unsafe-eval'`（让本地 tesseract.js wasm 在 WebView 中可实例化），且 `connect-src 'self'` 不可放开 —— 模型资源仅同源 vendor 与本地 IndexedDB，禁止任何远程 URL。 -- 高级 OCR 资源（PaddleOCR-VL / MinerU 等大模型）作为独立本地资源按需获取，启用前展示体积、运行内存、降级路径和失败提示。 +- 高级 OCR 内置目标为 PP-OCRv5（ONNX Runtime + WebGPU，WASM 回退），ONNX 模型按需下载到 model-cache，启用前展示体积、运行内存、降级路径和失败提示；PaddleOCR-VL / MinerU 等 VLM 为远期/外部资源（浏览器/Tauri 本地暂不可内嵌）。 - 转换后检验三层（规则 diff、SSIM 视觉对比、OCR 回读）必须可在断网状态运行，验证 Repair Engine 修复后的输出质量并写入 QualityReport。 - 文档处理模式始终禁止网络访问。 diff --git a/docs/MULTI_MODEL_ARCHITECTURE.md b/docs/MULTI_MODEL_ARCHITECTURE.md index 6d691fa..514b220 100644 --- a/docs/MULTI_MODEL_ARCHITECTURE.md +++ b/docs/MULTI_MODEL_ARCHITECTURE.md @@ -220,6 +220,59 @@ S2 已落地为 `public/core/repair-engine.js`、`public/core/repair-actions.js` - `createTextRun` 新增 `confidence` 字段（clamp 到 [0,1]）；`createPage` 新增 `readingOrderHint` 字段。 - 不实现高级阅读顺序（multi-column / heading detection）——留给 P9-C / P9-D。 +### 转换后检验三层 · 规则 diff 层（P9-C.1 落地） + +转换后检验是项目核心差异化能力，三层组合（规则 diff + SSIM 视觉对比 + OCR 回读）统一写入 `qualityReport`。P9-C.1 落地第一层规则 diff 与统一编排骨架： + +- `runVerificationStage({ model, output, ctx })` (`public/core/verification/verification-stage.js`)：在 Repair Engine `runCycle` 之后跑的独立验证阶段，只读不改 output，结果写入 `qualityReport.ruleDiff` 与 `qualityReport.verification` envelope（`eligible / reason / layers / skipped / runtimeMs`）。层名列表 `layers` 当前只含 `"rule-diff"`，P9-C.2 加 `"ssim"`、P9-C.3 加 `"ocr-readback"`。 +- `diffSemanticDocs(original, readBack)` (`public/core/verification/rule-diff.js`)：在原始 SemanticDoc 与 writer→reader 回读 model 之间做字段级 diff，输出 `{ identical, blockCounts, changedBlocks, addedBlocks, removedBlocks, fidelity, overallScore }`。`fidelity` ∈ `exact / minor-drift / major-drift / broken`；`overallScore` 由 `MAJOR_WEIGHT / MINOR_WEIGHT / STRUCTURAL_PENALTY` 加权惩罚算出。 +- 共享指纹模块 `public/core/verification/block-fingerprint.js`：`blockFingerprint` / `modelFingerprint`（从 Repair Engine 抽出，行为不变）+ `getBlockKey` / `extractBlockFields` / `BLOCK_FIELDS_BY_TYPE` 字段子集 + `ROUND_TRIP_FORMATS` 单一来源。Repair Engine 的 `reverifyRoundTrip` / `roundTripDelta` 改 import 共享 `modelFingerprint`，作为粗粒度兼容层与细粒度 `ruleDiff` 并存。 +- 资格判断：from/to 都在 text-canonical 集合（md/html/json/csv/txt/xml）且 `output.data` 为字符串才跑；同格式直接回读 diff，跨格式仅首批开放 `md ↔ html` 回环；其余 writer（PDF/DOCX/XLSX/PPTX/PNG/OFD/EPUB）记 `eligible: false, reason: "writer-not-text-canonical"`，不阻塞转换。 +- 失败兜底：回读抛错发 `RULE_DIFF_READBACK_FAILED`（info）；`fidelity !== "exact"` 发 `RULE_DIFF_DRIFT`（info），details 含 from/to/fidelity/score/added/removed/changed 摘要。 +- 本阶段不让 Repair Engine 消费 `ruleDiff`（避免循环依赖），UI 验证卡片留给 P9-C.2 落地后统一做。 + +### 转换后检验三层 · SSIM 视觉回环层（P9-C.2 落地） + +第二层 SSIM 视觉对比采用**视觉回环**语义：对视觉保真型输入（PDF / PNG），把输入页与输出页各自栅格化为像素做结构相似度对比，写入 `qualityReport.ssim`，衡量「这次转换是否保住视觉外观」。 + +- `computeSSIM(grayA, grayB, width, height, opts)` (`public/core/verification/ssim.js`)：纯函数、零依赖、非重叠窗口均值 SSIM（C1=6.5025 / C2=58.5225）；配套 `rgbaToGrayscale` / `resampleGrayscale`（box 重采样到公共网格）/ `compareImages`（两图归一后算分）。Node / 浏览器均可运行、完整可测。 +- `runVerificationStageAsync({ model, output, ctx })` (`public/core/verification/verification-stage.js`)：异步编排，先调同步 `runVerificationStage` 拿 rule-diff 基底，再跑 `runSsimLayer` 视觉回环，合并 `layers` / `skipped` / `warnings` / `runtimeMs` + `ssim` 字段。同步 `runVerificationStage` 不变，供 sync `convert()` 用（其 `qualityReport.ssim` 恒为 `null`）。 +- `runSsimLayer({ ctx, output })`：资格判断 `ctx.from ∈ {pdf,png}` 且 `ctx.to ∈ {pdf,png}`（当前实际命中 `pdf→pdf` / `png→pdf`）；经 `defaultPageImageSource` 取源图 + 输出图像素 → `compareImages` → `qualityReport.ssim = { score, threshold, passed, width, height, pageIndex, sourceFormat, outputFormat }`；低于阈值（默认 0.85）发 info 级 `SSIM_VISUAL_DRIFT`。 +- 像素源抽象 `public/core/verification/page-image-source.js`：`defaultPageImageSource`（Node 抛 `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE`；浏览器首次调用 dynamic import `page-image-source-browser.js` 用 vendor pdfjs + canvas `getImageData` 取 RGBA）+ `setPageImageSource` / `resetPageImageSource` 让测试注入 stub。 +- `format-registry.js` 抽出 `_runRepairCycle` / `_assembleQuality` 共享，`convert()`（sync）走 `_wrapWithRepairCycle`（rule-diff），`convertAsync()` 走 `_wrapWithRepairCycleAsync`（rule-diff + SSIM）。`options.repair === false` 仍短路整个验证阶段。 +- 注意：Trans2Former 的 `pdf → pdf` 走「reader 抽文本 → writer 重排版」，视觉本就不保真，SSIM 偏低是**诚实信号**，故仅发 info warning，不判失败、不阻塞。本轮渲染 stub-only（Node 无 canvas；真实 PDF/PNG 渲染 fixture + 浏览器端端到端验证留给后续）。 + +### 转换后检验三层 · OCR 回读层（P9-C.3 落地） + +第三层也是收口层 OCR 回读：把转换输出（当前仅 PDF）栅格化后用 OCR 引擎读回文本，与原始 SemanticDoc 文本对照，写入 `qualityReport.ocrReadback`，回答「转成视觉格式后文字还认得回来吗」。 + +- `compareText(original, recognized)` (`public/core/verification/ocr-readback.js`)：纯函数、零依赖、**字符级多重集** recall / precision / f1（配 `normalizeText` NFKC + 小写 + 去空白）。字符级对中英文混排与 OCR 噪声稳健，无需分词。 +- `extractModelText(model)`：拼接 block 文本（heading/paragraph/quote/list/table/code/content）。 +- `runOcrReadbackLayer({ model, output, ctx, engine?, rasterizer? })`：资格 `ctx.to === "pdf"` 且原文非空 且 OCR engine 可用；经 OCR `defaultPdfPageRasterizer` 栅格化输出 PDF → `engine.recognize` → `compareText` → `qualityReport.ocrReadback = { recall, precision, f1, threshold, passed, engineId, originalLength, recognizedLength, averageConfidence }`；低于阈值（默认 f1 ≥ 0.7）发 info `OCR_READBACK_DRIFT`；engine/rasterizer 不可用或 recognize 抛错 → eligible:false（`OCR_READBACK_FAILED` info），不抛、不阻塞。 +- `runVerificationStageAsync` 末尾 dynamic import `ocr-readback.js` 跑第三层，合并进 envelope；`qualityReport.ocrReadback` 同步路径恒 `null`。 +- 命中路径：`md/html/txt/json/xml/docx/doc/epub/csv/xlsx → pdf`（凡产出 PDF 的文本路径），engine 复用已注册的 `ocr-text`（tesseract，需用户导入 tessdata）。 +- 本轮 stub-only（Node 无 canvas/tessdata；真实 OCR 回读端到端留给浏览器手动验证）；不让 Repair Engine 消费 `ocrReadback`；高级 OCR 属 P9-D。 + +至此 P9-C 三层检验（rule-diff + ssim + ocr-readback）齐备，统一写入 `qualityReport.{ ruleDiff, ssim, ocrReadback }` + `qualityReport.verification` envelope。 + +### 高级 OCR · PP-OCRv5 (ONNX/WebGPU)（P9-D 方向 + P9-D.1 骨架） + +调研结论（[2026-05-29-p9d-advanced-ocr-research.md](superpowers/specs/2026-05-29-p9d-advanced-ocr-research.md)）：**PaddleOCR-VL（0.9B VLM）/ MinerU** 在「浏览器/Tauri 本地 + 零云端 + 30–80MB 轻量默认包」约束下当前不可内嵌（VLM 无成熟 ONNX/WebGPU 路径、需 ~500MB + 1–2GB VRAM 或 vLLM 服务；MinerU 是 Python/vLLM 工具）。因此 **P9-D 高级 OCR 的内置目标改为 PP-OCRv5（ONNX Runtime + WebGPU，WASM 回退）**；PaddleOCR-VL / MinerU 标注为**远期/外部资源**，不作为内置路径。 + +P9-D.1 骨架（同 tesseract 骨架先行）： + +- `paddleOcrEngine`（`public/core/ocr/paddle-ocr-engine.js`，id `paddleocr-v5`，taskCapabilities `["ocr-text","ocr-layout"]`）实现现有 `OCREngine` 契约，注册到 `defaultOCRRegistry`；`isAvailable()` 检查 vendor 就位 + det/cls/rec 模型在本地缓存，Node/未就位恒 false；`recognize()` 三阶段拒绝（vendor-not-ready / model-missing / runtime-not-wired）。 +- `paddle-ocr-bootstrap.js` 注册 PP-OCRv5 ONNX ModelManifest（`engine: "paddleocr"`，int8，det/cls/rec perFile 占位）到 `defaultModelCache`，状态 `not-downloaded`，按需下载到 `model-cache`。 +- P9-D.1 本轮不引入 onnxruntime-web、不实跑推理。 + +P9-D.2 接入 onnxruntime-web 运行时骨架：`onnxruntime-web` 作为 optionalDependency + `scripts/sync-onnxruntime-vendor.js`（缺包 exit 0）同步到 `public/vendor/onnxruntime/`；`public/core/ocr/paddle-ocr-runtime.js` 提供 `loadOnnxRuntime`（dynamic import 同源 vendor ORT，设 `ort.env.wasm.wasmPaths` 同源、Node 抛 `OCR_VENDOR_LOAD_FAILED`）、`pickExecutionProviders`（`navigator.gpu` → `["webgpu","wasm"]`，否则 `["wasm"]`）、`createOcrSession`/`disposeOcrSession` 骨架。`paddleOcrEngine.recognize` 第三阶段经 `loadOnnxRuntime()`，浏览器装好 vendor + 模型后以 `pipeline-not-wired` 拒绝（det/cls/rec 推理管线 + CTC 解码留给 P9-D.2.b）。Tauri CSP 已含 `wasm-unsafe-eval` + `worker-src blob:` + `connect-src 'self'`，无需改动。后续：P9-D.4 接入转换链并让 paddle 在可用时优先于 tesseract。 + +P9-D.3 模型导入与安全中心管理：复用 tesseract tessdata 的**本地导入**模式（禁联网，不做远程 fetch）。安全中心「模型缓存」对 PP-OCRv5 行渲染导入 det/cls/rec onnx + 清除按钮；导入走 file picker → `sha256Hex` → `defaultOCRStorage.put("paddleocr/v5/")` → `paddleOcrEngine.ensureProbe()`，三件齐全才 `markPaddleOcrVendorReady(true)` + 状态 `available`。**同时修复一个潜伏 bug**：`paddleOcrEngine` / `tesseractOCREngine` 的就绪状态原先存在 `Object.freeze` 后的实例属性上，`ensureProbe()` 赋值在严格模式（ES module）下抛 `Cannot assign to read only property`，会让安全中心导入流程静默失败；改为模块级可变变量持有就绪状态，引擎对象仍冻结。 + +P9-D.2.b 推理管线：`public/core/ocr/paddle-ocr-pipeline.js` 提供纯函数 `parseCharDictionary` / `preprocessForDetection`（ImageNet 归一化 + 32 倍数 + limit_side_len）/ `preprocessForRecognition`（高 48 + [-1,1] 归一化）/ `dbPostProcess`（阈值二值化 + 4-连通域 + 轴对齐 bbox + box 分数过滤 + 缩放回原图）/ `ctcGreedyDecode`（逐时刻 argmax → 折叠连续重复 → 去 blank → 映射字典）/ `cropImageData` / `resizeRgba`，以及编排器 `runPaddlePipeline({ ort, detSession, clsSession, recSession, imageData, dictionary, options })` → OCRResult。`paddleOcrEngine.recognize` 在浏览器把 image 解码为 RGBA（Image+canvas，不用 fetch）→ 从本地缓存取 det/cls/rec 模型 + 可选字典 `paddleocr/v5/dict.txt` → `createOcrSession` ×3 → `runPaddlePipeline`；Node/未就位仍在 `loadOnnxRuntime` 前置拒绝。纯函数 + 编排器（mock session）在 Node 完整单测，真实模型端到端为浏览器手动。本轮不做 cls 角度旋转校正、不做 minAreaRect+unclip 高精度框。 + +P9-D.4 接入转换链（路由偏好）：`OCREngineRegistry.pickForTask` 改为**优先级感知**——候选按 `priority` 降序挑第一个 available（缺省 0），无可用时回退末位。引擎优先级 `placeholderOCREngine=0` / `tesseractOCREngine=10` / `paddleOcrEngine=20`，因此 PP-OCRv5 可用时优先于 tesseract。PNG / 扫描 PDF stage（`enhanceWithOCR` / `runScannedPdfOCRStage`）经 `defaultOCRRegistry.pickForTask("ocr-text")` 取引擎，自动选到可用的最高优先级引擎，无需改动。至此 P9-D PP-OCRv5 本地高级 OCR 链路（契约 → 运行时 → 模型导入 → 推理管线 → 路由偏好）齐备，剩真实模型 + 字典导入后的浏览器端端到端验证。 + ## 不做什么（明确边界） - **不引入 DOCX / HTML / PDF 文件级 pivot**：pivot 是内存对象，不是落盘文件。 diff --git a/docs/PP_OCRV5_BROWSER_VERIFICATION.md b/docs/PP_OCRV5_BROWSER_VERIFICATION.md new file mode 100644 index 0000000..f97ee72 --- /dev/null +++ b/docs/PP_OCRV5_BROWSER_VERIFICATION.md @@ -0,0 +1,55 @@ +# PP-OCRv5 高级 OCR 浏览器端到端验证清单 + +适用：P9-D 全链路（.1 契约 / .2 onnxruntime-web 运行时 / .3 模型导入 / .2.b 推理管线 / .4 路由偏好）已在 Node 侧以 mock + 纯函数全覆盖。**真实模型推理只能在浏览器/Tauri（WebGPU/WASM）跑**，本清单给出手动验证步骤。 + +## 前置：准备 vendor 与模型 + +1. 安装可选依赖并同步 vendor（一次性）： + ``` + npm install onnxruntime-web + npm run vendor:onnx # 同步 ort*.mjs + *.wasm 到 public/vendor/onnxruntime/ + ``` + （`npm install tesseract.js && npm run vendor:tesseract` 同理，可选，用于对比轻量 OCR。） + +2. 准备 PP-OCRv5 ONNX 模型与字典： + ``` + npm run vendor:paddle # 从钉定来源下载 det/rec + 字典，SHA-256 校验后写入 public/vendor/paddleocr/ + ``` + - `det.onnx`（DB 文本检测）—— **必选**，随包同步 + - `rec.onnx`（CTC 文本识别）—— **必选**，随包同步 + - `dict.txt`（PP-OCRv5 keys）—— **必选**，随包同步（默认字典已随包，无需手动导入） + - `cls.onnx`（方向分类，180°）—— **可选**，不随包；管线缺它也能跑（跳过方向校正）。如需启用，在安全中心导入键名 `paddleocr/v5/cls.onnx` + + 说明：`vendor:paddle` 来源与校验和钉死在 [scripts/paddleocr-models.manifest.json](../scripts/paddleocr-models.manifest.json)（`ppu-paddle-ocr-models`，Apache-2.0，onnx 源自 paddleocr.ai）。模型文件被 `.gitignore` 忽略、不入库，随 `release:prepare` 从磁盘打进发布包。下载仅发生在构建期；转换/识别阶段零联网、零上传。 + +## 步骤：浏览器/Tauri 内验证 + +1. 启动：`npm start`（浏览器）或 `npm run desktop:dev`（Tauri）。 +2. 打开**安全中心** → 「模型缓存」card，找到 **PP-OCRv5 高级 OCR (ONNX/WebGPU)** 行： + - 若已跑过 `npm run vendor:paddle`，det/rec/dict 随包，启动即自动载入、状态直接 **可用**，无需手动导入。 + - 手动覆盖/替换：点「导入 det.onnx / rec.onnx」选择对应文件；**必选 det+rec 齐全**后状态即变 **可用**（SHA-256 校验通过）。cls.onnx 为可选导入（方向校正）。 + - （字典：默认 `dict.txt` 已随包，无需手动导入。自定义字典暂无专用按钮——可临时在 console 调 `defaultOCRStorage.put("paddleocr/v5/dict.txt", buf, {sha256})`；专用按钮列为已知后续。） +3. 验证**引擎优先级**：在 console 执行 + ```js + const m = await import("/browser-transformer.js"); + m.defaultOCRRegistry.pickForTask("ocr-text").id; // 期望 "paddleocr-v5"（paddle 可用时优先于 tesseract） + ``` +4. 验证**真实识别**：上传一张含文字的 PNG，转换到 `txt` / `md`： + - 期望输出包含识别出的文字。 + - 期望「转换检验报告」面板出现，`ocrReadback` 行显示 f1/recall（若 OCR 引擎可用）。 +5. 验证**扫描 PDF**：上传扫描型 PDF（无文本层），转换： + - 期望经 `isScannedPdf` 检测 → rasterize → PP-OCRv5 识别 → 文本输出 + FixedLayoutModel。 +6. 验证**禁联网**：打开 DevTools Network 面板，整个导入 + 识别过程**不应有任何远程请求**（仅同源 vendor / blob / dataURL）。安全中心「对外部请求监控」应为空。 + +## 通过标准 + +- 必选 det+rec（+随包 dict）就位后 PP-OCRv5 行为「可用」，`pickForTask` 选中 `paddleocr-v5`；cls 为可选（仅影响 180° 方向校正）。 +- 含文字 PNG / 扫描 PDF 经高级 OCR 得到合理识别文本（精度取决于所用模型）。 +- 三层检验报告出现，rule-diff 恒在文本路径触发，ocrReadback 在 OCR 可用时触发。 +- 全程无远程网络请求。 + +## 已知后续（不阻塞本验证） + +- 字典导入专用按钮（当前可用 console 兜底）。 +- cls 角度旋转校正、minAreaRect+unclip 高精度框、多栏阅读顺序（精度增强）。 +- 真实 PDF/PNG 渲染 baseline 与 SSIM/OCR 回读 fixture 入库。 diff --git a/docs/PRODUCT_STRATEGY.md b/docs/PRODUCT_STRATEGY.md index 4cf5090..b09f12f 100644 --- a/docs/PRODUCT_STRATEGY.md +++ b/docs/PRODUCT_STRATEGY.md @@ -31,7 +31,7 @@ Tauri 桌面壳 - 中间模型优先：新增格式必须走 `input -> DocumentModel -> output`，避免 `N * N` 转换路线。 - 软件自动修复：质量问题由本地模型识别并由 Repair Engine 执行结构化修复，用户不承担逐项修复判断。 - 核心模块优先：默认安装包保持轻量（目标 30–80 MB）；热门基础格式免下载；重格式与 OCR 等增强能力代码核心内置，模型资源按需下载到本地 model-cache，默认包不含 GB 级模型。 -- 高保真攻坚：难格式不是回避项，OFD、PDF、Office 复杂文档和本地 OCR 是长期差异化攻坚方向；高级 OCR（PaddleOCR-VL / MinerU 等）作为独立本地资源按需获取，不与默认安装包绑定。 +- 高保真攻坚：难格式不是回避项，OFD、PDF、Office 复杂文档和本地 OCR 是长期差异化攻坚方向；高级 OCR 内置目标为 PP-OCRv5（ONNX/WebGPU，按需下载 ONNX 模型），PaddleOCR-VL / MinerU 等 VLM 作为远期/外部资源，不与默认安装包绑定。 - 可验证交付：每个阶段都必须有样例、自动化测试、质量报告和可解释 warnings。 ## 产品壁垒 diff --git a/docs/RESOURCE_BUDGET.md b/docs/RESOURCE_BUDGET.md index 0373dcb..a99e538 100644 --- a/docs/RESOURCE_BUDGET.md +++ b/docs/RESOURCE_BUDGET.md @@ -56,7 +56,7 @@ OCR / 版面 / 表格能力的代码核心内置，但**模型资源不进入默 - model-cache 目录必须支持：manifest 记录每个模型资产的版本、checksum、量化方式、任务范围、最低内存和 fallback；用户可见的缓存路径、清理入口、禁用入口；断网降级提示与失败 fallback。 - 缓存包只保存推理资源，不保存训练检查点、优化器状态、标注数据、调试样本或任何用户文档内容。 - OCR、layout、table、quality-reviewer 共享资源必须去重，避免重复下载 tokenizer、字典、字体、运行库或视觉 backbone。 -- 轻量 OCR（Tesseract.js / 轻量 PaddleOCR）与高级 OCR（PaddleOCR-VL / MinerU）使用独立缓存条目；高级 OCR 启用前展示体积、运行内存、降级路径和失败提示。 +- 轻量 OCR（Tesseract.js）与高级 OCR（PP-OCRv5 ONNX/WebGPU）使用独立缓存条目；高级 OCR 启用前展示体积、运行内存、降级路径和失败提示。PaddleOCR-VL / MinerU 等 VLM 为远期/外部资源，不进入默认 dependencies 或安装包本体。 - 具体 MB/GB 上限以首个可运行 OCR 模型构建后的质量、速度、内存测试结果确定，不沿用默认安装包预算。 ### model-cache 目录结构 diff --git a/docs/superpowers/specs/2026-05-29-p9c-three-layer-verification-design.md b/docs/superpowers/specs/2026-05-29-p9c-three-layer-verification-design.md new file mode 100644 index 0000000..a0bd78f --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9c-three-layer-verification-design.md @@ -0,0 +1,106 @@ +# P9-C 转换后检验三层架构总设计 + +状态：生效 +日期：2026-05-29 +前置基础：P9-A.1 → P9-A.4 OCR 链路 / P9-B OCR → FixedLayoutModel / S2 Repair Engine / [2026-05-28-lightweight-default-bundle-direction.md](2026-05-28-lightweight-default-bundle-direction.md) +后续阶段：P9-D 高级 OCR / P7-B 跨平台发布 + +## 目标 + +DEVELOPMENT_TASKS.md 把「转换后检验」列为项目核心差异化能力之一：用户最关心的是「这次转换有没有丢东西」，而不是单一 writer 的程序化质量。P8-B 已经把 RoutePlanner 和路径分级说准，S2 Repair Engine 已经在做模型自审 + 同格式 round-trip，但当前 `metadata.qualityReport` 只有粗粒度的 `structureFidelity / tableFidelity / assetFidelity / warningCount / downgradeCount`，没有结构化的差异数据；视觉对比和 OCR 回读完全是占位。 + +P9-C 落地之后： + +- 任何一次 `convertContent` / `convertContentAsync` 在 Repair Engine 自审之后再过一层「验证阶段」（verification stage），把可执行的三层检验结果合并写入 `metadata.qualityReport`。 +- 三层检验之间是独立、可降级、共享同一份数据契约的子系统： + +``` +verification-stage + ├ rule-diff (P9-C.1) → qualityReport.ruleDiff + ├ ssim-visual (P9-C.2) → qualityReport.ssim + └ ocr-readback (P9-C.3) → qualityReport.ocrReadback +``` + +- 每层都按"可证据 → 触发；不可证据 → eligible:false + reason"原则运行；不夸大覆盖、不夸大保真度。 +- UI / Repair Engine / 任务表都从 `qualityReport.verification.layers` 读到当次实际跑过哪些层，避免 P8 之前那种「质量等级写得满，但路径根本没执行」的回潮。 + +## 三层结构与数据契约 + +### 公共 envelope `qualityReport.verification` + +```js +qualityReport.verification = { + eligible: boolean, // 至少一层 eligible 则 true + layers: ["rule-diff"], // 当次跑过且 eligible 的层名列表 + skipped: [ // 不 eligible 的层 + 原因 + { layer: "ssim", reason: "writer-not-rasterizable" }, + { layer: "ocr-readback", reason: "ocr-engine-unavailable" }, + ], + runtimeMs: number, // 三层合计 wall-clock +} +``` + +### 层级具体字段 + +每层的详细结果挂在 `qualityReport.` 平面字段下，方便 UI 直接渲染、Repair Engine validator 直接消费、测试断言直接定位。 + +| 层 | qualityReport 字段 | 触发条件 | 主要字段（详见各子阶段 spec） | +| --- | --- | --- | --- | +| 规则 diff（P9-C.1） | `qualityReport.ruleDiff` | from/to ∈ text-canonical 集合（md/html/json/csv/txt/xml）且 `output.data` 为字符串 | `identical / blockCounts / changedBlocks / addedBlocks / removedBlocks / fidelity / overallScore` | +| SSIM 视觉对比（P9-C.2） | `qualityReport.ssim` | writer 是 PDF / PNG / OFD 等可栅格化输出，且 baseline 注入 ok | `score / threshold / changedPixels / baseline / passed` | +| OCR 回读（P9-C.3） | `qualityReport.ocrReadback` | OCR engine 已 ready（tesseract 或更高级）+ writer 产物可以渲染为图像 | `textRecall / textPrecision / driftedBlocks / engineId / runtimeMs` | + +任意一层不 eligible 时对应字段为 `null`，且在 `verification.skipped` 中显式带 reason，前端不展示该层卡片。 + +### 与 Repair Engine 的关系 + +| 维度 | Repair Engine（S2） | Verification Stage（P9-C） | +| --- | --- | --- | +| 时机 | writer 之后立即跑 | Repair Engine cycle 完成之后跑 | +| 目的 | 自审 + 自动修复 + 可选 fallback | 多层独立证据采集 | +| 入口 | `defaultRepairEngine.runCycle({ model, output, ctx })` | `runVerificationStage({ model, output, ctx })` | +| 数据归宿 | `metadata.autoRepair` + `metadata.modelReview` + `qualityReport.repairStatus/finalDecision` | `qualityReport.verification` + `qualityReport.{ruleDiff,ssim,ocrReadback}` | +| 是否改 output | 可（fallback writer 切换） | 否（只读、只写 metadata + warnings） | +| 是否抛错 | 内部抓错落到 rejected actions | 内部抓错落到层级 warning，eligible 仍可为 true | + +Repair Engine 的 `reverifyRoundTrip` 字段（`roundTripDelta`）保留，作为粗粒度兼容层；P9-C.1 ruleDiff 是它的字段级细化版本，并行存在。Repair Engine 后续可能会注册一个 `detectRuleDiffDrift` validator 来消费 ruleDiff 结果生成 `replaceTextRun` 等 RepairAction，但**不在 P9-C 阶段做**（避免循环依赖）。 + +### 与 P8 RoutePlanner 的关系 + +RoutePlanner 决定 reader → writer 经过哪些模型 mapper、温度和强制 warning；Verification Stage 只看最终 `output` 和最终 `model`，与路径分级正交。`routeClass: "generated" | "restricted"` 路径仍会跑 verification——只要 writer 可被 round-trip / 栅格化 / OCR，结果就有意义；只是 fidelity 低时 ruleDiff/ssim/ocrReadback 会自然反映出来。 + +## 子阶段顺序与里程碑 + +| 子阶段 | 落地内容 | 依赖外部资源 | +| --- | --- | --- | +| **P9-C.1 规则 diff** | `public/core/verification/` 三模块骨架 + `runVerificationStage` 编排 + 接入 `_wrapWithRepairCycle` + `qualityReport.ruleDiff` + `qualityReport.verification` envelope | 无 | +| **P9-C.2 SSIM 视觉对比** | `ssim.js`（自实现，不引第三方 npm） + 复用 P9-B `defaultPdfPageRasterizer` 渲染 PDF 第 1 页 + `tests/visual-baselines/pdf/` 初始基线（md→pdf / html→pdf） + `qualityReport.ssim` | 浏览器/Tauri runtime（PDF.js vendor 已就位）；Node 侧 stub | +| **P9-C.3 OCR 回读** | 复用 tesseract engine 对 writer 产物 OCR 文本与原始 SemanticDoc 文本对比；扫描 PDF / PNG / 渲染后 PDF 都可参与 + `qualityReport.ocrReadback` | tessdata 已下载到 IndexedDB（用户手动启用） | + +P9-C.1 是无外部依赖的纯函数验证，应该最先落地，提供 envelope 数据契约 + 单测脚本，为 P9-C.2 / P9-C.3 提供接入位。 + +## 与历史 spec 的关系 + +| 历史 spec | 状态 | 处理 | +| --- | --- | --- | +| [2026-05-27 PDF Single-Page Visual Regression Design](2026-05-27-pdf-single-page-visual-regression-design.md) | 单层视觉对比设计稿；只覆盖 PDF。 | 在 P9-C.2 spec 中作为前置参考，不再单独执行。 | +| [docs/VISUAL_COMPARISON_PLAN.md](../../VISUAL_COMPARISON_PLAN.md) | 2026-05-12 框架文档；建议引入 sharp/ssim.js/pdf-to-png 等 npm 依赖。 | P9-C 方向调整后**不引入新 npm 依赖**；该文档在 P9-C.2 落地时同步收敛或归档。 | +| `scripts/visual-comparison-test.js` | 2026-05-12 占位 stub。 | P9-C.2 落地时拆为 `scripts/ssim-baseline-test.js`（或合并入 `scripts/visual-comparison-test.js` 实现）。P9-C.1 不动。 | + +## 风险与缓解 + +| 风险 | 缓解 | +| --- | --- | +| 三层 envelope 字段一旦发布，未来反复改 schema 会让 UI / 测试断言碎裂 | P9-C.1 把 envelope 字段一次性钉死（`eligible / layers / skipped / runtimeMs`），未来子层只往 `qualityReport.` 加平面字段，不动 envelope。 | +| 三层都跑会显著延长 convert 耗时 | P9-C.1 是纯同步、可降级；P9-C.2 默认渲染 PDF 第 1 页一次（< 200ms）；P9-C.3 单页 OCR ~1s。每层都按 `eligible` 短路，且 `options.repair === false` 仍然跳过整个验证阶段。 | +| Repair Engine 与 Verification Stage 出现循环依赖（Repair Engine 想看 ruleDiff，Verification Stage 又跑在 Repair Engine 之后） | P9-C 阶段 Repair Engine 只消费 `metadata.warnings`，不消费 `qualityReport.ruleDiff`；若后续要让 Repair 消费 ruleDiff，再走单独的 P10 阶段把 Repair Engine 改造为可重入。 | +| 历史 `roundTripDelta` 与新 `ruleDiff` 字段含义重叠造成歧义 | 文档里显式标注：`roundTripDelta` 是粗粒度布尔（保留兼容），`ruleDiff` 是细粒度字段级（P9-C 标准字段）；UI / Repair Engine 推荐读 `ruleDiff`。 | + +## 验收门槛 + +P9-C 视为通过的标准（每个子阶段独立验证）： + +1. 任意一次 `convertContent` / `convertContentAsync` 在 `options.repair !== false` 时返回 `result.quality.qualityReport.verification.layers` 为非空数组（至少含一个已落地层）或返回 `verification.eligible: false` + 完整 `skipped` 列表。 +2. `repair-engine` 现有契约（`autoRepair / modelReview / roundTripDelta / repairStatus / finalDecision`）一字段未动，老断言全过。 +3. `qualityReport.verification.layers` 与 `qualityReport.` 字段对齐：列表里有 `"rule-diff"` 必然 `qualityReport.ruleDiff` 非 null，反之亦然。 +4. 守门脚本（`local-security-test.js` / `local-model-direction-test.js`）覆盖三层骨架关键词；DEVELOPMENT_TASKS.md / docs/MULTI_MODEL_ARCHITECTURE.md / docs/PRODUCT_STRATEGY.md 与本 spec 一致。 diff --git a/docs/superpowers/specs/2026-05-29-p9c1-rule-diff-design.md b/docs/superpowers/specs/2026-05-29-p9c1-rule-diff-design.md new file mode 100644 index 0000000..3462281 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9c1-rule-diff-design.md @@ -0,0 +1,158 @@ +# P9-C.1 规则 diff 验证阶段 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9c-three-layer-verification-design.md](2026-05-29-p9c-three-layer-verification-design.md) / S2 Repair Engine（`reverifyRoundTrip` / `roundTripDelta`） / P8-B 执行型路由 +后续阶段：P9-C.2 SSIM 视觉对比 / P9-C.3 OCR 回读 + +## 目标 + +P9-C 总 spec 钉好了 envelope；本子阶段交付**第一层可执行验证**——规则 diff，并把 `runVerificationStage` 接入 `_wrapWithRepairCycle`，让 envelope 字段在每次转换中真实出现。 + +落地后： + +- `convertContent({ from: "md", to: "md", content: "# Hi" })` 返回 `result.quality.qualityReport.ruleDiff = { identical: true, fidelity: "exact", overallScore: 1, ... }` + `verification.layers = ["rule-diff"]`。 +- `convertContent({ from: "md", to: "html", content })` 跨格式回环 (md→html→md→read-back) 落地 ruleDiff，结构差异以 `changedBlocks / addedBlocks / removedBlocks` 暴露。 +- `convertContent({ from: "md", to: "pdf", content })` 显示 `verification.eligible: false, skipped: [{ layer: "rule-diff", reason: "writer-not-text-canonical" }]`，不阻塞。 +- `repair-engine.js` 的 `blockFingerprint` / `modelFingerprint` 抽到共享模块；行为字节级不变。 + +## 数据流 + +``` +ConverterRegistry.convert / convertAsync + → prepareConversionModel (P8-B 路由 + mapper) + → write (writer 同步) + → _wrapWithRepairCycle + ├ defaultRepairEngine.runCycle (S2 自审 / fallback / roundTripDelta) + └ runVerificationStage({ model: finalModel, output: cycle.output, ctx }) + ├ 资格判断 ROUND_TRIP_FORMATS + output.data 为字符串 + ├ 同格式 (from === to) 路径：ctx.read(output.data, from = ctx.to) → diffSemanticDocs(originalModel, readBack) + ├ 跨格式回环 (md ↔ html)：ctx.read(output.data, from = ctx.to) → 反向写回 ctx.from → ctx.read(...) → diffSemanticDocs(originalModel, readBack2) + ├ 失败兜底：read 抛 → ruleDiff = null + warning RULE_DIFF_READBACK_FAILED + └ 输出 { eligible, layers, ruleDiff, warnings, runtimeMs } + → 合并到 quality.qualityReport.{ruleDiff, verification} + → 合并 warnings 到 metadata +``` + +## 新增 / 改造模块 + +| 文件 | 职责 | +| --- | --- | +| [`public/core/verification/block-fingerprint.js`](../../../public/core/verification/block-fingerprint.js) | 共享指纹模块：`blockFingerprint(block)` / `modelFingerprint(model)`（从 `repair-engine.js` 提取，行为不变）+ `getBlockKey(block, index)`（稳定对齐键）+ `extractBlockFields(block)`（字段子集）+ `BLOCK_FIELDS_BY_TYPE` 常量 + `ROUND_TRIP_FORMATS` 单一来源。 | +| [`public/core/verification/rule-diff.js`](../../../public/core/verification/rule-diff.js) | 结构化 diff：`diffSemanticDocs(original, readBack)` → `{ identical, blockCounts, changedBlocks, addedBlocks, removedBlocks, fidelity, overallScore }`；常量 `MINOR_WEIGHT`、`MAJOR_WEIGHT`、`STRUCTURAL_PENALTY` 暴露。 | +| [`public/core/verification/verification-stage.js`](../../../public/core/verification/verification-stage.js) | 编排：`runVerificationStage({ model, output, ctx })` → envelope；处理同格式 / 跨格式回环 / 不 eligible / 失败兜底；warning code 常量 `RULE_DIFF_DRIFT` / `RULE_DIFF_READBACK_FAILED`。 | +| [`public/core/repair-engine.js`](../../../public/core/repair-engine.js) | 改 import 共享指纹；删本地 `blockFingerprint` / `modelFingerprint` / `ROUND_TRIP_FORMATS` 副本，行为不变。 | +| [`public/core/format-registry.js`](../../../public/core/format-registry.js) | `_wrapWithRepairCycle` 末尾接入 `runVerificationStage`；`quality.qualityReport` 增加 `ruleDiff` / `verification` 字段；warnings 合并到 `metadata`。 | +| [`public/browser-transformer.js`](../../../public/browser-transformer.js) | 顶层 export `runVerificationStage` / `diffSemanticDocs` / `blockFingerprint` / `modelFingerprint` / `ROUND_TRIP_FORMATS` / `RULE_DIFF_DRIFT` / `RULE_DIFF_READBACK_FAILED`。 | +| [`scripts/rule-diff-test.js`](../../../scripts/rule-diff-test.js) | 10 组断言：单元（diffSemanticDocs / runVerificationStage 各场景）+ 端到端（md→md、md→html、md→pdf）+ 指纹抽取等价性。 | +| `package.json` | `scripts.test` 链插入 `&& node scripts/rule-diff-test.js`，位置：`repair-engine-test.js` 之后、`model-cache-test.js` 之前。 | +| [`scripts/local-security-test.js`](../../../scripts/local-security-test.js) | `ALLOWED_PUBLIC_FILES` + `STRICT_LOCAL_ONLY_FILES` 加三个新模块路径。 | +| [`scripts/local-model-direction-test.js`](../../../scripts/local-model-direction-test.js) | `assertIncludes("multiModel", ...)` 加 `runVerificationStage` / `diffSemanticDocs` / `RULE_DIFF_DRIFT`；`assertIncludes("tasks", ...)` 加 `qualityReport.ruleDiff`。 | +| [`docs/MULTI_MODEL_ARCHITECTURE.md`](../../MULTI_MODEL_ARCHITECTURE.md) | 增章节简介验证阶段架构，关键词与守门同步。 | +| [`DEVELOPMENT_TASKS.md`](../../../DEVELOPMENT_TASKS.md) | 阶段状态表新增 P9-C.1 行（已完成）；`最近验收修复` 顶部追加详细条目；脚本计数 "20 个" → "21 个"。 | + +## 关键设计点 + +### ROUND_TRIP_FORMATS 单一来源 + +`repair-engine.js:10` 定义的 `const ROUND_TRIP_FORMATS = new Set(["md", "html", "json", "csv", "txt", "xml"])` 搬到 `verification/block-fingerprint.js` 作为唯一来源，`repair-engine.js` import 而非重复定义。 + +### 跨格式回环：本批仅开 md ↔ html + +`md → html → md` / `html → md → html` 是仓库里 reader/writer 双向都已实现、`inline-tokens.js` + `semantic-inlines.js` 提供统一 inline pipeline 的路径。2026-05-26 已通过跨格式回归确认这条链不产生不可逆漂移（强弱嵌套、task list、code 块、列表都被 fixture 锁定）。其它 text-canonical 跨格式回环（如 md ↔ json、html ↔ xml）由于 reader 损失模型差异较大，留给后续阶段单独评估，本批显式不开。 + +### diff 对齐策略 + +`diffSemanticDocs(original, readBack)`： + +1. 用 `getBlockKey(block, index)` 给每个 block 算稳定 key：优先 `block.id`，否则 `${block.type}-${index}-${hash(JSON.stringify(extractBlockFields(block)))}`。 +2. 按 key 直接匹配；命中的进 `changedBlocks` 候选池。 +3. 未匹配的走 LCS-lite：按 `(type, firstWords(8))` 启发对齐剩余块；命中加入 `changedBlocks`，否则进 `addedBlocks` / `removedBlocks`。 +4. 字段级比较用 `extractBlockFields(block)` 子集做 deep equal；不一致字段进 `fieldsDiffered`，每个差异分类 severity： + - **minor**：纯空白 / 标点 / 大小写差异，或仅 `text` 字段的非语义变化。 + - **major**：`level / ordered / headers / rows.length / code / language / src / assetId / format` 等结构字段。 +5. `fidelity` 推导： + - `identical: true` → `exact` + - `addedBlocks.length + removedBlocks.length > 0` 且 `(added + removed) / max(1, original.length) > 0.3` → `broken` + - 有任意 major → `major-drift` + - 仅 minor → `minor-drift` + - 全空 → `exact` +6. `overallScore`： + ``` + const penalty = ( + MAJOR_WEIGHT * majorFieldCount + + MINOR_WEIGHT * minorFieldCount + + STRUCTURAL_PENALTY * (addedBlocks.length + removedBlocks.length) + ); + const score = clamp(1 - penalty / Math.max(1, original.blocks.length), 0, 1); + ``` + 常量值：`MAJOR_WEIGHT = 0.4`, `MINOR_WEIGHT = 0.05`, `STRUCTURAL_PENALTY = 0.5`，作为模块顶层 export 暴露。 + +### Warning 策略 + +- `RULE_DIFF_DRIFT`（info 级）：当 `fidelity !== "exact"` 时发；`details` 含 `{ from, to, fidelity, score, addedCount, removedCount, changedCount }`。 +- `RULE_DIFF_READBACK_FAILED`（info 级）：当 ctx.read 抛错时发；`details` 含 `{ from, to, cause: errorCode }`。 +- 两条都走 `createWarning("info", code, message, details)`，不修改 `warnings.js` 本体。 + +### envelope 写入 + +`format-registry.js` `_wrapWithRepairCycle` 末尾： + +```js +const verification = runVerificationStage({ model: finalModel, output: cycle.output, ctx }); +const finalModelWithVerification = ensureDocumentAudit({ + ...finalModel, + metadata: withWarnings(finalModel.metadata, verification.warnings), +}, { content, reader: fromFormat, writer: ..., targetFormat: ..., fileName, options }); + +const baseQualityReport = finalModelWithVerification.metadata?.qualityReport || {}; +const qualityReport = { + ...baseQualityReport, + repairStatus: cycle.autoRepair?.attempted ? "verified" : "not-attempted", + finalDecision: cycle.autoRepair?.finalDecision || "pending", + ruleDiff: verification.ruleDiff, + verification: { + eligible: verification.eligible, + layers: verification.layers, + skipped: verification.skipped, + runtimeMs: verification.runtimeMs, + }, +}; +``` + +`roundTripDelta` 字段保留在 `cycle.autoRepair` 内，**字段未动**。 + +## 测试覆盖 + +`scripts/rule-diff-test.js` 10 组断言： + +1. `diffSemanticDocs`：相同模型 → `identical: true / fidelity: "exact" / overallScore: 1`。 +2. `diffSemanticDocs`：单 paragraph 大小写变化（`Hello` → `hello`）→ `fidelity: "minor-drift" / changedBlocks.length === 1 / fieldsDiffered === ["text"] / severity === "minor"`。 +3. `diffSemanticDocs`：heading level 改变（h1 → h2）→ `fidelity: "major-drift"`。 +4. `diffSemanticDocs`：缺一个 block + 多一个 block → `addedBlocks.length === 1 / removedBlocks.length === 1`；超 30% 块数差 → `fidelity: "broken"`。 +5. `runVerificationStage`：mock ctx.read 返回相同模型 → `ruleDiff.identical: true / warnings.length === 0 / eligible: true / layers === ["rule-diff"]`。 +6. `runVerificationStage`：mock ctx.read 抛错 → 不抛异常 + `RULE_DIFF_READBACK_FAILED` warning + `ruleDiff: null / eligible: true`。 +7. `runVerificationStage`：`from = "md"`、`to = "pptx"` → `eligible: false / reason 含 "writer-not-text-canonical" / layers === [] / ruleDiff: null / skipped[0].layer === "rule-diff"`。 +8. 端到端 `convertContent({ from: "md", to: "md", content: "# Title\n\nBody" })` → `result.quality.qualityReport.ruleDiff.identical === true / verification.layers === ["rule-diff"] / verification.eligible === true`。 +9. 端到端 `convertContent({ from: "md", to: "html", content: "# A\n\nB" })` → 跨格式回环走通；`ruleDiff !== null / verification.eligible === true`（不断言 identical，避免回环 noise 假阳性）。 +10. 端到端 `convertContent({ from: "md", to: "pdf", content: "# Hi" })` → `ruleDiff === null / verification.eligible === false / verification.skipped[0].reason === "writer-not-text-canonical"`。 + +外加双跑指纹断言（在第 1 组旁边）：用同一 model 调 `blockFingerprint`（共享版）+ inline 复用旧 repair-engine 算法（直接抄 lines 16-34 的等价实现）→ 字节级相等。 + +## 验收门槛 + +1. `npm test` 全 21 个脚本通过；`repair-engine-test.js`（10 个断言）不漂移。 +2. `git diff --check` 无 trailing whitespace。 +3. `npm run release:prepare` 不抛错。 +4. 守门关键词全过：`runVerificationStage` / `diffSemanticDocs` / `RULE_DIFF_DRIFT` 出现在 MULTI_MODEL_ARCHITECTURE.md；`qualityReport.ruleDiff` 出现在 DEVELOPMENT_TASKS.md。 +5. 三模块（block-fingerprint / rule-diff / verification-stage）进入 ALLOWED + STRICT 白名单。 + +## 本轮不做 + +- **不做** SSIM 视觉对比（P9-C.2）。 +- **不做** OCR 回读（P9-C.3）。 +- **不让** Repair Engine 消费 ruleDiff 来生成 RepairAction（避免循环依赖，留给后续阶段）。 +- **不动** writer/reader 输出语义。 +- **不动** UI（landing/workbench/preview/security-center），UI 渲染 verification 卡片留给 P9-C.2 落地后统一做。 +- **不引入** 新 npm 依赖。 +- **不开** 除 md ↔ html 之外的跨格式回环。 diff --git a/docs/superpowers/specs/2026-05-29-p9c2-ssim-visual-loopback-design.md b/docs/superpowers/specs/2026-05-29-p9c2-ssim-visual-loopback-design.md new file mode 100644 index 0000000..215ddc3 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9c2-ssim-visual-loopback-design.md @@ -0,0 +1,93 @@ +# P9-C.2 SSIM 视觉对比 · 视觉回环层 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9c-three-layer-verification-design.md](2026-05-29-p9c-three-layer-verification-design.md) / P9-C.1 规则 diff / P9-B 浏览器 rasterize / [2026-05-27-pdf-single-page-visual-regression-design.md](2026-05-27-pdf-single-page-visual-regression-design.md) +后续阶段：P9-C.3 OCR 回读 / P9-D 高级 OCR + +## 目标 + +P9-C 三层检验的第二层：SSIM 视觉对比，采用**视觉回环**语义——对视觉保真型输入（PDF / PNG），把**输入页**与**输出页**各自栅格化为像素，做结构相似度（SSIM）对比，写入 `qualityReport.ssim`，衡量「这次转换是否保住了视觉外观」。 + +落地后： + +- `convertContentAsync({ from: "pdf", to: "pdf" })` / `convertContentAsync({ from: "png", to: "pdf" })` 在 image source 可用时，`result.quality.qualityReport.ssim = { score, threshold, passed, width, height, pageIndex, sourceFormat, outputFormat }`。 +- 非视觉保真路径（`md → pdf` 无源图、`pdf → md` 输出不可栅格化）记 `qualityReport.ssim = null` + `verification.skipped` 带 reason，不阻塞。 +- SSIM 算法**自实现、零新依赖**：纯函数 `computeSSIM` 操作灰度像素缓冲，Node 完全可测。 +- 渲染本轮 **stub-only**：Node 无 canvas/pdfjs runtime，`defaultPageImageSource` 默认抛 `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE`；浏览器/Tauri 自动 dynamic import canvas 实现；测试用注入 stub image source + 合成像素覆盖代码路径，真实 PDF 渲染 fixture 留给后续。 + +## 为什么是异步层 + +栅格化（dynamic import vendor pdfjs + canvas.render + Image 解码）本质异步，而同步 `convert()` 被大量同步调用方依赖（`convertContent` sync）。因此： + +- 同步 `runVerificationStage`（P9-C.1）保持不变，只跑 rule-diff 层，供 sync `convert()` 用。 +- 新增异步 `runVerificationStageAsync`：先调同步 `runVerificationStage` 拿 rule-diff 基底 envelope，再跑 SSIM 层，合并 layers / skipped / warnings / runtimeMs + `ssim` 字段。供 `convertAsync()` 用。 +- `format-registry.js` 抽出 `_assembleQuality({ cycle, verification, ... })` 共享组装；`convert()` 走同步 verification，`convertAsync()` 走异步 verification。 +- envelope 字段 `qualityReport.ssim` 在同步路径恒为 `null`（同步不跑 SSIM），异步路径在 eligible 时填充。 + +## 数据流 + +``` +convertContentAsync({ from, to }) + → prepareConversionModel + (OCR stage 若适用) + write + → _wrapWithRepairCycleAsync + ├ defaultRepairEngine.runCycle (S2) + ├ verification = await runVerificationStageAsync({ model, output, ctx }) + │ ├ base = runVerificationStage(...) // rule-diff（同步） + │ └ ssim = await runSsimLayer({ ctx, output }) // 视觉回环（异步） + │ ├ gate: ctx.from ∈ {pdf,png} && ctx.to ∈ {pdf,png} + │ ├ srcImage = getPageImage({ format: ctx.from, content: ctx.content }) + │ ├ outImage = getPageImage({ format: ctx.to, content: output.data }) + │ ├ compareImages(srcImage, outImage) → score + │ └ passed = score >= threshold; warning SSIM_VISUAL_DRIFT if !passed + └ _assembleQuality → quality.qualityReport.{ ruleDiff, ssim } + verification envelope +``` + +## 新增 / 改造模块 + +| 文件 | 职责 | +| --- | --- | +| `public/core/verification/ssim.js` | 纯 SSIM 核心：`rgbaToGrayscale` / `resampleGrayscale`（box 重采样到公共网格）/ `computeSSIM(grayA, grayB, w, h, opts)`（非重叠窗口均值 SSIM，C1/C2 标准常量）/ `compareImages(imgA, imgB, opts)`（两图归一到公共网格后算分）。常量 `SSIM_C1` / `SSIM_C2` / `DEFAULT_WINDOW_SIZE` / `DEFAULT_TARGET_WIDTH` 暴露。 | +| `public/core/verification/page-image-source.js` | 像素源抽象：`defaultPageImageSource`（Node 抛 `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE`；浏览器首次调用 dynamic import browser 实现）+ `setPageImageSource(impl)` / `resetPageImageSource()`。契约 `getPageImage({ format, content, pageIndex, dpi })` → `{ pixels: RGBA, width, height }`。错误码 `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE` / `VERIFICATION_IMAGE_SOURCE_FAILED`。 | +| `public/core/verification/page-image-source-browser.js` | 浏览器实现：PDF → `createBrowserPdfPageRasterizer` 得 dataUrl → `Image` → canvas → `getImageData` 取像素；PNG → dataUrl/bytes → `Image` → canvas → `getImageData`。STRICT local-only。 | +| `public/core/verification/verification-stage.js` | 增 `runVerificationStageAsync` + `runSsimLayer` + warning 常量 `SSIM_VISUAL_DRIFT` / `SSIM_SOURCE_UNAVAILABLE`。同步 `runVerificationStage` 不变。 | +| `public/core/format-registry.js` | 抽 `_assembleQuality`；`_wrapWithRepairCycle`（sync）+ 新 `_wrapWithRepairCycleAsync`；`convertAsync` 改用 async wrap。 | +| `public/browser-transformer.js` | 顶层 export `computeSSIM` / `compareImages` / `rgbaToGrayscale` / `resampleGrayscale` / `runVerificationStageAsync` / `defaultPageImageSource` / `setPageImageSource` / `resetPageImageSource` / `SSIM_VISUAL_DRIFT` / `VERIFICATION_IMAGE_SOURCE_UNAVAILABLE` 等。 | +| `scripts/ssim-verification-test.js` | 断言：SSIM core（相同图=1、全黑全白≈0、加噪声单调下降、resample 尺寸）+ compareImages 不同尺寸归一 + runSsimLayer 注入 stub image source 端到端 + 非视觉路径 eligible:false + defaultPageImageSource Node 抛错 + runVerificationStageAsync 合并 rule-diff + ssim 双层。 | +| `package.json` | test 链插入 `ssim-verification-test.js`（在 `rule-diff-test.js` 之后）。 | +| `scripts/local-security-test.js` | 四个新模块加 ALLOWED + STRICT。 | +| `scripts/local-model-direction-test.js` | 守门关键词加 `computeSSIM` / `runVerificationStageAsync` / `SSIM_VISUAL_DRIFT`。 | +| `docs/MULTI_MODEL_ARCHITECTURE.md` / `DEVELOPMENT_TASKS.md` | 同步章节、状态行、验收条目；脚本计数 21 → 22。 | + +## SSIM 算法 + +- 输入：两张 `{ pixels: Uint8ClampedArray (RGBA), width, height }`。 +- `rgbaToGrayscale`：`0.299R + 0.587G + 0.114B`，输出 `Uint8ClampedArray` 长度 w*h。 +- `resampleGrayscale`：box 平均重采样到目标网格（默认 `DEFAULT_TARGET_WIDTH = 256`，高度按 imgA 宽高比推导），两图强制到同一网格；尺寸/宽高比不匹配自然拉低分值。 +- `computeSSIM`：非重叠 `windowSize=8` 窗口，逐窗算 `(2μxμy+C1)(2σxy+C2)/((μx²+μy²+C1)(σx²+σy²+C2))`，取所有窗口均值。`C1=(0.01·255)²=6.5025`，`C2=(0.03·255)²=58.5225`。 +- 不重叠窗口 + 固定网格保证确定性，跨平台稳定，零依赖。 + +## 资格与阈值 + +- SSIM 层 eligible 条件：`ctx.from ∈ {pdf, png}` 且 `ctx.to ∈ {pdf, png}`（即有源图、输出可栅格化）。 +- 当前产品矩阵实际命中：`pdf → pdf`、`png → pdf`。`ofd` 源图本轮不支持（无 OFD 渲染）→ 记 reason `format-not-rasterizable`。 +- 默认阈值 `0.85`（可经 `options.verification.ssimThreshold` 调）。注意：Trans2Former 的 `pdf → pdf` 走「reader 抽文本 → writer 重排版」，视觉本就不保真，SSIM 偏低是**诚实信号**，故默认仅发 info 级 `SSIM_VISUAL_DRIFT`，不判失败、不阻塞。 +- image source 不可用（Node 默认 / 浏览器 vendor 缺失）→ `eligible: false, reason: "image-source-unavailable"`，不抛、不阻塞转换。 + +## 验收门槛 + +1. `npm test` 全 22 个脚本通过；P9-C.1 `rule-diff-test` 与 `repair-engine-test` 不漂移。 +2. SSIM core 纯函数在 Node 完整覆盖（相同图=1、退化、resample）。 +3. `runSsimLayer` 注入 stub image source 端到端跑通，写出 `qualityReport.ssim`。 +4. `convertContent`（sync）行为不变：`qualityReport.ssim === null`，rule-diff 字段不动。 +5. 守门关键词 + 白名单覆盖四个新模块；docs 同步。 +6. `git diff --check` / `npm run release:prepare` 通过。 + +## 本轮不做 + +- **不做** OCR 回读（P9-C.3）。 +- **不入库** 真实 PDF/PNG 渲染 baseline（stub-only，真实 fixture + 浏览器端 canvas 像素 wiring 的端到端验证留给后续/手动）。 +- **不引入** 新 npm 依赖（不加 canvas / sharp / ssim.js / pixelmatch）。 +- **不支持** OFD 源图渲染；不做多页（仅第 1 页）；不做跨平台像素级 baseline 承诺。 +- **不改** 同步 `convert()` 语义 / `options.repair === false` 短路。 +- **不改** UI（验证卡片渲染留给三层齐备后统一做）。 diff --git a/docs/superpowers/specs/2026-05-29-p9c3-ocr-readback-design.md b/docs/superpowers/specs/2026-05-29-p9c3-ocr-readback-design.md new file mode 100644 index 0000000..c340450 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9c3-ocr-readback-design.md @@ -0,0 +1,90 @@ +# P9-C.3 OCR 回读 · 转换后检验三层第三层 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9c-three-layer-verification-design.md](2026-05-29-p9c-three-layer-verification-design.md) / P9-C.1 规则 diff / P9-C.2 SSIM 视觉回环 / P9-A.2.b tesseract runtime +后续阶段：P9-D 高级 OCR + +## 目标 + +P9-C 三层检验的第三层，也是收口层：OCR 回读。把转换**输出**（当前仅 PDF）栅格化后用 OCR 引擎读回文本，与**原始 SemanticDoc 文本**对照，写入 `qualityReport.ocrReadback`，回答「转成视觉格式后，文字还认得回来吗」。 + +落地后： + +- `convertContentAsync({ from: "md", to: "pdf" })`（以及 html/txt/docx/... → pdf）在 OCR engine 可用时，`result.quality.qualityReport.ocrReadback = { recall, precision, f1, threshold, passed, engineId, originalLength, recognizedLength, averageConfidence }`。 +- OCR engine 不可用（Node 默认 placeholder / 用户未导入 tessdata）或输出不可栅格化 → `qualityReport.ocrReadback = null` + `verification.skipped` 带 reason，不阻塞。 +- 文本相似度 `compareText` **纯函数、零依赖、字符级多重集**，跨中英文稳健，Node 完全可测。 +- 渲染 + OCR 本轮 **stub-only**：Node 无 canvas/tessdata，用注入 stub engine + stub rasterizer 覆盖代码路径；真实 OCR 回读端到端留给浏览器手动验证。 + +## 为什么是字符级多重集相似度 + +OCR 输出有噪声，且中文无空格分词。token（空格切分）召回对 CJK 失效。采用**字符级多重集**： + +- `originalChars` = 归一化（NFKC + 小写 + 去空白）后原文字符多重集 +- `recognizedChars` = OCR 文本同样归一化后的多重集 +- `intersection = Σ min(count_original(c), count_recognized(c))` +- `recall = intersection / max(1, |originalChars|)`（原文有多少被读回） +- `precision = intersection / max(1, |recognizedChars|)`（OCR 读到的有多少是原文里的） +- `f1 = 2PR/(P+R)` + +字符级对中英文混排、OCR 噪声都稳健，零依赖。 + +## 数据流 + +``` +convertContentAsync({ from: , to: "pdf" }) + → ... write → _wrapWithRepairCycleAsync + └ verification = await runVerificationStageAsync(...) + ├ base = runVerificationStage(...) // rule-diff（同步） + ├ ssim = await runSsimLayer(...) // 视觉回环 + └ ocrReadback = await runOcrReadbackLayer(...) // 动态 import ocr-readback.js + ├ gate: ctx.to === "pdf" 且 原文有文本 + ├ engine = injected || defaultOCRRegistry.pickForTask("ocr-text")；不可用→eligible:false + ├ rasterizer = injected || OCR defaultPdfPageRasterizer + ├ raster = await rasterizer.rasterize({ content: output.data, pageIndex: 0 }) // dataURL + ├ ocr = await engine.recognize({ image: raster.dataUrl, options:{language} }) + ├ recognizedText = ocr.fullText || join(pages.lines.text) + ├ compareText(originalText, recognizedText) → { recall, precision, f1 } + └ passed = f1 >= threshold；低于发 info OCR_READBACK_DRIFT + → _assembleQuality → quality.qualityReport.{ ruleDiff, ssim, ocrReadback } +``` + +## 新增 / 改造模块 + +| 文件 | 职责 | +| --- | --- | +| `public/core/verification/ocr-readback.js` | `compareText(original, recognized)` 纯函数（字符多重集 recall/precision/f1 + `normalizeText`）+ `extractModelText(model)`（拼接 block 文本）+ `runOcrReadbackLayer({ model, output, ctx, engine?, rasterizer? })` 异步层。常量 `DEFAULT_OCR_READBACK_THRESHOLD` / warning `OCR_READBACK_DRIFT` / `OCR_READBACK_FAILED`。 | +| `public/core/verification/verification-stage.js` | `runVerificationStageAsync` 末尾 dynamic import `ocr-readback.js` 跑第三层；合并 `layers`/`skipped`/`warnings` + `ocrReadback` 字段。 | +| `public/core/format-registry.js` | `_assembleQuality` 增 `ocrReadback: verification.ocrReadback ?? null`（同步路径恒 null）。 | +| `public/browser-transformer.js` | 顶层 export `compareText` / `extractModelText` / `runOcrReadbackLayer` / `OCR_READBACK_DRIFT` / `DEFAULT_OCR_READBACK_THRESHOLD`。 | +| `scripts/ocr-readback-test.js` | 断言：compareText（相同=1、子集 recall<1/precision=1、CJK、空文本）+ extractModelText + runOcrReadbackLayer（stub engine+rasterizer 端到端 / engine 不可用 eligible:false / 非 pdf 输出 eligible:false / rasterize 抛错兜底）+ runVerificationStageAsync 三层合并 + convertContentAsync md→pdf 注入 stub 填充 ocrReadback。 | +| `package.json` | test 链插入 `ocr-readback-test.js`（在 `ssim-verification-test.js` 之后）。 | +| `scripts/local-security-test.js` | `ocr-readback.js` 加 ALLOWED + STRICT。 | +| `scripts/local-model-direction-test.js` | 守门加 `runOcrReadbackLayer` / `compareText` / `OCR_READBACK_DRIFT`。 | +| `docs/MULTI_MODEL_ARCHITECTURE.md` / `DEVELOPMENT_TASKS.md` | 同步章节、状态行、验收条目；脚本计数 22 → 23。 | + +## 资格与阈值 + +- OCR 回读 eligible 条件：`ctx.to === "pdf"`（当前唯一可栅格化文本 writer）且原文文本非空 且 OCR engine 可用 且 rasterizer 成功。 +- 命中路径：`md/html/txt/json/xml/docx/doc/epub/csv/xlsx → pdf`（凡产出 PDF 的文本路径）。 +- 默认阈值 `f1 >= 0.7`（OCR 噪声容忍）；低于发 info 级 `OCR_READBACK_DRIFT`，不判失败、不阻塞。 +- engine 不可用（Node placeholder / 未导入 tessdata）→ `eligible:false, reason:"ocr-engine-unavailable"`，不抛。 +- rasterizer 不可用 → `eligible:false, reason:"rasterizer-unavailable"`；rasterize/recognize 抛错 → `OCR_READBACK_FAILED` info warning + eligible:false。 + +## 验收门槛 + +1. `npm test` 全 23 个脚本通过；P9-C.1/C.2、repair-engine、ocr-baseline 不漂移。 +2. `compareText` 纯函数 Node 完整覆盖（相同/子集/CJK/空）。 +3. `runOcrReadbackLayer` 注入 stub engine + stub rasterizer 端到端，写出 `qualityReport.ocrReadback`。 +4. `convertContent`（sync）行为不变：`qualityReport.ocrReadback === null`。 +5. 三层 envelope 对齐：`layers` 含 `ocr-readback` ⟺ `qualityReport.ocrReadback` 非 null。 +6. 守门 + 白名单 + docs 同步；`git diff --check` / `npm run release:prepare` 通过。 + +## 本轮不做 + +- **不入库** 真实 PDF 渲染 + tessdata OCR 回读 fixture（stub-only；浏览器端真实回读手动验证）。 +- **不引入** 新 npm 依赖。 +- **不让** Repair Engine 消费 `ocrReadback`（避免循环依赖）。 +- **不做** 多页回读（仅第 1 页）；不做 OCR→原文的逐块定位（只给聚合 recall/precision/f1）。 +- **不改** 同步 `convert()` 语义 / `options.repair === false` 短路 / UI。 +- **不接** 高级 OCR（PaddleOCR-VL / MinerU 属 P9-D）；回读复用已注册的 `ocr-text` engine。 diff --git a/docs/superpowers/specs/2026-05-29-p9c4-verification-ui-design.md b/docs/superpowers/specs/2026-05-29-p9c4-verification-ui-design.md new file mode 100644 index 0000000..5366429 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9c4-verification-ui-design.md @@ -0,0 +1,59 @@ +# P9-C.4 转换检验结果 UI + +状态：生效 +日期：2026-05-29 +前置基础：P9-C.1 规则 diff / P9-C.2 SSIM / P9-C.3 OCR 回读（三层均已写入 `qualityReport`）/ UI-A 三视图重构 +后续阶段：P9-D 高级 OCR + +## 目标 + +P9-C.1/2/3 把三层检验结果算进了 `convert()` / `convertAsync()` 返回值的 `result.quality`（`qualityReport.{ ruleDiff, ssim, ocrReadback }` + `verification` envelope + `autoRepair`），但 `public/app.js` 在转换后**丢弃了 `result.quality`**（只用 `toConversionDocumentModel` 重建 model 渲染基础信息），底部抽屉面板又已在 UI-A 前被移除——核心差异化能力「转换后检验」对用户完全不可见。 + +本子阶段把它呈现出来：转换完成后，在「转换结果」面板内展示一个紧凑、可折叠的**转换检验报告**，显示自动修复结论 + 三层检验（规则 diff / SSIM / OCR 回读）的命中状态与关键指标，未命中层显式给出原因。纯展示，不改转换核心。 + +## 范围 + +### 纳入 +- `public/index.html`：在 `#outputPreviewPanel` 内新增 `#verificationReportPanel`（`
` 折叠面板，默认 hidden，转换后显示）。 +- `public/app.js`： + - `transformContent` 捕获 `result.quality` 存入 `currentConversionQuality`。 + - 新增 `renderVerificationReport(quality)` 渲染面板；文本与二进制结果路径都调用。 + - `resetGeneratedOutput` / 新转换开始时清空面板。 +- `public/styles.css`：`.verification-report` 视觉规则（沿用 slate+teal + mini 风格）。 +- `scripts/browser-smoke-test.js`：断言 `#verificationReportPanel` 存在。 +- docs / DEVELOPMENT_TASKS 同步。 + +### 排除 +- **不复活** 已移除的底部抽屉（`bottomReportPanel`/`warningsPanel`/`qualityReportPanel`/`diffPanel`/`versionsPanel` 保持移除，smoke-test 负断言不破坏）。 +- **不改** 转换核心 / verification-stage / format-registry。 +- **不做** 真实渲染 fixture 入库（SSIM/OCR 在浏览器真实跑，但样例验证仍手动）。 +- **不引入** 新依赖。 + +## 展示内容（来自 `result.quality`） + +``` +转换检验报告 +├ 自动修复： · 结论 （来自 autoRepair） +├ 规则 diff：<命中? fidelity + score : 跳过 reason> +├ SSIM 视觉对比：<命中? score(threshold) + passed : 跳过 reason> +├ OCR 回读：<命中? f1/recall(threshold) + passed : 跳过 reason> +└ warnings：<按 severity 计数> +``` + +- 三层逐行；每行用 `data-layer` 标记，命中显示指标，未命中显示 `verification.skipped[].reason`（如 `writer-not-text-canonical` / `image-source-unavailable` / `ocr-engine-unavailable`）。 +- 文案诚实：明确「检验仅在可证据路径触发」，未触发不代表失败。 +- `result.quality` 缺失（`options.repair === false` 或旧路径）→ 面板隐藏。 + +## 渲染函数契约 + +`renderVerificationReport(quality)`： +- `quality == null` → 面板 `hidden = true`，return。 +- 否则填充各行（读 `quality.qualityReport.ruleDiff/ssim/ocrReadback/verification` + `quality.autoRepair`），`hidden = false`。 +- 纯 DOM 文本写入，无 innerHTML 注入用户内容（防 XSS：用 textContent）。 + +## 验收 + +1. `npm test` 全 24 个脚本通过；`browser-smoke-test` 断言 `#verificationReportPanel` 存在且旧抽屉负断言仍成立。 +2. `git diff --check` / `npm run release:prepare` 通过。 +3. 浏览器手动：`md → md` 转换后面板显示规则 diff 命中（fidelity exact）、SSIM/OCR 跳过并给原因。 +4. 不破坏现有结果面板、PDF 预览、输出编辑器、错误面板。 diff --git a/docs/superpowers/specs/2026-05-29-p9d-advanced-ocr-research.md b/docs/superpowers/specs/2026-05-29-p9d-advanced-ocr-research.md new file mode 100644 index 0000000..7611b4a --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d-advanced-ocr-research.md @@ -0,0 +1,68 @@ +# P9-D 高级 OCR 接入路线调研 + +状态：调研 / 待方向确认 +日期：2026-05-29 +前置基础：P9-A OCR 链路（tesseract）/ P9-B FixedLayoutModel / P9-C 三层检验 / [2026-05-28-lightweight-default-bundle-direction.md](2026-05-28-lightweight-default-bundle-direction.md) +触发：DEVELOPMENT_TASKS 把 P9-D 命名为「PaddleOCR-VL / MinerU」，本调研核实其在本项目约束下的可行性。 + +## 项目硬约束（来自既定方向） + +- 本地优先、零上传、**不调用云端 OCR/AI**、处理阶段禁联网。 +- 默认安装包 30–80 MB；GB 级模型**不进默认包**，按需下载到 model-cache。 +- 运行形态：浏览器 + Tauri（Web 前端 + Rust 壳），**无 Python 运行时**。 +- OCR 作为核心内置能力，按需启用、按需下载、可禁用、可清理。 + +## 调研结论 + +### PaddleOCR-VL（0.9B VLM）—— 浏览器/本地不可行（当前） + +- 即便量化，模型约 **500MB** 下载，推理需 **1–2GB VRAM**。 +- **无成熟的 ONNX / WebGPU 转换路径**（依赖 PaddlePaddle 自有框架）；官方推荐通过 vLLM 服务或 API 使用。 +- 结论：与「浏览器/Tauri 本地、零云端」冲突，**本阶段不接 VLM**。 + +来源： +- [PaddleOCR-VL Inference Backends (DeepWiki)](https://deepwiki.com/PaddlePaddle/PaddleOCR/2.2.2-paddleocr-vl-inference-backends-and-acceleration) +- [PaddleOCR-VL-1.5 分析（lilting）](https://lilting.ch/en/articles/paddleocr-vl-1-5-document-parsing) +- [PaddleOCR-VL 官方用法](https://www.paddleocr.ai/latest/en/version3.x/pipeline_usage/PaddleOCR-VL.html) + +### MinerU（2.5 / Pro 1.2B VLM + pipeline atomic models）—— Python 工具，非 JS 可嵌入 + +- 现代栈基于 PyTorch（pipeline 原子模型 ~1–2GB）+ vLLM（VLM 后端，官方 Docker 需 CUDA）。 +- 支持完全离线（`MINERU_MODEL_SOURCE=local` + `mineru-models-download`），但是 **Python CLI/服务**，不能嵌入 Web/Tauri 前端。 +- 唯一接入方式是「外部 Python sidecar」：重、需 Python/CUDA、与 30–80MB 轻量默认包原则冲突。 +- 结论：**本阶段不接 MinerU 内嵌**；可作为「高级用户外部工具」远期评估。 + +来源： +- [MinerU GitHub](https://github.com/opendatalab/mineru) +- [MinerU 模型配置/离线（DeepWiki）](https://deepwiki.com/opendatalab/MinerU/3.2-model-configuration) +- [MinerU2.5 论文](https://arxiv.org/html/2509.22186v1) + +### PP-OCRv5（ONNX Runtime + WebGPU）—— 真正可行的本地高级 OCR + +- **PaddleOCR.js** / 社区 **ppu-paddle-ocr**：基于 PP-OCRv5 的浏览器/多 JS runtime SDK，ONNX Runtime + WebGPU 加速 + WASM 回退，INT8 量化，40–100+ 语言，数据留在本地。 +- PP-OCRv5 全系列都有 **ONNX 导出**；WebGPU 不可用时自动回退 WASM。 +- 与本项目契合度高：作为比 tesseract 更高精度的 OCR engine 注册到现有 `defaultOCRRegistry`，ONNX 模型按需下载到 model-cache，复用 P9-A 的 manifest/checksum/Storage + P9-B 的 FixedLayoutModel + P9-C 的 OCR 回读检验。 + +来源： +- [PaddleOCR.js 浏览器部署](http://www.paddleocr.ai/main/en/version3.x/deployment/browser.html) +- [ppu-paddle-ocr (JSR)](https://jsr.io/@snowfluke/ppu-paddle-ocr) +- [Deterministic OCR in JavaScript: PaddleOCR for Node/Bun/Deno/Browser (DEV)](https://dev.to/awalariansyah/deterministic-ocr-in-javascript-paddleocr-for-node-bun-deno-and-the-browser-2bgn) + +## 建议：把 P9-D「高级 OCR」目标从 VLM 改为 PP-OCRv5（ONNX/WebGPU） + +理由：VLM（PaddleOCR-VL/MinerU）在「浏览器/Tauri 本地 + 零云端 + 轻量默认包」约束下当前不可落地；PP-OCRv5（ONNX/WebGPU）是同时满足精度提升与全部硬约束的现实路径，且能无缝复用 P9-A~C 的全部基础设施（registry / manifest / model-cache / FixedLayout / OCR 回读）。 + +如确认，需同步修订把「PaddleOCR-VL / MinerU」写为内置目标的文档：`DEVELOPMENT_TASKS` / `DESKTOP_APP_ARCHITECTURE` / `DESKTOP_RELEASE_PLAN` / `RESOURCE_BUDGET` / `PRODUCT_STRATEGY` / `MULTI_MODEL_ARCHITECTURE` / `CONVERSION_ROUTING`（及 `local-model-direction-test` 守门关键词），将 VLM 标注为「远期/外部资源」，把 PP-OCRv5（ONNX/WebGPU）确立为高级 OCR 内置路径。 + +## 拟定子阶段（若采纳 PP-OCRv5 路线） + +- **P9-D.1 引擎骨架 + 契约**：`paddle-ocr-engine.js`（实现现有 `OCREngine` 接口，注册到 `defaultOCRRegistry`，taskCapabilities 含 `ocr-text`/`ocr-layout`）+ ONNX 模型 ModelManifest 登记到 `defaultModelCache`（not-downloaded）+ Node 端不可用回退。**不引入运行时依赖、不实跑推理**（沿用 tesseract 骨架先行的节奏）。 +- **P9-D.2 ONNX runtime vendor + WebGPU 接入**：vendor onnxruntime-web（optionalDependency）+ WebGPU/WASM 检测 + COOP/COEP 说明；浏览器端真实推理，Node stub。 +- **P9-D.3 模型按需下载 + 安全中心 UI**：PP-OCRv5 det/rec/cls ONNX 模型按需下载到 model-cache（SHA-256），安全中心导入/清理按钮，断网降级提示。 +- **P9-D.4 接入转换链 + 三层检验**：把高精度 engine 经 `pickForTask` 优先于 tesseract；OCR 回读层复用以更高精度回读；FixedLayout 版面增强。 + +## 本调研不做 + +- 不写任何 P9-D 代码（等方向确认）。 +- 不改既有文档（等方向确认后统一修订）。 +- 不接 VLM 内嵌；不引入 Python sidecar。 diff --git a/docs/superpowers/specs/2026-05-29-p9d1-paddle-ocr-skeleton-design.md b/docs/superpowers/specs/2026-05-29-p9d1-paddle-ocr-skeleton-design.md new file mode 100644 index 0000000..c015964 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d1-paddle-ocr-skeleton-design.md @@ -0,0 +1,47 @@ +# P9-D.1 PP-OCRv5 高级 OCR 引擎骨架 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9d-advanced-ocr-research.md](2026-05-29-p9d-advanced-ocr-research.md)（方向已确认：高级 OCR = PP-OCRv5 ONNX/WebGPU）/ P9-A.1 OCR 契约 / P9-A.2 tesseract 骨架 / S3 model-cache +后续阶段：P9-D.2 ONNX runtime vendor + WebGPU / P9-D.3 模型按需下载 + UI / P9-D.4 接入转换链 + +## 目标 + +按「骨架先行」节奏（同 P9-A.2 tesseract）落地 PP-OCRv5 高级 OCR 的**引擎契约 + manifest 登记 + Node 不可用回退**，不引入运行时依赖、不实跑推理。同时把方向文档从「PaddleOCR-VL / MinerU 内置」修订为「PP-OCRv5 (ONNX/WebGPU) 内置；VLM 远期/外部」。 + +落地后： +- `paddleOcrEngine` 实现现有 `OCREngine` 接口，注册到 `defaultOCRRegistry`；Node/未就位时 `isAvailable()===false`，`recognize()` 三阶段拒绝（vendor-not-ready / model-missing / runtime-not-wired）。 +- PP-OCRv5 ONNX 模型集（det+rec+cls）以 ModelManifest 登记到 `defaultModelCache`，状态 `not-downloaded`。 +- 复用 P9-A 的 registry/manifest/Storage、P9-B 的 FixedLayoutModel、P9-C 的 OCR 回读检验（后续 P9-D.2+ 接真实推理后自然受益）。 + +## 新增 / 改造模块 + +| 文件 | 职责 | +| --- | --- | +| `public/core/ocr/paddle-ocr-engine.js` | `paddleOcrEngine`（id `paddleocr-v5`，taskCapabilities `["ocr-text","ocr-layout"]`，manifestId `ocr-text.paddleocr.v5`）：`isAvailable()` = vendorReady(`__t2fPaddleOcrVendorReady`) && modelReady；`recognize()` 三阶段拒绝（`OCR_UNAVAILABLE` / `OCR_ENGINE_FAILED`）；`markPaddleOcrVendorReady(ready)` + `ensureProbe()`。**不引入 onnxruntime，不实跑推理**。 | +| `public/core/ocr/paddle-ocr-bootstrap.js` | 副作用 import：注册 `paddleOcrEngine` 到 `defaultOCRRegistry`（在 tesseract 之后）+ 注册 PP-OCRv5 ModelManifest（`engine: "paddleocr"`，int8，det/rec/cls perFile 占位）到 `defaultModelCache`（`STATUS_NOT_DOWNLOADED`）。 | +| `public/browser-transformer.js` | 顶层 import `paddle-ocr-bootstrap`（tesseract-bootstrap 之后）+ export `paddleOcrEngine` / `PADDLE_OCR_MANIFEST_ID` / `markPaddleOcrVendorReady` / `ensurePaddleOcrBootstrap`。 | +| `scripts/ocr-baseline-test.js` | 更新两处 `pickForTask` 回退集合断言加入 `paddleocr-v5`；新增 paddle 骨架断言（注册 / isAvailable false / manifest 登记 / recognize 三阶段拒绝 / markPaddleOcrVendorReady）。 | +| `scripts/local-security-test.js` | 两个新模块加 ALLOWED + STRICT。 | +| `scripts/local-model-direction-test.js` | multiModel 守门加 `PP-OCRv5` / `ONNX` / `WebGPU` / `paddleOcrEngine`；保留既有「不默认内置 PaddleOCR-VL/MinerU」负断言。 | +| 方向文档（`DEVELOPMENT_TASKS` / `DESKTOP_APP_ARCHITECTURE` / `DESKTOP_RELEASE_PLAN` / `RESOURCE_BUDGET` / `PRODUCT_STRATEGY` / `MULTI_MODEL_ARCHITECTURE` / `CONVERSION_ROUTING`） | 把高级 OCR 内置目标改为 PP-OCRv5 (ONNX/WebGPU)，VLM(PaddleOCR-VL/MinerU) 标注为远期/外部资源（与研究 spec 一致）。 | + +## pickForTask 优先级说明 + +`OCREngineRegistry.pickForTask` 返回注册顺序中第一个 available 的 engine；都不可用时返回最后一个候选。本轮 paddle 注册在 tesseract 之后 → 都不可用时回退候选变为 paddle（已更新测试断言）。 + +「paddle 可用时优先于 tesseract」的偏好排序留给 **P9-D.4**（届时通过 priority 字段或调整注册顺序实现）；P9-D.1 paddle 恒不可用，偏好排序不影响当前行为。 + +## 验收 + +1. `npm test` 全 24 个脚本通过；既有 placeholder/tesseract 断言不破坏（仅扩展回退集合）。 +2. paddle 引擎注册、`isAvailable()===false`、manifest 登记、recognize 三阶段拒绝均被覆盖。 +3. 方向文档与研究 spec 一致；`local-model-direction-test` 正负断言全过。 +4. `git diff --check` / `npm run release:prepare` 通过；无新增运行时 npm 依赖。 + +## 本轮不做 + +- 不引入 onnxruntime-web / 不实跑 PP-OCRv5 推理（P9-D.2）。 +- 不做模型按需下载 / 安全中心 UI（P9-D.3）。 +- 不改 pickForTask 偏好排序 / 不接转换链（P9-D.4）。 +- 不接 VLM 内嵌 / 不引入 Python sidecar。 diff --git a/docs/superpowers/specs/2026-05-29-p9d2-onnxruntime-vendor-design.md b/docs/superpowers/specs/2026-05-29-p9d2-onnxruntime-vendor-design.md new file mode 100644 index 0000000..9987d32 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d2-onnxruntime-vendor-design.md @@ -0,0 +1,47 @@ +# P9-D.2 PP-OCRv5 onnxruntime-web vendor + 运行时加载骨架 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9d1-paddle-ocr-skeleton-design.md](2026-05-29-p9d1-paddle-ocr-skeleton-design.md) / P9-A.2 tesseract vendor 骨架（同节奏） +后续阶段：P9-D.2.b 真实 det/cls/rec 推理管线 + CTC 解码 / P9-D.3 模型按需下载 + UI / P9-D.4 接入转换链 + +## 目标 + +按「vendor + 运行时骨架」节奏（同 P9-A.2 tesseract）接入 PP-OCRv5 的 ONNX Runtime（onnxruntime-web）：optionalDependency + vendor 同步脚本 + 运行时加载器 + 执行后端（WebGPU/WASM）选择。**本轮不实现 det/cls/rec 推理管线与 CTC 解码**（留 P9-D.2.b，需真实模型 + 字典）。 + +落地后： +- `onnxruntime-web` 作为 optionalDependency 声明；缺失不阻塞（vendor 脚本 exit 0）。 +- `paddle-ocr-runtime.js` 提供 `loadOnnxRuntime`（dynamic import 同源 vendor ORT，Node 抛 `OCR_VENDOR_LOAD_FAILED`）、`pickExecutionProviders`（`navigator.gpu` → `["webgpu","wasm"]`，否则 `["wasm"]`）、`createOcrSession` / `disposeSession` 骨架、`PADDLE_VENDOR_PATHS`。 +- `paddleOcrEngine.recognize` 第三阶段改为真实尝试 `loadOnnxRuntime()`：浏览器装好 vendor + 模型则加载 ORT，再以 `pipeline-not-wired` 拒绝（P9-D.2.b 接管线）；Node 在 model-missing 阶段已先行拒绝。 + +## CSP 现状（无需改动） + +Tauri CSP 已是 `script-src 'self' 'wasm-unsafe-eval'` + `worker-src 'self' blob:` + `connect-src 'self'`，足够 onnxruntime-web 同源加载 wasm/worker 与实例化；WebGPU 无需额外 CSP。本轮不动 CSP。 + +## 新增 / 改造模块 + +| 文件 | 职责 | +| --- | --- | +| `scripts/sync-onnxruntime-vendor.js` | 模仿 sync-tesseract-vendor：从 `node_modules/onnxruntime-web/dist/` 同步 `ort*.mjs` + `*.wasm` 到 `public/vendor/onnxruntime/`；缺包 exit 0 不阻塞。 | +| `public/core/ocr/paddle-ocr-runtime.js` | `loadOnnxRuntime(vendorUrl)`（dynamic import，Node 抛 `OCR_VENDOR_LOAD_FAILED`，设 `ort.env.wasm.wasmPaths`）+ `pickExecutionProviders()` + `createOcrSession({ ort, modelBuffer, providers })` + `disposeSession` + `PADDLE_VENDOR_PATHS`。 | +| `public/core/ocr/paddle-ocr-engine.js` | recognize 第三阶段经 `loadOnnxRuntime()` → 暂以 `pipeline-not-wired`（`OCR_ENGINE_FAILED`）拒绝。 | +| `package.json` | `onnxruntime-web` 加 optionalDependencies；`vendor:onnx` script；`release:prepare` 加入 onnx vendor sync。 | +| `public/browser-transformer.js` | export `loadOnnxRuntime` / `pickExecutionProviders` / `createOcrSession` / `disposeOcrSession` / `PADDLE_VENDOR_PATHS`。 | +| `scripts/local-security-test.js` | `isLocalVendorAsset` 识别 `public/vendor/onnxruntime/`；`paddle-ocr-runtime.js` 加 ALLOWED + STRICT。 | +| `scripts/local-model-direction-test.js` | multiModel 守门加 `onnxruntime-web`。 | +| `scripts/ocr-baseline-test.js` | `pickExecutionProviders()` Node 返回 `["wasm"]`；`loadOnnxRuntime()` Node 抛 `OCR_VENDOR_LOAD_FAILED`。 | +| docs / DEVELOPMENT_TASKS | P9-D.2 条目与状态行。 | + +## 验收 + +1. `npm test` 全 24 个脚本通过；paddle 骨架（P9-D.1）断言不破坏。 +2. `pickExecutionProviders` Node 返回 `["wasm"]`；`loadOnnxRuntime` Node 抛 `OCR_VENDOR_LOAD_FAILED`。 +3. `npm run release:prepare` 包含 onnx vendor sync（缺包 exit 0）。 +4. 守门白名单/关键词覆盖；`git diff --check` 通过；onnxruntime-web 仅 optionalDependency，缺失不阻塞。 + +## 本轮不做 + +- 不实现 det/cls/rec 推理管线 / DB 后处理 / CTC 解码（P9-D.2.b，需真实模型 + 字典）。 +- 不做模型按需下载 / 安全中心 UI（P9-D.3）。 +- 不接转换链 / 不改 pickForTask 偏好（P9-D.4）。 +- 不强制安装 onnxruntime-web（仅声明 optionalDependency，npm test 在 Node 用拒绝路径覆盖）。 diff --git a/docs/superpowers/specs/2026-05-29-p9d2b-paddle-inference-pipeline-design.md b/docs/superpowers/specs/2026-05-29-p9d2b-paddle-inference-pipeline-design.md new file mode 100644 index 0000000..d9f9af3 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d2b-paddle-inference-pipeline-design.md @@ -0,0 +1,53 @@ +# P9-D.2.b PP-OCRv5 推理管线（det + cls + rec + CTC） + +状态：生效 +日期：2026-05-29 +前置基础：P9-D.2 onnxruntime-web 运行时骨架 / P9-D.3 模型导入 / P9-A.1 OCRResult 契约 +后续阶段：P9-D.4 接入转换链并让 paddle 在可用时优先于 tesseract + +## 目标 + +实现 PP-OCRv5 的真实推理管线，把检测/方向/识别三段 ONNX 前向 + 经典前后处理串成 `OCRResult`。**核心前后处理写成纯函数**（预处理、DB 检测后处理、CTC 贪心解码、字典解析、裁剪），在 Node 用合成张量完整单测；`runPaddlePipeline` 编排器接受**可注入的 session 对象**，因此可在 Node 用 mock session + mock ort 端到端测试，无需真实模型。 + +`paddleOcrEngine.recognize` 在浏览器把 `image` 解码为 RGBA → 从本地缓存加载 det/cls/rec 模型 + 字典 → 创建 session → 调 `runPaddlePipeline`。Node/未就位仍在 vendor-load / model-missing 前置拒绝。 + +## 新增 / 改造 + +| 文件 | 职责 | +| --- | --- | +| `public/core/ocr/paddle-ocr-pipeline.js` | 纯函数：`parseCharDictionary` / `preprocessForDetection` / `preprocessForRecognition` / `dbPostProcess` / `ctcGreedyDecode` / `cropImageData` / `resizeRgba`；编排器 `runPaddlePipeline({ ort, detSession, clsSession, recSession, imageData, dictionary, options })` → `OCRResult`。常量 `DET_LIMIT_SIDE_LEN`/`REC_IMAGE_HEIGHT`/`DET_MEAN`/`DET_STD`。 | +| `public/core/ocr/paddle-ocr-engine.js` | recognize 第三阶段：`loadOnnxRuntime` → `decodeImageToImageData(image)`（浏览器 canvas，Node 抛）→ 从 `_storage` 取 det/cls/rec 模型 buffer + 可选字典 `paddleocr/v5/dict.txt` → `createOcrSession` ×3 → `runPaddlePipeline`；任一步失败抛 `OCR_ENGINE_FAILED`。 | +| `public/browser-transformer.js` | export `runPaddlePipeline` / `parseCharDictionary` / `preprocessForDetection` / `preprocessForRecognition` / `dbPostProcess` / `ctcGreedyDecode` / `cropImageData`。 | +| `scripts/paddle-ocr-pipeline-test.js` | 纯函数单测（字典解析、det/rec 预处理形状与归一、DB 连通域出框、CTC 折叠去重去 blank）+ `runPaddlePipeline` 用 mock ort/session + 合成图端到端出 OCRResult。接入 `npm test`（第 25 个）。 | +| `scripts/local-security-test.js` | `paddle-ocr-pipeline.js` 加 ALLOWED + STRICT。 | +| `scripts/local-model-direction-test.js` | multiModel 守门加 `runPaddlePipeline` / `ctcGreedyDecode`。 | +| docs / DEVELOPMENT_TASKS | P9-D.2.b 章节与状态行；脚本计数 24 → 25。 | + +## 管线与契约 + +``` +runPaddlePipeline: + imageData(RGBA) → preprocessForDetection → ort.Tensor → detSession.run + → probMap(1,1,H,W) → dbPostProcess(thresh/boxThresh/minSize) → boxes[] + for box in boxes: + cropImageData → [clsSession.run（方向，本轮仅调用不旋转）] + → preprocessForRecognition(H=48) → recSession.run → logits(1,T,C) + → ctcGreedyDecode(dictionary) → { text, confidence } + → createOCRResult(pages[0].lines = boxes×decode, fullText, averageConfidence) +``` + +- **DB 后处理**：阈值二值化 + 4-连通域 BFS + 轴对齐 bbox + box 平均概率打分 + 尺寸/分数过滤 + 按 det→原图比例缩放回坐标。本轮用轴对齐 bbox（非 minAreaRect+unclip），简化但正确，文档标注；多栏/旋转文本精度提升留后。 +- **CTC 贪心解码**：逐时刻 argmax 取 idx+conf → 折叠连续重复 → 去 blank(0) → 映射字典 → text + 平均 conf。 +- **预处理常量**：det `mean=[0.485,0.456,0.406]/std=[0.229,0.224,0.225]`、`limit_side_len=960`、尺寸取 32 的倍数；rec 高 48、`(x/255-0.5)/0.5`。真实模型精度的端到端校验为浏览器/手动（导入真实 PP-OCRv5 ONNX + 字典后）。 + +## 验收 + +1. `npm test` 全 25 个脚本通过；P9-D.1/D.2/D.3 断言不破坏。 +2. 纯函数单测覆盖字典/预处理/DB 出框/CTC 折叠；`runPaddlePipeline` mock 端到端出含已知文本的 OCRResult。 +3. `git diff --check` / `npm run release:prepare` 通过；无新增运行时依赖（onnxruntime-web 仍仅 optionalDependency）。 + +## 本轮不做 + +- 不做 cls 角度旋转校正（仅调用 clsSession 占位；旋转留后）、不做 minAreaRect+unclip 高精度框、不做多栏阅读顺序。 +- 不在 Node 跑真实 ONNX（mock session 覆盖编排；真实模型端到端为浏览器手动）。 +- 不接转换链 / 偏好排序（P9-D.4）。 diff --git a/docs/superpowers/specs/2026-05-29-p9d3-paddle-model-management-design.md b/docs/superpowers/specs/2026-05-29-p9d3-paddle-model-management-design.md new file mode 100644 index 0000000..b324d16 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d3-paddle-model-management-design.md @@ -0,0 +1,44 @@ +# P9-D.3 PP-OCRv5 模型导入与安全中心管理 + +状态：生效 +日期：2026-05-29 +前置基础：[2026-05-29-p9d2-onnxruntime-vendor-design.md](2026-05-29-p9d2-onnxruntime-vendor-design.md) / P9-A.2.b tesseract tessdata 导入流程（同模式）/ S3 model-cache +后续阶段：P9-D.2.b 真实 det/cls/rec 推理管线 + CTC 解码 / P9-D.4 接入转换链 + +## 目标 + +让用户能在安全中心把 PP-OCRv5 的 det/cls/rec ONNX 模型导入本地缓存，使 `paddleOcrEngine` 从「model-missing」走向就绪。**复用 tesseract tessdata 的本地导入（file picker + SHA-256 + IndexedDB）模式**——项目禁联网/STRICT 守门禁止任何远程 URL，所谓"按需下载"在本项目中即"用户本地导入模型文件"，不做自动远程 fetch。 + +落地后： +- 安全中心「模型缓存」card 对 `engine === "paddleocr"` 行渲染三个导入按钮（det/cls/rec onnx）+ 清除按钮。 +- 导入：file picker → `arrayBuffer` → `sha256Hex` → `defaultOCRStorage.put("paddleocr/v5/")` → `paddleOcrEngine.ensureProbe()`；三件齐全 → `markPaddleOcrVendorReady(true)` + 状态 `available`。 +- 清除：删除三个键 + `ensureProbe` + 状态回 `not-downloaded`。 + +## 新增 / 改造 + +| 文件 | 改动 | +| --- | --- | +| `public/security-center.js` | import `paddleOcrEngine` / `markPaddleOcrVendorReady` / `PADDLE_OCR_MODEL_FILES`；`renderModelCache` 对 paddle 行调 `renderPaddleActions`；新增 `importPaddleModel(dialog, button)`（按 `data-file` 导入到 `paddleocr/v5/`，全部就绪才 `markPaddleOcrVendorReady(true)` + `STATUS_AVAILABLE`，否则保持 `STATUS_VERIFYING`/部分提示）+ `clearPaddleModels`；click 委托加 `[data-import-paddle]` / `[data-clear-paddle]`。 | +| `public/browser-transformer.js` | 已 export 所需 API（P9-D.1/D.2），无需新增。 | +| `scripts/ocr-baseline-test.js` | 第 37 组：手动把三件模型 put 进 `paddleOcrEngine._storage` + `markPaddleOcrVendorReady(true)` + `ensureProbe()` → `isAvailable()===true`；删任一件 → `false`（验证就绪逻辑，不依赖 UI/ORT）。 | +| `scripts/browser-smoke-test.js` | 断言 index.html `#modelCacheFileInput` 存在（导入复用同一隐藏 file input，已存在）；无新 DOM 需要。 | +| `docs/MULTI_MODEL_ARCHITECTURE.md` / `DEVELOPMENT_TASKS.md` | P9-D.3 章节 + 状态行 + 验收条目。 | + +## 关键点 + +- 存储键 `paddleocr/v5/det.onnx` / `cls.onnx` / `rec.onnx`，与 `paddle-ocr-engine.js` 的 `MODEL_KEY_PREFIX` + `PADDLE_OCR_MODEL_FILES` 对齐。 +- 就绪判定：`paddleOcrEngine.ensureProbe()` 检查三件齐全；安全中心仅在三件齐全后置 `STATUS_AVAILABLE`，否则提示「还需导入 X」。 +- `markPaddleOcrVendorReady(true)` 表示 ORT vendor 就位（浏览器已 `npm run vendor:onnx`）；与模型导入解耦，但导入流程在三件齐全时一并置位，保持与 tesseract 体验一致。 +- 不触网：复用现有 `#modelCacheFileInput` 隐藏 file input；导入是本地文件，不发起任何请求。security-center.js 已在 ALLOWED 白名单。 + +## 验收 + +1. `npm test` 全 24 个脚本通过；paddle 就绪/清除逻辑被覆盖（不依赖 ORT/UI）。 +2. `git diff --check` / `npm run release:prepare` 通过。 +3. 浏览器手动：安全中心对 PP-OCRv5 行显示导入 det/cls/rec + 清除；导入三件后状态变「可用」。 + +## 本轮不做 + +- 不实现 det/cls/rec 推理 + CTC 解码（P9-D.2.b）。 +- 不做自动远程下载（违反禁联网；坚持本地导入）。 +- 不接转换链 / 偏好排序（P9-D.4）。 diff --git a/docs/superpowers/specs/2026-05-29-p9d4-ocr-route-preference-design.md b/docs/superpowers/specs/2026-05-29-p9d4-ocr-route-preference-design.md new file mode 100644 index 0000000..11f1375 --- /dev/null +++ b/docs/superpowers/specs/2026-05-29-p9d4-ocr-route-preference-design.md @@ -0,0 +1,41 @@ +# P9-D.4 高级 OCR 接入转换链（路由偏好） + +状态：生效 +日期：2026-05-29 +前置基础：P9-D.1 引擎契约 / P9-D.2 ORT 运行时 / P9-D.3 模型导入 / P9-D.2.b 推理管线 +后续阶段：真实模型 + 字典导入后的浏览器端端到端验证（手动） + +## 目标 + +P9-D 收口：让 `paddleOcrEngine`（PP-OCRv5）在**可用时优先于** tesseract 被选用，且 PNG / 扫描 PDF 的 OCR stage 自动受益（它们经 `pickForTask("ocr-text")` 选引擎）。当前 `pickForTask` 返回注册顺序中第一个 available；paddle 注册在 tesseract 之后，两者都可用时会错选 tesseract。引入**优先级感知**选择修正。 + +## 设计 + +`OCREngineRegistry.pickForTask(task)`： +- 候选 = 注册引擎中 `taskCapabilities.includes(task)` 的。 +- 在候选中**按 `priority`（降序）挑第一个 available**（`priority` 缺省 0）；都不可用时回退到最后注册的候选（行为不变）。 +- 引擎 `priority`：`placeholderOCREngine` = 0（缺省）、`tesseractOCREngine` = 10、`paddleOcrEngine` = 20（最高，优先）。 + +PNG / 扫描 PDF stage 无需改动：`enhanceWithOCR` / `runScannedPdfOCRStage` 经 `defaultOCRRegistry.pickForTask("ocr-text")` 取引擎，自动选到可用的最高优先级引擎（有 paddle 用 paddle，否则 tesseract，否则 placeholder/降级 warning）。 + +## 新增 / 改造 + +| 文件 | 改动 | +| --- | --- | +| `public/core/ocr/ocr-engine.js` | `pickForTask` 改为优先级感知：候选按 `priority` 降序挑首个 available；无可用回退末位。 | +| `public/core/ocr/paddle-ocr-engine.js` | engine 加 `priority: 20`。 | +| `public/core/ocr/tesseract-engine.js` | engine 加 `priority: 10`。 | +| `scripts/ocr-baseline-test.js` | 第 38 组：自建 registry 两 available stub（priority 高/低）→ pickForTask 返回高优先级；默认 registry 同时让 paddle + tesseract available → pickForTask("ocr-text") 返回 `paddleocr-v5`，清理后回到 false。 | +| docs / DEVELOPMENT_TASKS | P9-D.4 章节与状态行。 | + +## 验收 + +1. `npm test` 全 25 个脚本通过；既有 pickForTask 回退断言（无可用时）不破坏。 +2. 两引擎都可用时 `pickForTask("ocr-text")` 选 `paddleocr-v5`；仅 tesseract 可用时选 tesseract。 +3. `git diff --check` / `npm run 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+ "version": "5.1.1", + "resolved": "https://registry.npmjs.org/tesseract.js-core/-/tesseract.js-core-5.1.1.tgz", + "integrity": "sha512-KX3bYSU5iGcO1XJa+QGPbi+Zjo2qq6eBhNjSGR5E5q0JtzkoipJKOUQD7ph8kFyteCEfEQ0maWLu8MCXtvX5uQ==", + "license": "Apache-2.0", + "optional": true + }, "node_modules/toidentifier": { "version": "1.0.1", "resolved": "https://registry.npmjs.org/toidentifier/-/toidentifier-1.0.1.tgz", @@ -1081,6 +1334,13 @@ "node": ">=0.6" } }, + "node_modules/tr46": { + "version": "0.0.3", + "resolved": "https://registry.npmjs.org/tr46/-/tr46-0.0.3.tgz", + "integrity": "sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==", + "license": "MIT", + "optional": true + }, "node_modules/type-is": { "version": "1.6.18", "resolved": "https://registry.npmjs.org/type-is/-/type-is-1.6.18.tgz", @@ -1094,6 +1354,13 @@ "node": ">= 0.6" } }, + "node_modules/undici-types": { + "version": "7.24.6", + "resolved": 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"license": "BSD-2-Clause", + "optional": true + }, + "node_modules/whatwg-url": { + "version": "5.0.0", + "resolved": "https://registry.npmjs.org/whatwg-url/-/whatwg-url-5.0.0.tgz", + "integrity": "sha512-saE57nupxk6v3HY35+jzBwYa0rKSy0XR8JSxZPwgLr7ys0IBzhGviA1/TUGJLmSVqs8pb9AnvICXEuOHLprYTw==", + "license": "MIT", + "optional": true, + "dependencies": { + "tr46": "~0.0.3", + "webidl-conversions": "^3.0.0" + } + }, + "node_modules/zlibjs": { + "version": "0.3.1", + "resolved": "https://registry.npmjs.org/zlibjs/-/zlibjs-0.3.1.tgz", + "integrity": "sha512-+J9RrgTKOmlxFSDHo0pI1xM6BLVUv+o0ZT9ANtCxGkjIVCCUdx9alUF8Gm+dGLKbkkkidWIHFDZHDMpfITt4+w==", + "license": "MIT", + "optional": true, + "engines": { + "node": "*" + } } } } diff --git a/package.json b/package.json index b2272af..a33cae6 100644 --- a/package.json +++ b/package.json @@ -1,6 +1,6 @@ { "name": "trans2former", - "version": "2.2.0", + "version": "2.3.0", "description": "Trans2Former: Browser-first multi-format document transformer.", "type": "module", "main": "src/web-server.js", @@ -9,11 +9,14 @@ "web": "node src/web-server.js", "vendor:pdfjs": "node scripts/sync-pdfjs-vendor.js", "vendor:tesseract": "node scripts/sync-tesseract-vendor.js", - "release:prepare": "node scripts/sync-pdfjs-vendor.js && node scripts/sync-tesseract-vendor.js && node scripts/prepare-release.js", + "vendor:onnx": "node scripts/sync-onnxruntime-vendor.js", + "vendor:paddle": "node scripts/sync-paddleocr-vendor.js", + "samples:generate": "node scripts/generate-samples.js", + "release:prepare": "node scripts/sync-pdfjs-vendor.js && node scripts/sync-tesseract-vendor.js && node scripts/sync-onnxruntime-vendor.js && node scripts/sync-paddleocr-vendor.js && node scripts/prepare-release.js", "desktop:check": "node scripts/desktop-shell-test.js", "desktop:dev": "npm exec @tauri-apps/cli -- dev", "desktop:build": "npm exec @tauri-apps/cli -- build", - "test": "node scripts/smoke-test.js && node scripts/conversion-snapshot-test.js && node scripts/conversion-capability-audit-test.js && node scripts/product-matrix-docs-test.js && node scripts/conversion-quality-test.js && node scripts/format-integrity-test.js && node scripts/worker-payload-test.js && node scripts/browser-smoke-test.js && node scripts/workbench-queue-test.js && node scripts/desktop-shell-test.js && node scripts/local-security-test.js && node scripts/local-model-direction-test.js && node scripts/repair-engine-test.js && node scripts/model-cache-test.js && node scripts/ocr-baseline-test.js && node scripts/resource-budget-test.js && node scripts/p2-responsiveness-test.js && node scripts/p4-p5-p6-test.js && node scripts/p7-release-productization-test.js && node scripts/release-readiness-test.js" + "test": "node scripts/smoke-test.js && node scripts/conversion-snapshot-test.js && node scripts/conversion-capability-audit-test.js && node scripts/product-matrix-docs-test.js && node scripts/conversion-quality-test.js && node scripts/format-integrity-test.js && node scripts/worker-payload-test.js && node scripts/browser-smoke-test.js && node scripts/workbench-queue-test.js && node scripts/desktop-shell-test.js && node scripts/local-security-test.js && node scripts/local-model-direction-test.js && node scripts/repair-engine-test.js && node scripts/rule-diff-test.js && node scripts/ssim-verification-test.js && node scripts/ocr-readback-test.js && node scripts/sample-corpus-test.js && node scripts/paddle-ocr-pipeline-test.js && node scripts/paddle-ocr-integration-test.js && node scripts/ocr-structure-test.js && node scripts/latex-math-test.js && node scripts/model-cache-test.js && node scripts/ocr-baseline-test.js && node scripts/resource-budget-test.js && node scripts/p2-responsiveness-test.js && node scripts/p4-p5-p6-test.js && node scripts/p7-release-productization-test.js && node scripts/release-readiness-test.js" }, "keywords": [ "converter", @@ -38,6 +41,7 @@ }, "homepage": "https://github.com/Vantalens/Trans2Former#readme", "optionalDependencies": { + "onnxruntime-web": "^1.26.0", "pdfjs-dist": "^5.7.284", "tesseract.js": "^5.1.1" } diff --git a/public/app.js b/public/app.js index e88a539..7f6664a 100644 --- a/public/app.js +++ b/public/app.js @@ -8,6 +8,7 @@ import { renderPreviewHtml, toConversionDocumentModel, toDocumentModel, + ensurePaddleDefaultModels, } from "./browser-transformer.js"; import { normalizeConversionError } from "./core/conversion-error.js"; import { getPlainText } from "./core/document-model.js"; @@ -30,6 +31,7 @@ import { import { readBlobAsDecodedText } from "./core/text-decoding.js"; import { expandPdfContentForTextExtraction } from "./formats/pdf.js"; import { openPreview } from "./router.js"; +import { renderMathIn } from "./katex-render.js"; const inputContent = document.getElementById("inputContent"); const sourcePane = document.querySelector(".source-pane"); @@ -83,6 +85,15 @@ const clearResolvedWarningsButton = document.getElementById("clearResolvedWarnin const qualityReportList = document.getElementById("qualityReportList"); const diffSummary = document.getElementById("diffSummary"); const versionsList = document.getElementById("versionsList"); +const verificationReportPanel = document.getElementById("verificationReportPanel"); +const verificationReportBadge = document.getElementById("verificationReportBadge"); +const verificationRepair = document.getElementById("verificationRepair"); +const verificationRuleDiff = document.getElementById("verificationRuleDiff"); +const verificationSsim = document.getElementById("verificationSsim"); +const verificationOcrReadback = document.getElementById("verificationOcrReadback"); +const verificationOcrRecognition = document.getElementById("verificationOcrRecognition"); +const verificationOcrRecognitionRow = document.getElementById("verificationOcrRecognitionRow"); +const verificationWarnings = document.getElementById("verificationWarnings"); const securityCenterButton = document.getElementById("securityCenterButton"); const workbenchTabs = document.getElementById("workbenchTabs"); const wordCountEl = document.getElementById("wordCount"); @@ -130,6 +141,7 @@ let outputDirectoryLabel = "浏览器下载目录"; let sessionVersions = []; let outputVersionIndex = -1; let currentDocumentModel = null; +let currentConversionQuality = null; let currentOutputFormat = ""; let currentOutputMime = ""; let currentOutputType = "none"; @@ -551,6 +563,97 @@ function renderBottomReports(model = null, output = "") { updateWarningsResolvedControls(model); } +function describeRuleDiff(ruleDiff, verification) { + if (ruleDiff) { + const score = typeof ruleDiff.overallScore === "number" ? ruleDiff.overallScore.toFixed(3) : "-"; + const struct = `+${ruleDiff.addedBlocks?.length || 0}/-${ruleDiff.removedBlocks?.length || 0}/~${ruleDiff.changedBlocks?.length || 0}`; + return { state: ruleDiff.identical ? "ok" : "drift", text: `${ruleDiff.fidelity} · score ${score} · 块 ${struct}` }; + } + const skip = (verification?.skipped || []).find((entry) => entry.layer === "rule-diff"); + return { state: "skip", text: `跳过：${skip?.reason || "未触发"}` }; +} + +function describeSsim(ssim, verification) { + if (ssim) { + const score = typeof ssim.score === "number" ? ssim.score.toFixed(3) : "-"; + return { state: ssim.passed ? "ok" : "drift", text: `score ${score} (阈值 ${ssim.threshold}) · ${ssim.sourceFormat}→${ssim.outputFormat}` }; + } + const skip = (verification?.skipped || []).find((entry) => entry.layer === "ssim"); + return { state: "skip", text: `跳过：${skip?.reason || "未触发"}` }; +} + +function describeOcrReadback(ocrReadback, verification) { + if (ocrReadback) { + const f1 = typeof ocrReadback.f1 === "number" ? ocrReadback.f1.toFixed(3) : "-"; + const recall = typeof ocrReadback.recall === "number" ? ocrReadback.recall.toFixed(3) : "-"; + return { state: ocrReadback.passed ? "ok" : "drift", text: `f1 ${f1} · recall ${recall} (阈值 ${ocrReadback.threshold}) · ${ocrReadback.engineId}` }; + } + const skip = (verification?.skipped || []).find((entry) => entry.layer === "ocr-readback"); + return { state: "skip", text: `跳过：${skip?.reason || "未触发"}` }; +} + +function applyVerificationRow(node, descriptor) { + if (!node) return; + node.textContent = descriptor.text; + node.dataset.state = descriptor.state; +} + +function renderVerificationReport(quality = currentConversionQuality) { + if (!verificationReportPanel) return; + if (!quality || !quality.qualityReport) { + verificationReportPanel.hidden = true; + return; + } + const report = quality.qualityReport; + const verification = report.verification || { layers: [], skipped: [] }; + const autoRepair = quality.autoRepair || {}; + + const repairStatus = report.repairStatus || (autoRepair.attempted ? "verified" : "not-attempted"); + const finalDecision = report.finalDecision || autoRepair.finalDecision || "pending"; + applyVerificationRow(verificationRepair, { + state: finalDecision === "verified" ? "ok" : (finalDecision === "failed-quality-gate" ? "drift" : "skip"), + text: `${repairStatus} · 结论 ${finalDecision}`, + }); + + applyVerificationRow(verificationRuleDiff, describeRuleDiff(report.ruleDiff, verification)); + applyVerificationRow(verificationSsim, describeSsim(report.ssim, verification)); + applyVerificationRow(verificationOcrReadback, describeOcrReadback(report.ocrReadback, verification)); + + // OCR 识别质量（仅当本次转换跑了 OCR 识别才显示） + const modelReview = quality.modelReview || {}; + if (verificationOcrRecognitionRow) { + if (modelReview.ocr) { + const ocr = modelReview.ocr; + const q = modelReview.ocrQuality || {}; + const conf = typeof ocr.averageConfidence === "number" ? ocr.averageConfidence.toFixed(3) : "-"; + const parts = [`引擎 ${ocr.engine || "-"}`, `${ocr.lineCount ?? 0} 行`, `置信度 ${conf}`]; + if (q.grade) parts.push(`质量 ${q.grade}`); + if (q.lowConfidenceLines) parts.push(`低置信 ${q.lowConfidenceLines}`); + if (q.skewApplied) parts.push(`纠偏 ${q.skewApplied}°`); + if (q.rotatedLines) parts.push(`方向校正 ${q.rotatedLines}`); + if (q.denoised) parts.push("已去噪"); + const state = q.grade === "low" ? "drift" : (q.grade === "medium" ? "skip" : "ok"); + applyVerificationRow(verificationOcrRecognition, { state, text: parts.join(" · ") }); + verificationOcrRecognitionRow.hidden = false; + } else { + verificationOcrRecognitionRow.hidden = true; + } + } + + const severity = report.warningsBySeverity || {}; + const severityText = Object.keys(severity).length > 0 + ? Object.entries(severity).map(([level, count]) => `${level}:${count}`).join(" · ") + : "无"; + applyVerificationRow(verificationWarnings, { state: (report.downgradeCount || 0) > 0 ? "drift" : "ok", text: `${report.warningCount || 0} 条（${severityText}）` }); + + const activeLayers = (verification.layers || []).length; + if (verificationReportBadge) { + verificationReportBadge.textContent = activeLayers > 0 ? `${activeLayers} 层已检验` : "未触发检验层"; + verificationReportBadge.dataset.state = activeLayers > 0 ? "ok" : "skip"; + } + verificationReportPanel.hidden = false; +} + function getOutputLineCount(output) { return String(output || "").split("\n").length; } @@ -610,6 +713,7 @@ function renderOutputPreview(content = "") { try { textOutputPreview.innerHTML = renderPreviewHtml(content, currentOutputFormat, currentFileName); + renderMathIn(textOutputPreview); outputPreviewNotice.hidden = true; outputPreviewNotice.textContent = ""; } catch (error) { @@ -860,6 +964,10 @@ function resetGeneratedOutput(metaMessage = "尚未生成") { currentOutputFormat = ""; currentOutputType = "none"; currentResolvedWarnings = new Set(); + currentConversionQuality = null; + if (verificationReportPanel) { + verificationReportPanel.hidden = true; + } textOutputPreview.textContent = ""; pdfPreview.removeAttribute("src"); downloadOutputButton.textContent = "下载输出"; @@ -1032,6 +1140,7 @@ function renderLargeDocumentPreview(rawContent, fileName = currentFileName) { `

当前仅渲染前 ${Math.min(model.blocks.length, LARGE_PREVIEW_BLOCK_LIMIT)} 个结构块，转换仍在 Worker 中完整执行。

`, ].join(""); htmlPreview.innerHTML = summary + renderPreviewHtml(previewContent, fromFormatSelect.value, fileName); + renderMathIn(htmlPreview); renderDocumentModelPanel({ ...model, blocks: model.blocks.slice(0, LARGE_PREVIEW_BLOCK_LIMIT), @@ -1071,6 +1180,7 @@ function renderPreview() { const model = toDocumentModel(content, fromFormatSelect.value, currentFileName); const bodyHtml = renderPreviewHtml(content, fromFormatSelect.value, currentFileName); htmlPreview.innerHTML = bodyHtml; + renderMathIn(htmlPreview); renderDocumentModelPanel(model); renderBottomReports(model); lastRenderedPayload = payloadKey; @@ -1230,11 +1340,16 @@ function releaseConversionResources() { } function convertWithWorker(payload) { + const fromFmt = String(payload?.from || "").toLowerCase(); + // OCR 适用输入（图片 / PDF）必须走主线程的异步管线：OCR 需要 canvas 解码图像 + + // onnxruntime 推理，这些在转换 Web Worker 里不可用。直接走 convertContentAsync—— + // 图片与扫描 PDF 触发 OCR；文本 PDF 仍走常规文本路径。 + if (fromFmt === "png" || fromFmt === "pdf") { + // 先确保随包 PP-OCRv5 模型已载入本地缓存（幂等），再跑异步转换/OCR。 + return ensurePaddleDefaultModels().catch(() => {}).then(() => convertInBrowserAsync(payload)); + } const worker = createConvertWorker(); if (!worker) { - if (String(payload?.from || "").toLowerCase() === "png") { - return Promise.resolve(convertInBrowserAsync(payload)); - } return Promise.resolve(convertInBrowser(payload)); } @@ -1304,6 +1419,7 @@ async function transformContent() { const result = await convertWithWorker({ content, from, to, title, fileName: currentFileName, options: { profile: markdownOutputProfile } }); const model = toConversionDocumentModel(content, from, to, currentFileName, currentFileName); currentDocumentModel = model; + currentConversionQuality = result.quality || null; renderDocumentModelPanel(model); currentOutputType = result.type; currentOutputFormat = result.format; @@ -1311,6 +1427,7 @@ async function transformContent() { clearOutputHistory(); updateOutputVersionControls(); renderBottomReports(model, result.type === "text" ? result.data : ""); + renderVerificationReport(currentConversionQuality); if (result.type === "binary") { currentOutputType = "binary"; @@ -1672,3 +1789,7 @@ syncPdfPaperControl(); openPdfPreviewButton.disabled = true; if (openStandalonePreviewButton) openStandalonePreviewButton.disabled = true; updateConversionProgress({ stage: "idle", progress: 0 }); + +// 后台开箱即用加载随包 PP-OCRv5 模型（同源 vendor → 本地缓存），让高级 OCR 无需手动导入。 +// 失败/缺失静默（仍可经安全中心手动导入），不阻塞 UI。 +ensurePaddleDefaultModels().catch(() => {}); diff --git a/public/browser-transformer.js b/public/browser-transformer.js index e2ce542..b3f325d 100644 --- a/public/browser-transformer.js +++ b/public/browser-transformer.js @@ -1,4 +1,4 @@ -import { ConverterRegistry, getAllowedOutputFormats, normalizeFormat } from "./core/format-registry.js"; +import { ConverterRegistry, getAllowedOutputFormats, getKnownInputFormats, normalizeFormat } from "./core/format-registry.js"; import { readCsv, writeCsv } from "./formats/csv.js"; import { readDoc } from "./formats/doc.js"; import { readDocx } from "./formats/docx.js"; @@ -249,9 +249,61 @@ export function listFormats() { export { normalizeFormat }; export { getAllowedOutputFormats }; +export { getKnownInputFormats }; export { expandPdfContentForTextExtraction }; export { defaultRepairEngine, RepairEngine, MIN_CONFIDENCE } from "./core/repair-engine.js"; export { REPAIR_ACTION_TYPES, createRepairAction, validateRepairAction } from "./core/repair-actions.js"; +export { + ROUND_TRIP_FORMATS, + blockFingerprint, + modelFingerprint, + getBlockKey, + extractBlockFields, + BLOCK_FIELDS_BY_TYPE, +} from "./core/verification/block-fingerprint.js"; +export { + diffSemanticDocs, + MAJOR_WEIGHT, + MINOR_WEIGHT, + STRUCTURAL_PENALTY, +} from "./core/verification/rule-diff.js"; +export { + runVerificationStage, + runVerificationStageAsync, + runSsimLayer, + RULE_DIFF_DRIFT, + RULE_DIFF_READBACK_FAILED, + SSIM_VISUAL_DRIFT, + SSIM_SOURCE_UNAVAILABLE, + DEFAULT_SSIM_THRESHOLD, +} from "./core/verification/verification-stage.js"; +export { + computeSSIM, + compareImages, + rgbaToGrayscale, + resampleGrayscale, + SSIM_C1, + SSIM_C2, + DEFAULT_WINDOW_SIZE, + DEFAULT_TARGET_WIDTH, +} from "./core/verification/ssim.js"; +export { + defaultPageImageSource, + setPageImageSource, + resetPageImageSource, + RASTERIZABLE_FORMATS, + VERIFICATION_IMAGE_SOURCE_UNAVAILABLE, + VERIFICATION_IMAGE_SOURCE_FAILED, +} from "./core/verification/page-image-source.js"; +export { + compareText, + normalizeText, + extractModelText, + runOcrReadbackLayer, + OCR_READBACK_DRIFT, + OCR_READBACK_FAILED, + DEFAULT_OCR_READBACK_THRESHOLD, +} from "./core/verification/ocr-readback.js"; export { MODEL_MANIFEST_SCHEMA_VERSION, MODEL_TASKS, @@ -291,6 +343,7 @@ export { } from "./core/model-cache/ui-text.js"; import "./core/ocr/ocr-bootstrap.js"; import "./core/ocr/tesseract-bootstrap.js"; +import "./core/ocr/paddle-ocr-bootstrap.js"; export { OCR_RESULT_SCHEMA_VERSION, OCR_LANGUAGES, @@ -324,6 +377,42 @@ export { markTesseractVendorReady, } from "./core/ocr/tesseract-engine.js"; export { ensureTesseractBootstrap } from "./core/ocr/tesseract-bootstrap.js"; +export { + paddleOcrEngine, + PADDLE_OCR_MANIFEST_ID, + PADDLE_OCR_MODEL_FILES, + PADDLE_OCR_REQUIRED_FILES, + markPaddleOcrVendorReady, +} from "./core/ocr/paddle-ocr-engine.js"; +export { ensurePaddleOcrBootstrap } from "./core/ocr/paddle-ocr-bootstrap.js"; +export { ensurePaddleDefaultModels } from "./core/ocr/paddle-default-models.js"; +export { + loadOnnxRuntime, + pickExecutionProviders, + createOcrSession, + disposeOcrSession, + resetOnnxRuntimeCache, + PADDLE_VENDOR_PATHS, +} from "./core/ocr/paddle-ocr-runtime.js"; +export { + runPaddlePipeline, + parseCharDictionary, + preprocessForDetection, + preprocessForRecognition, + dbPostProcess, + ctcGreedyDecode, + cropImageData, + resizeRgba, + rotateImageData90, + rotateImageData180, + rotateImageDataByAngle, + estimateSkewAngle, + interpretClsOutput, + denoiseImageData, + estimateNoiseLevel, + DET_LIMIT_SIDE_LEN, + REC_IMAGE_HEIGHT, +} from "./core/ocr/paddle-ocr-pipeline.js"; export { InMemoryStorage, createIndexedDBStorage, @@ -339,6 +428,7 @@ export { disposeWorker, } from "./core/ocr/tesseract-runtime.js"; export { enhanceWithOCR } from "./core/ocr/png-ocr.js"; +export { deriveOcrStructure, blocksFromOcrResult } from "./core/ocr/ocr-structure.js"; export { runOCRStage, getDefaultOCRLanguage } from "./core/ocr/ocr-stage.js"; export { detectOCRLowConfidence } from "./core/ocr/ocr-validator.js"; export { diff --git a/public/core/format-registry.js b/public/core/format-registry.js index 36707ac..e3a9f1e 100644 --- a/public/core/format-registry.js +++ b/public/core/format-registry.js @@ -1,6 +1,7 @@ import { ConversionError } from "./conversion-error.js"; import { ensureDocumentAudit } from "./document-audit.js"; import { defaultRepairEngine } from "./repair-engine.js"; +import { runVerificationStage, runVerificationStageAsync } from "./verification/verification-stage.js"; import { createWarning, withWarnings } from "./warnings.js"; const FORMAT_ALIASES = { @@ -438,7 +439,8 @@ export class ConverterRegistry { }; } - _wrapWithRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }) { + // 跑 Repair Engine cycle，返回 { earlyReturn } 或 { cycle, effectiveTo, auditedModel }。 + _runRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }) { let cycle; try { cycle = defaultRepairEngine.runCycle({ model, output, ctx }); @@ -461,35 +463,75 @@ export class ConverterRegistry { options, }); return { - ...output, - quality: { - qualityReport: audited.metadata?.qualityReport || null, - modelReview: null, - autoRepair: { attempted: false, error: error?.code || "unknown", finalDecision: "failed-quality-gate" }, - conversion: audited.metadata?.conversion || null, + earlyReturn: { + ...output, + quality: { + qualityReport: audited.metadata?.qualityReport || null, + modelReview: null, + autoRepair: { attempted: false, error: error?.code || "unknown", finalDecision: "failed-quality-gate" }, + conversion: audited.metadata?.conversion || null, + }, }, }; } - const finalModel = ensureDocumentAudit({ + const effectiveTo = cycle.autoRepair?.fallbackUsed ? (cycle.autoRepair.fallbackTo || toFormat) : toFormat; + // Repair Engine 写自己的 modelReview，但要保留上游 OCR stage 记下的 ocr / ocrQuality + // 子对象（否则识别质量数据会被覆盖丢失，UI 无法展示）。 + const priorReview = cycle.model.metadata?.modelReview || {}; + const mergedModelReview = { + ...cycle.modelReview, + ...(priorReview.ocr ? { ocr: priorReview.ocr } : {}), + ...(priorReview.ocrQuality ? { ocrQuality: priorReview.ocrQuality } : {}), + }; + const auditedModel = ensureDocumentAudit({ ...cycle.model, metadata: { ...(cycle.model.metadata || {}), autoRepair: cycle.autoRepair, - modelReview: cycle.modelReview, + modelReview: mergedModelReview, }, }, { content, reader: fromFormat, - writer: cycle.autoRepair?.fallbackUsed ? (cycle.autoRepair.fallbackTo || toFormat) : toFormat, - targetFormat: cycle.autoRepair?.fallbackUsed ? (cycle.autoRepair.fallbackTo || toFormat) : toFormat, + writer: effectiveTo, + targetFormat: effectiveTo, fileName, options, }); + return { cycle, effectiveTo, auditedModel }; + } + + // 给定 Repair cycle 结果 + verification envelope，组装最终 quality 返回值。 + _assembleQuality({ cycle, effectiveTo, auditedModel, verification, content, fromFormat, fileName, options }) { + const finalModel = verification.warnings.length > 0 + ? ensureDocumentAudit({ + ...auditedModel, + metadata: withWarnings(auditedModel.metadata || {}, verification.warnings), + }, { + content, + reader: fromFormat, + writer: effectiveTo, + targetFormat: effectiveTo, + fileName, + options, + }) + : auditedModel; + const baseQualityReport = finalModel.metadata?.qualityReport || {}; const qualityReport = { ...baseQualityReport, repairStatus: cycle.autoRepair?.attempted ? "verified" : "not-attempted", finalDecision: cycle.autoRepair?.finalDecision || "pending", + ruleDiff: verification.ruleDiff, + ssim: verification.ssim ?? null, + ocrReadback: verification.ocrReadback ?? null, + verification: { + eligible: verification.eligible, + reason: verification.reason, + layers: verification.layers, + skipped: verification.skipped, + runtimeMs: verification.runtimeMs, + }, }; return { ...cycle.output, @@ -502,6 +544,24 @@ export class ConverterRegistry { }; } + // 同步路径：Repair cycle + 同步验证阶段（仅 rule-diff 层）。 + _wrapWithRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }) { + const cycleResult = this._runRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }); + if (cycleResult.earlyReturn) return cycleResult.earlyReturn; + const { cycle, effectiveTo, auditedModel } = cycleResult; + const verification = runVerificationStage({ model: auditedModel, output: cycle.output, ctx }); + return this._assembleQuality({ cycle, effectiveTo, auditedModel, verification, content, fromFormat, fileName, options }); + } + + // 异步路径：Repair cycle + 异步验证阶段（rule-diff + SSIM 视觉回环）。 + async _wrapWithRepairCycleAsync({ model, output, ctx, content, fromFormat, toFormat, fileName, options }) { + const cycleResult = this._runRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }); + if (cycleResult.earlyReturn) return cycleResult.earlyReturn; + const { cycle, effectiveTo, auditedModel } = cycleResult; + const verification = await runVerificationStageAsync({ model: auditedModel, output: cycle.output, ctx }); + return this._assembleQuality({ cycle, effectiveTo, auditedModel, verification, content, fromFormat, fileName, options }); + } + convert({ content, from, to, title = "document", fileName = "", options = {} }) { const fromFormat = normalizeFormat(from); const toFormat = normalizeFormat(to); @@ -545,6 +605,6 @@ export class ConverterRegistry { return output; } const ctx = this._buildRepairCtx({ content, fromFormat, toFormat, title, fileName, options }); - return this._wrapWithRepairCycle({ model, output, ctx, content, fromFormat, toFormat, fileName, options }); + return this._wrapWithRepairCycleAsync({ model, output, ctx, content, fromFormat, toFormat, fileName, options }); } } diff --git a/public/core/models/semantic-inlines.js b/public/core/models/semantic-inlines.js index c23cc5e..e1fe126 100644 --- a/public/core/models/semantic-inlines.js +++ b/public/core/models/semantic-inlines.js @@ -64,6 +64,11 @@ export function createInlineFootnoteRef(id) { return { type: "footnoteRef", id: String(id ?? "") }; } +// LaTeX 数学：{ type:"math", value: 原始 tex, display: 块级? }。内容逐字保留，不转义、不递归。 +export function createInlineMath(value, display = false) { + return { type: "math", value: String(value ?? ""), display: Boolean(display) }; +} + export function normalizeInlines(input) { if (input === null || input === undefined) return []; if (typeof input === "string") { @@ -85,6 +90,10 @@ export function inlinesToPlainText(inlines) { .map((node) => { if (!node || typeof node !== "object") return ""; if (node.type === "text" || node.type === "code") return String(node.value ?? ""); + if (node.type === "math") { + const d = node.display ? "$$" : "$"; + return `${d}${String(node.value ?? "")}${d}`; + } if (node.type === "linebreak") return "\n"; if (Array.isArray(node.inlines)) return inlinesToPlainText(node.inlines); return ""; @@ -101,6 +110,10 @@ export function inlinesToMarkdown(inlines) { if (node.type === "em") return `*${inlinesToMarkdown(node.inlines)}*`; if (node.type === "del") return `~~${inlinesToMarkdown(node.inlines)}~~`; if (node.type === "code") return `\`${String(node.value ?? "").replace(/`/g, "\\`")}\``; + if (node.type === "math") { + const d = node.display ? "$$" : "$"; + return `${d}${String(node.value ?? "")}${d}`; + } if (node.type === "link") { const inner = inlinesToMarkdown(node.inlines) || node.href || ""; const title = node.title ? ` "${node.title.replace(/"/g, '\\"')}"` : ""; @@ -123,6 +136,12 @@ export function inlinesToHtml(inlines) { if (node.type === "em") return `${inlinesToHtml(node.inlines)}`; if (node.type === "del") return `${inlinesToHtml(node.inlines)}`; if (node.type === "code") return `${escapeHtmlInline(node.value)}`; + if (node.type === "math") { + // 原始 tex 存 data-tex（客户端 KaTeX 渲染）；span 文本是带定界符的 tex 作为无 JS 兜底。 + const tex = String(node.value ?? ""); + const d = node.display ? "$$" : "$"; + return `${escapeHtmlInline(`${d}${tex}${d}`)}`; + } if (node.type === "link") { const inner = inlinesToHtml(node.inlines); const titleAttr = node.title ? ` title="${escapeHtmlInline(node.title)}"` : ""; diff --git a/public/core/ocr/ocr-engine.js b/public/core/ocr/ocr-engine.js index b203f0a..084ebdf 100644 --- a/public/core/ocr/ocr-engine.js +++ b/public/core/ocr/ocr-engine.js @@ -98,14 +98,20 @@ export class OCREngineRegistry { pickForTask(task) { const candidates = this.list().filter((engine) => engine.taskCapabilities.includes(task)); if (candidates.length === 0) return null; - const available = candidates.find((engine) => { + // 优先级感知：在候选中按 priority 降序挑第一个 available（priority 缺省 0）。 + // 这样高级引擎（如 PP-OCRv5 priority=20）可用时优先于 tesseract（10）/ placeholder（0）。 + const isAvail = (engine) => { try { return engine.isAvailable() === true; } catch (error) { return false; } - }); + }; + const priorityOf = (engine) => Number(engine.priority) || 0; + const byPriority = [...candidates].sort((a, b) => priorityOf(b) - priorityOf(a)); + const available = byPriority.find(isAvail); if (available) return available; + // 无可用引擎：回退到最后注册的候选（行为不变，仅作为"不可用"代表）。 return candidates[candidates.length - 1]; } diff --git a/public/core/ocr/ocr-structure.js b/public/core/ocr/ocr-structure.js new file mode 100644 index 0000000..2656d02 --- /dev/null +++ b/public/core/ocr/ocr-structure.js @@ -0,0 +1,119 @@ +// OCR 版面结构推断（格式识别增强）：把识别到的文本行（带 bbox）按阅读顺序归并成 +// 标题 + 段落，而不是平铺成一个大段。用相对字号（行高）判定标题，用行间垂直间距分段。 +// 纯函数，可测；无 bbox 几何信息时优雅回退（每行一段 / 单段）。 + +import { createParagraph, createHeading } from "../document-model.js"; + +function median(values) { + if (values.length === 0) return 0; + const sorted = [...values].sort((a, b) => a - b); + const mid = sorted.length >> 1; + return sorted.length % 2 ? sorted[mid] : (sorted[mid - 1] + sorted[mid]) / 2; +} + +const CJK = /[㐀-鿿豈-﫿぀-ヿ가-힯]/; + +function isCjk(ch) { + return typeof ch === "string" && CJK.test(ch); +} + +// 同段相邻行拼接：两侧都是 CJK 则直连（无空格），否则空格分隔。 +function joinLines(prevText, lineText) { + if (!prevText) return lineText; + const a = prevText[prevText.length - 1]; + const b = lineText[0]; + return isCjk(a) && isCjk(b) ? prevText + lineText : `${prevText} ${lineText}`; +} + +function headingLevel(ratio) { + if (ratio >= 2) return 1; + if (ratio >= 1.6) return 2; + return 3; +} + +// lines: [{ text, bbox:{x,y,w,h} }]（confidence 可选）。返回 block 数组（heading/paragraph）。 +export function deriveOcrStructure(lines, { + headingRatio = 1.35, + paraGapRatio = 0.7, +} = {}) { + const usable = (lines || []).filter((l) => l && typeof l.text === "string" && l.text.trim().length > 0); + if (usable.length === 0) return []; + + const withBox = usable.filter((l) => l.bbox && Number.isFinite(l.bbox.h) && l.bbox.h > 0); + // 几何信息不足（如桩引擎无 bbox）：无法结构化，回退为单一段落（保持旧行为）。 + if (withBox.length < 2) { + return [createParagraph(usable.map((l) => l.text.trim()).join("\n"))]; + } + + const sorted = [...withBox].sort((a, b) => (a.bbox.y - b.bbox.y) || (a.bbox.x - b.bbox.x)); + const medianHeight = median(sorted.map((l) => l.bbox.h)) || 1; + const gapThreshold = medianHeight * paraGapRatio; + + const blocks = []; + let para = ""; + let prevBottom = null; + + const flushPara = () => { + if (para.trim().length > 0) blocks.push(createParagraph(para.trim())); + para = ""; + }; + + for (const line of sorted) { + const text = line.text.trim(); + const ratio = line.bbox.h / medianHeight; + const top = line.bbox.y; + + if (ratio >= headingRatio) { + // 标题：独立成块 + flushPara(); + blocks.push(createHeading(headingLevel(ratio), text)); + prevBottom = line.bbox.y + line.bbox.h; + continue; + } + + const bigGap = prevBottom !== null && (top - prevBottom) > gapThreshold; + if (bigGap) flushPara(); + para = joinLines(para, text); + prevBottom = line.bbox.y + line.bbox.h; + } + flushPara(); + + return blocks; +} + +// 为一批 OCR 行回填它们所属块的 id。OCR 追加块在进入 repair cycle 前不会被 document-audit +// 赋 id，故调用方需先给这些块预赋稳定 id（如 "ocr-block-<绝对索引>"）再调用本函数。 +// 匹配用「修剪文本包含」：块文本由若干行 trim 后拼接而成，每行 trim 文本必是某块文本的子串。 +// 单调游标处理「多行→一块」（无 bbox 回退、CJK 拼接段落）；回卷一遍兼容扫描 PDF 的阅读顺序 +// 重排（lines 顺序 ≠ 块顺序）。空/空白行不产块 → 返回 ""。 +export function mapLinesToBlockIds(lines, blocks) { + const list = Array.isArray(lines) ? lines : []; + const blk = Array.isArray(blocks) ? blocks : []; + let cursor = 0; + return list.map((line) => { + const t = (line?.text || "").trim(); + if (!t) return ""; + for (let j = cursor; j < blk.length; j += 1) { + const bt = (blk[j]?.text || "").trim(); + if (bt && bt.includes(t)) { cursor = j; return blk[j]?.id || ""; } + } + for (let j = 0; j < cursor; j += 1) { + const bt = (blk[j]?.text || "").trim(); + if (bt && bt.includes(t)) return blk[j]?.id || ""; + } + return ""; + }); +} + +// 从 OCRResult 各页推断结构块（按页顺序拼接）。 +export function blocksFromOcrResult(result, options = {}) { + const pages = Array.isArray(result?.pages) ? result.pages : []; + const blocks = []; + for (const page of pages) { + blocks.push(...deriveOcrStructure(page?.lines || [], options)); + } + if (blocks.length === 0 && typeof result?.fullText === "string" && result.fullText.trim().length > 0) { + blocks.push(createParagraph(result.fullText.trim())); + } + return blocks; +} diff --git a/public/core/ocr/paddle-default-models.js b/public/core/ocr/paddle-default-models.js new file mode 100644 index 0000000..2519743 --- /dev/null +++ b/public/core/ocr/paddle-default-models.js @@ -0,0 +1,82 @@ +// 浏览器端开箱即用：把随应用打包的 PP-OCRv5 模型（public/vendor/paddleocr/ 同源） +// 自动载入 OCR 本地缓存（IndexedDB），让高级 OCR 无需手动导入即可用。仅 fetch 同源 +// vendor 资源，不联网、不上传。vendor 缺失时静默跳过（仍可经安全中心手动导入）。 + +import { defaultOCRStorage } from "./ocr-storage.js"; +import { paddleOcrEngine, markPaddleOcrVendorReady, PADDLE_OCR_REQUIRED_FILES } from "./paddle-ocr-engine.js"; + +const VENDOR_BASE = "/vendor/paddleocr/"; +const STORAGE_PREFIX = "paddleocr/v5/"; +const DICT_FILE = "dict.txt"; +// cls（方向分类）可选：vendor 缺失时静默跳过，不拖垮 det/rec 的随包载入。 +const OPTIONAL_FILE = "cls.onnx"; + +let inflight = null; + +function isBrowser() { + return typeof globalThis !== "undefined" + && typeof globalThis.fetch === "function" + && typeof globalThis.document === "object"; +} + +async function fetchToBuffer(url) { + const response = await globalThis.fetch(url); + if (!response.ok) throw new Error(`${url} -> HTTP ${response.status}`); + return response.arrayBuffer(); +} + +async function alreadyLoaded() { + for (const file of PADDLE_OCR_REQUIRED_FILES) { + if (!(await defaultOCRStorage.has(`${STORAGE_PREFIX}${file}`))) return false; + } + return true; +} + +// 幂等：若 vendor 模型已在缓存则只置位；否则 fetch 同源 vendor → 写入缓存 → markReady → probe。 +export async function ensurePaddleDefaultModels() { + if (!isBrowser()) return { loaded: false, reason: "not-browser" }; + if (inflight) return inflight; + inflight = (async () => { + try { + if (await alreadyLoaded()) { + markPaddleOcrVendorReady(true); + await paddleOcrEngine.ensureProbe(); + return { loaded: true, reason: "cached" }; + } + // 先确认 vendor 真的随包提供（HEAD det），缺失则跳过（不报错，留给手动导入）。 + const probe = await globalThis.fetch(`${VENDOR_BASE}det.onnx`, { method: "HEAD" }); + if (!probe.ok) return { loaded: false, reason: "vendor-absent" }; + + for (const file of PADDLE_OCR_REQUIRED_FILES) { + const buffer = await fetchToBuffer(`${VENDOR_BASE}${file}`); + await defaultOCRStorage.put(`${STORAGE_PREFIX}${file}`, buffer, { source: "vendor-bundle" }); + } + // 方向分类 cls（可选）：vendor 缺失不致命；缺它管线跳过 180° 校正。 + try { + const cls = await fetchToBuffer(`${VENDOR_BASE}${OPTIONAL_FILE}`); + await defaultOCRStorage.put(`${STORAGE_PREFIX}${OPTIONAL_FILE}`, cls, { source: "vendor-bundle" }); + } catch (clsError) { + // cls 缺失不致命。 + } + // 字典（可选） + try { + const dict = await fetchToBuffer(`${VENDOR_BASE}${DICT_FILE}`); + await defaultOCRStorage.put(`${STORAGE_PREFIX}${DICT_FILE}`, dict, { source: "vendor-bundle" }); + } catch (dictError) { + // 字典缺失不致命；识别可降级。 + } + + markPaddleOcrVendorReady(true); + await paddleOcrEngine.ensureProbe(); + return { loaded: true, reason: "fetched" }; + } catch (error) { + return { loaded: false, reason: `error:${error?.message || error}` }; + } finally { + // 允许后续重试（例如首次 vendor 还没就位）。 + if (inflight) inflight = inflight; + } + })(); + const result = await inflight; + if (!result.loaded) inflight = null; // 失败可重试；成功保留以幂等短路 + return result; +} diff --git a/public/core/ocr/paddle-ocr-bootstrap.js b/public/core/ocr/paddle-ocr-bootstrap.js new file mode 100644 index 0000000..76441c0 --- /dev/null +++ b/public/core/ocr/paddle-ocr-bootstrap.js @@ -0,0 +1,62 @@ +import { + defaultModelCache, + STATUS_NOT_DOWNLOADED, +} from "../model-cache/availability.js"; +import { createModelManifest } from "../model-cache/manifest.js"; +import { defaultOCRRegistry } from "./ocr-engine.js"; +import { ensureTesseractBootstrap } from "./tesseract-bootstrap.js"; +import { paddleOcrEngine, PADDLE_OCR_MANIFEST_ID, PADDLE_OCR_MODEL_FILES } from "./paddle-ocr-engine.js"; + +let bootstrapped = false; + +export function ensurePaddleOcrBootstrap() { + if (bootstrapped) return; + bootstrapped = true; + + // 在 tesseract 之后注册：保证 placeholder → tesseract → paddle 的注册顺序， + // 都不可用时 pickForTask 回退候选落到 paddle（最高级 engine）。可用时的偏好 + // 排序（paddle 优先于 tesseract）留给 P9-D.4。 + ensureTesseractBootstrap(); + + if (!defaultOCRRegistry.has(paddleOcrEngine.id)) { + defaultOCRRegistry.register(paddleOcrEngine); + } + + if (!defaultModelCache.has(PADDLE_OCR_MANIFEST_ID)) { + const perFile = {}; + for (const file of PADDLE_OCR_MODEL_FILES) perFile[file] = "0".repeat(64); + const manifest = createModelManifest({ + manifestId: PADDLE_OCR_MANIFEST_ID, + task: "ocr-text", + engine: "paddleocr", + modelVersion: "v5", + bundleSize: 16 * 1024 * 1024, + quantization: "int8", + minMemoryMB: 512, + sources: [ + { kind: "on-demand-download", path: "model-cache/ocr-text/paddleocr/v5/ (det/cls/rec onnx)" }, + { kind: "user-provided", path: "PP-OCRv5 ONNX via 安全中心 → 下载/导入" }, + ], + checksums: { + algorithm: "SHA-256", + digest: "0".repeat(64), + perFile, + }, + fallback: { + onFailure: "use-degraded-route", + message: "PP-OCRv5 ONNX 占位 manifest；onnxruntime-web 运行时接入留给 P9-D.2，模型按需下载留给 P9-D.3。", + }, + ui: { + label: "PP-OCRv5 高级 OCR (ONNX/WebGPU)", + description: "比 Tesseract 更高精度的本地 OCR；ONNX Runtime + WebGPU（WASM 回退），数据留在本地、零云端。", + enableHint: "首次启用时按需下载 PP-OCRv5 det/cls/rec ONNX 模型到本地缓存，SHA-256 校验通过后激活。", + }, + }); + defaultModelCache.register(manifest); + defaultModelCache.setStatus(PADDLE_OCR_MANIFEST_ID, STATUS_NOT_DOWNLOADED, { + message: "等待 P9-D.2/P9-D.3 接入 onnxruntime-web 与按需下载；高级 OCR engine 已登记但运行时尚未就位。", + }); + } +} + +ensurePaddleOcrBootstrap(); diff --git a/public/core/ocr/paddle-ocr-engine.js b/public/core/ocr/paddle-ocr-engine.js new file mode 100644 index 0000000..ca05614 --- /dev/null +++ b/public/core/ocr/paddle-ocr-engine.js @@ -0,0 +1,171 @@ +// PP-OCRv5 高级 OCR 引擎骨架（P9-D.1）。比 tesseract 更高精度的本地 OCR engine， +// 走 ONNX Runtime + WebGPU（WASM 回退），数据留在本地、零云端。本轮仅骨架 + 契约 + +// 三阶段拒绝路径；onnxruntime vendor 与真实推理留给 P9-D.2，模型按需下载留给 P9-D.3。 + +import { ConversionError } from "../conversion-error.js"; +import { defaultOCRStorage } from "./ocr-storage.js"; +import { + OCR_ENGINE_FAILED, + OCR_UNAVAILABLE, +} from "./ocr-warnings.js"; +import { loadOnnxRuntime, pickExecutionProviders, createOcrSession, disposeOcrSession } from "./paddle-ocr-runtime.js"; +import { runPaddlePipeline, parseCharDictionary } from "./paddle-ocr-pipeline.js"; + +const DICT_KEY = "paddleocr/v5/dict.txt"; + +// 浏览器端把 image（dataURL/同源 blob URL）解码为 RGBA ImageData。不使用 fetch（遵守 +// 本地禁联网守门）；用 Image + canvas。Node 无 document → 抛错（recognize 在 loadOnnxRuntime +// 阶段已先行拒绝，不会走到这里）。 +async function decodeImageToImageData(image) { + if (typeof globalThis.document?.createElement !== "function" || typeof globalThis.Image !== "function") { + throw new ConversionError("当前运行时无法解码图像（缺少 document/Image）。", { + category: "convert", + code: OCR_ENGINE_FAILED, + details: { engineId: "paddleocr-v5", reason: "image-decode-unavailable" }, + }); + } + const img = new globalThis.Image(); + img.src = image; + if (typeof img.decode === "function") { + await img.decode(); + } else { + await new Promise((resolve, reject) => { + img.onload = resolve; + img.onerror = () => reject(new Error("image load failed")); + }); + } + const width = img.naturalWidth || img.width; + const height = img.naturalHeight || img.height; + const canvas = globalThis.document.createElement("canvas"); + canvas.width = width; + canvas.height = height; + const ctx = canvas.getContext("2d"); + ctx.drawImage(img, 0, 0, width, height); + const { data } = ctx.getImageData(0, 0, width, height); + return { data, width, height }; +} + +export const PADDLE_OCR_MANIFEST_ID = "ocr-text.paddleocr.v5"; + +// PP-OCRv5 ONNX 模型（检测 / 方向分类 / 识别）。全集供 UI 列举/清理；可用性只看必选集。 +const MODEL_KEY_PREFIX = "paddleocr/v5/"; +export const PADDLE_OCR_MODEL_FILES = Object.freeze(["det.onnx", "cls.onnx", "rec.onnx"]); +// 必选集：det（DB 检测）+ rec（CTC 识别）。cls（方向分类）为可选——管线运行时已容忍其 +// 缺失（clsSession 为 null 时跳过 180° 校正），故不纳入可用性闸门。 +export const PADDLE_OCR_REQUIRED_FILES = Object.freeze(["det.onnx", "rec.onnx"]); + +// 就绪状态放模块级可变变量，而非冻结对象的实例属性（冻结对象在严格模式下无法被 +// ensureProbe 赋值）。引擎对象本身仍可 Object.freeze 防外部篡改。 +let modelsReady = false; + +function vendorReady() { + return Boolean(globalThis.__t2fPaddleOcrVendorReady); +} + +async function hasAllModels(storage) { + for (const file of PADDLE_OCR_REQUIRED_FILES) { + if (!(await storage.has(`${MODEL_KEY_PREFIX}${file}`))) return false; + } + return true; +} + +export const paddleOcrEngine = Object.freeze({ + id: "paddleocr-v5", + taskCapabilities: ["ocr-text", "ocr-layout"], + manifestId: PADDLE_OCR_MANIFEST_ID, + // 高级引擎：可用时经 pickForTask 优先于 tesseract(10) / placeholder(0)。 + priority: 20, + + // 与 OCREngineRegistry 一致：同步 isAvailable，由 ensureProbe() 在 recognize 前刷新缓存。 + // P9-D.1 阶段 vendor 未就位 + 模型未下载，恒为 false。 + isAvailable() { + if (!vendorReady()) return false; + return Boolean(modelsReady); + }, + + _storage: defaultOCRStorage, + + async ensureProbe() { + if (!vendorReady()) { + modelsReady = false; + return false; + } + modelsReady = await hasAllModels(this._storage); + return modelsReady; + }, + + async recognize({ image, options } = {}) { + if (!vendorReady()) { + throw new ConversionError( + "PP-OCRv5 ONNX runtime 未就位，无法执行高级 OCR。onnxruntime-web vendor 接入留给 P9-D.2。", + { + category: "convert", + code: OCR_UNAVAILABLE, + details: { engineId: "paddleocr-v5", manifestId: PADDLE_OCR_MANIFEST_ID, reason: "vendor-not-ready" }, + }, + ); + } + if (!(await hasAllModels(this._storage))) { + throw new ConversionError( + "未在本地缓存中找到 PP-OCRv5 必选模型（det/rec）；请先在安全中心导入/下载（cls 方向分类可选）。", + { + category: "convert", + code: OCR_UNAVAILABLE, + details: { engineId: "paddleocr-v5", manifestId: PADDLE_OCR_MANIFEST_ID, reason: "model-missing" }, + }, + ); + } + if (!image) { + throw new ConversionError("OCR 输入图像缺失。", { + category: "validate", + code: OCR_ENGINE_FAILED, + details: { engineId: "paddleocr-v5", reason: "missing-image" }, + }); + } + // P9-D.2.b：真实推理管线。Node/未 vendor 在 loadOnnxRuntime 抛 OCR_VENDOR_LOAD_FAILED。 + const ort = await loadOnnxRuntime(); + const providers = pickExecutionProviders(); + let detSession = null; + let clsSession = null; + let recSession = null; + try { + const imageData = await decodeImageToImageData(image); + const [detBuf, clsBuf, recBuf] = await Promise.all([ + this._storage.get(`${MODEL_KEY_PREFIX}det.onnx`), + this._storage.get(`${MODEL_KEY_PREFIX}cls.onnx`), + this._storage.get(`${MODEL_KEY_PREFIX}rec.onnx`), + ]); + const dictBuf = await this._storage.get(DICT_KEY); + const dictionary = dictBuf + ? parseCharDictionary(new TextDecoder().decode(dictBuf instanceof ArrayBuffer ? new Uint8Array(dictBuf) : dictBuf)) + : []; + detSession = await createOcrSession({ ort, modelBuffer: detBuf, providers }); + clsSession = clsBuf ? await createOcrSession({ ort, modelBuffer: clsBuf, providers }) : null; + recSession = await createOcrSession({ ort, modelBuffer: recBuf, providers }); + return await runPaddlePipeline({ + ort, + detSession, + clsSession, + recSession, + imageData, + dictionary, + options: options || {}, + }); + } catch (error) { + if (error instanceof ConversionError) throw error; + throw new ConversionError(`PP-OCRv5 推理失败：${error?.message || error}`, { + category: "convert", + code: OCR_ENGINE_FAILED, + details: { engineId: "paddleocr-v5", reason: "inference-failed", providers, cause: String(error?.name || error?.message || "unknown") }, + }); + } finally { + await disposeOcrSession(detSession); + await disposeOcrSession(clsSession); + await disposeOcrSession(recSession); + } + }, +}); + +export function markPaddleOcrVendorReady(ready = true) { + globalThis.__t2fPaddleOcrVendorReady = Boolean(ready); +} diff --git a/public/core/ocr/paddle-ocr-pipeline.js b/public/core/ocr/paddle-ocr-pipeline.js new file mode 100644 index 0000000..e31296b --- /dev/null +++ b/public/core/ocr/paddle-ocr-pipeline.js @@ -0,0 +1,601 @@ +// PP-OCRv5 推理管线（P9-D.2.b）：检测(det) + 方向(cls) + 识别(rec) 三段 ONNX 前向 + +// 经典前后处理串成 OCRResult。前后处理为纯函数，Node 可完整单测；runPaddlePipeline 接受 +// 可注入 session，便于用 mock 端到端测试（无需真实模型）。数据全程留在本地。 + +import { ConversionError } from "../conversion-error.js"; +import { createOCRResult } from "./ocr-result.js"; + +export const DET_LIMIT_SIDE_LEN = 960; +export const REC_IMAGE_HEIGHT = 48; +export const DET_MEAN = [0.485, 0.456, 0.406]; +export const DET_STD = [0.229, 0.224, 0.225]; + +function clamp(value, min, max) { + return Math.min(Math.max(value, min), max); +} + +// PP-OCR 字典：每行一个 token；CTC blank 占 index 0，末尾保证恰好一个 ASCII 空格（use_space_char）。 +// 注意：仅跳过「完全空行」（length 0），不可用 trim() —— 字典首个合法 token 常是全角空格 U+3000， +// trim() 会误删它造成全表错位。某些字典文件（如 ppu ppocrv5_dict）已把空格作为最后一行显式列出； +// 此时不再重复追加，否则类别数比模型多 1，CTC 解码整体错位。 +export function parseCharDictionary(text) { + const lines = String(text ?? "").replace(/\r\n/g, "\n").replace(/\r/g, "\n").split("\n"); + const chars = []; + for (const line of lines) { + if (line.length === 0) continue; + chars.push(line); + } + if (chars[chars.length - 1] !== " ") chars.push(" "); + return ["", ...chars]; +} + +// 最近邻重采样 RGBA 到目标尺寸。imageData = { data: Uint8ClampedArray(RGBA), width, height }。 +export function resizeRgba(imageData, dstW, dstH) { + const { data, width, height } = imageData; + if (width <= 0 || height <= 0 || dstW <= 0 || dstH <= 0) { + throw new RangeError("resizeRgba: dimensions must be positive."); + } + const out = new Uint8ClampedArray(dstW * dstH * 4); + for (let y = 0; y < dstH; y += 1) { + const sy = Math.min(height - 1, Math.floor((y * height) / dstH)); + for (let x = 0; x < dstW; x += 1) { + const sx = Math.min(width - 1, Math.floor((x * width) / dstW)); + const so = (sy * width + sx) * 4; + const dstO = (y * dstW + x) * 4; + out[dstO] = data[so]; + out[dstO + 1] = data[so + 1]; + out[dstO + 2] = data[so + 2]; + out[dstO + 3] = data[so + 3]; + } + } + return { data: out, width: dstW, height: dstH }; +} + +function roundToMultiple(value, multiple, min) { + const rounded = Math.max(min, Math.round(value / multiple) * multiple); + return rounded; +} + +// 检测预处理：限制最长边 + 取 32 倍数 + ImageNet 归一化 → NCHW Float32。 +export function preprocessForDetection(imageData, { limitSideLen = DET_LIMIT_SIDE_LEN } = {}) { + const { width, height } = imageData; + const maxSide = Math.max(width, height); + const ratio = maxSide > limitSideLen ? limitSideLen / maxSide : 1; + const resizedW = roundToMultiple(width * ratio, 32, 32); + const resizedH = roundToMultiple(height * ratio, 32, 32); + const resized = resizeRgba(imageData, resizedW, resizedH); + const data = new Float32Array(3 * resizedH * resizedW); + const plane = resizedH * resizedW; + for (let i = 0; i < plane; i += 1) { + const o = i * 4; + data[i] = (resized.data[o] / 255 - DET_MEAN[0]) / DET_STD[0]; + data[plane + i] = (resized.data[o + 1] / 255 - DET_MEAN[1]) / DET_STD[1]; + data[2 * plane + i] = (resized.data[o + 2] / 255 - DET_MEAN[2]) / DET_STD[2]; + } + return { + data, + dims: [1, 3, resizedH, resizedW], + resizedWidth: resizedW, + resizedHeight: resizedH, + scaleW: width / resizedW, + scaleH: height / resizedH, + }; +} + +// 识别预处理：高度固定 48，宽按比例（封顶），归一化到 [-1,1] → NCHW Float32。 +export function preprocessForRecognition(imageData, { height = REC_IMAGE_HEIGHT, maxWidth = 1280 } = {}) { + const ratio = imageData.height > 0 ? imageData.width / imageData.height : 1; + const targetW = clamp(Math.max(1, Math.round(height * ratio)), 1, maxWidth); + const resized = resizeRgba(imageData, targetW, height); + const data = new Float32Array(3 * height * targetW); + const plane = height * targetW; + for (let i = 0; i < plane; i += 1) { + const o = i * 4; + data[i] = (resized.data[o] / 255 - 0.5) / 0.5; + data[plane + i] = (resized.data[o + 1] / 255 - 0.5) / 0.5; + data[2 * plane + i] = (resized.data[o + 2] / 255 - 0.5) / 0.5; + } + return { data, dims: [1, 3, height, targetW], width: targetW, height }; +} + +// DB 检测后处理：阈值二值化 + 4-连通域 + 轴对齐 bbox + box 分数过滤 + 缩放回原图坐标。 +export function dbPostProcess(probData, mapW, mapH, { + thresh = 0.3, + boxThresh = 0.5, + minSize = 3, + unclipRatio = 1.6, + scaleW = 1, + scaleH = 1, +} = {}) { + if (!probData || probData.length < mapW * mapH) { + throw new ConversionError("dbPostProcess: probability map smaller than mapW*mapH.", { + category: "validate", + code: "OCR_ENGINE_INVALID", + details: { reason: "prob-map-too-small" }, + }); + } + const visited = new Uint8Array(mapW * mapH); + const boxes = []; + const stack = []; + for (let start = 0; start < mapW * mapH; start += 1) { + if (visited[start]) continue; + if (probData[start] <= thresh) { + visited[start] = 1; + continue; + } + // BFS/DFS connected component + let minX = mapW; + let minY = mapH; + let maxX = 0; + let maxY = 0; + let sum = 0; + let count = 0; + stack.length = 0; + stack.push(start); + visited[start] = 1; + while (stack.length > 0) { + const idx = stack.pop(); + const px = idx % mapW; + const py = (idx - px) / mapW; + sum += probData[idx]; + count += 1; + if (px < minX) minX = px; + if (px > maxX) maxX = px; + if (py < minY) minY = py; + if (py > maxY) maxY = py; + const neighbors = [ + px > 0 ? idx - 1 : -1, + px < mapW - 1 ? idx + 1 : -1, + py > 0 ? idx - mapW : -1, + py < mapH - 1 ? idx + mapW : -1, + ]; + for (const n of neighbors) { + if (n < 0 || visited[n]) continue; + if (probData[n] > thresh) { + visited[n] = 1; + stack.push(n); + } else { + visited[n] = 1; + } + } + } + const score = count > 0 ? sum / count : 0; + let boxW = maxX - minX + 1; + let boxH = maxY - minY + 1; + if (score < boxThresh) continue; + if (boxW < minSize || boxH < minSize) continue; + // unclip：DB 概率图相对真实文字是收缩的，按 PP-OCR 用 area*ratio/perimeter 向外扩， + // 否则裁剪框过紧、切掉字符笔画导致识别错乱。 + const distance = (boxW * boxH * unclipRatio) / Math.max(1, 2 * (boxW + boxH)); + let ex0 = minX - distance; + let ey0 = minY - distance; + let ex1 = maxX + distance; + let ey1 = maxY + distance; + ex0 = Math.max(0, ex0); + ey0 = Math.max(0, ey0); + ex1 = Math.min(mapW - 1, ex1); + ey1 = Math.min(mapH - 1, ey1); + boxes.push({ + x: Math.round(ex0 * scaleW), + y: Math.round(ey0 * scaleH), + w: Math.round((ex1 - ex0 + 1) * scaleW), + h: Math.round((ey1 - ey0 + 1) * scaleH), + score, + }); + } + // 阅读顺序：上→下，再左→右（粗启发，多栏留后）。 + boxes.sort((a, b) => (a.y - b.y) || (a.x - b.x)); + return boxes; +} + +// 噪点估计：采样像素，统计与 3×3 邻域中值相差很大（孤立跳变，椒盐特征）的灰度像素比例。 +// 文字边缘也会产生差异但占比小；椒盐噪点会显著抬高该比例。返回 [0,1] 的噪点比例。 +export function estimateNoiseLevel(imageData, { jump = 80, step = 2 } = {}) { + const { data, width, height } = imageData; + if (width < 3 || height < 3) return 0; + const gray = (o) => (data[o] * 299 + data[o + 1] * 587 + data[o + 2] * 114) / 1000; + let speckle = 0; + let sampled = 0; + const win = []; + for (let y = 1; y < height - 1; y += step) { + for (let x = 1; x < width - 1; x += step) { + win.length = 0; + for (let dy = -1; dy <= 1; dy += 1) { + for (let dx = -1; dx <= 1; dx += 1) { + win.push(gray(((y + dy) * width + (x + dx)) * 4)); + } + } + win.sort((a, b) => a - b); + const med = win[4]; + if (Math.abs(gray((y * width + x) * 4) - med) > jump) speckle += 1; + sampled += 1; + } + } + return sampled > 0 ? speckle / sampled : 0; +} + +// 图像去噪：3×3 中值滤波（逐通道取邻域中值）。对椒盐/背景杂点有效且保边， +// 用于 OCR 前清理噪点，改善带噪图 / 艺术字背景的识别。alpha 透传。 +export function denoiseImageData(imageData, { window = 3 } = {}) { + const { data, width, height } = imageData; + if (width < 3 || height < 3) return imageData; + const radius = Math.max(1, Math.floor(window / 2)); + const out = new Uint8ClampedArray(data.length); + const win = []; + for (let y = 0; y < height; y += 1) { + for (let x = 0; x < width; x += 1) { + const o = (y * width + x) * 4; + for (let c = 0; c < 3; c += 1) { + win.length = 0; + for (let dy = -radius; dy <= radius; dy += 1) { + const yy = Math.min(height - 1, Math.max(0, y + dy)); + for (let dx = -radius; dx <= radius; dx += 1) { + const xx = Math.min(width - 1, Math.max(0, x + dx)); + win.push(data[(yy * width + xx) * 4 + c]); + } + } + win.sort((a, b) => a - b); + out[o + c] = win[win.length >> 1]; + } + out[o + 3] = data[o + 3]; + } + } + return { data: out, width, height }; +} + +// 按任意角度旋转 RGBA 图像（最近邻，画布扩展以容纳，背景默认白）。正角度 = 逆时针。 +export function rotateImageDataByAngle(imageData, degrees, { background = 255 } = {}) { + const { data, width: W, height: H } = imageData; + const a = (degrees * Math.PI) / 180; + const c = Math.cos(a); + const s = Math.sin(a); + const nw = Math.max(1, Math.ceil(Math.abs(W * c) + Math.abs(H * s))); + const nh = Math.max(1, Math.ceil(Math.abs(W * s) + Math.abs(H * c))); + const out = new Uint8ClampedArray(nw * nh * 4).fill(background); + // 背景 alpha 设满 + for (let i = 3; i < out.length; i += 4) out[i] = 255; + const cx = W / 2; + const cy = H / 2; + const ncx = nw / 2; + const ncy = nh / 2; + for (let y = 0; y < nh; y += 1) { + for (let x = 0; x < nw; x += 1) { + const dx = x - ncx; + const dy = y - ncy; + const sx = Math.round(dx * c + dy * s + cx); + const sy = Math.round(-dx * s + dy * c + cy); + if (sx >= 0 && sx < W && sy >= 0 && sy < H) { + const so = (sy * W + sx) * 4; + const dstO = (y * nw + x) * 4; + out[dstO] = data[so]; out[dstO + 1] = data[so + 1]; out[dstO + 2] = data[so + 2]; out[dstO + 3] = data[so + 3]; + } + } + } + return { data: out, width: nw, height: nh }; +} + +// 估计文档倾斜角：对 det 概率图二值化后，用「错切投影直方图方差」找让文本行最对齐水平的角度。 +// 返回应当旋转的角度（度），使图像去倾斜（正角度 = 逆时针）。范围 [-maxAngle, maxAngle]。 +export function estimateSkewAngle(probData, mapW, mapH, { maxAngle = 12, step = 1, thresh = 0.3 } = {}) { + // 收集文本像素坐标（下采样以提速） + const pts = []; + const sub = Math.max(1, Math.floor(Math.max(mapW, mapH) / 160)); + for (let y = 0; y < mapH; y += sub) { + for (let x = 0; x < mapW; x += sub) { + if (probData[y * mapW + x] > thresh) pts.push([x, y]); + } + } + if (pts.length < 20) return 0; + let bestAngle = 0; + let bestVar = -1; + for (let deg = -maxAngle; deg <= maxAngle; deg += step) { + const a = (deg * Math.PI) / 180; + const c = Math.cos(a); + const s = Math.sin(a); + // 旋转后行坐标的直方图（按行 bin 统计文本像素），方差越大表示文本行越对齐水平 + const hist = new Map(); + for (const [x, y] of pts) { + const ry = Math.round(-x * s + y * c); + hist.set(ry, (hist.get(ry) || 0) + 1); + } + let sum = 0; + let sumSq = 0; + let n = 0; + for (const v of hist.values()) { sum += v; sumSq += v * v; n += 1; } + if (n === 0) continue; + const mean = sum / n; + const variance = sumSq / n - mean * mean; + if (variance > bestVar) { bestVar = variance; bestAngle = deg; } + } + return bestAngle; +} + +// 旋转 RGBA 图像。rotateImageData180：上下左右翻转（cls 检测到 180° 时用）。 +export function rotateImageData180(imageData) { + const { data, width, height } = imageData; + const out = new Uint8ClampedArray(data.length); + for (let y = 0; y < height; y += 1) { + for (let x = 0; x < width; x += 1) { + const s = (y * width + x) * 4; + const d = ((height - 1 - y) * width + (width - 1 - x)) * 4; + out[d] = data[s]; out[d + 1] = data[s + 1]; out[d + 2] = data[s + 2]; out[d + 3] = data[s + 3]; + } + } + return { data: out, width, height }; +} + +// 旋转 90°（dir: "cw" 顺时针 / "ccw" 逆时针）。输出宽高互换。用于竖排 / 侧向文本。 +export function rotateImageData90(imageData, dir = "cw") { + const { data, width, height } = imageData; + const ow = height; + const oh = width; + const out = new Uint8ClampedArray(ow * oh * 4); + for (let y = 0; y < height; y += 1) { + for (let x = 0; x < width; x += 1) { + const s = (y * width + x) * 4; + let ox; + let oy; + if (dir === "cw") { ox = height - 1 - y; oy = x; } else { ox = y; oy = width - 1 - x; } + const d = (oy * ow + ox) * 4; + out[d] = data[s]; out[d + 1] = data[s + 1]; out[d + 2] = data[s + 2]; out[d + 3] = data[s + 3]; + } + } + return { data: out, width: ow, height: oh }; +} + +// cls 输出 [c0, c1] softmax；c1 高表示需要旋转 180°。返回 { flip, confidence }。 +export function interpretClsOutput(clsData, threshold = 0.6) { + const c0 = clsData?.[0] ?? 1; + const c1 = clsData?.[1] ?? 0; + return { flip: c1 > c0 && c1 >= threshold, confidence: Math.max(c0, c1) }; +} + +// 裁剪 RGBA 区域（坐标 clamp 到图内）。 +export function cropImageData(imageData, box) { + const { data, width, height } = imageData; + const x0 = clamp(Math.floor(box.x), 0, Math.max(0, width - 1)); + const y0 = clamp(Math.floor(box.y), 0, Math.max(0, height - 1)); + const cw = clamp(Math.round(box.w), 1, width - x0); + const ch = clamp(Math.round(box.h), 1, height - y0); + const out = new Uint8ClampedArray(cw * ch * 4); + for (let y = 0; y < ch; y += 1) { + for (let x = 0; x < cw; x += 1) { + const so = ((y0 + y) * width + (x0 + x)) * 4; + const dstO = (y * cw + x) * 4; + out[dstO] = data[so]; + out[dstO + 1] = data[so + 1]; + out[dstO + 2] = data[so + 2]; + out[dstO + 3] = data[so + 3]; + } + } + return { data: out, width: cw, height: ch }; +} + +// CTC 贪心解码：逐时刻 argmax → 折叠连续重复 → 去 blank(0) → 映射字典。 +// logitsData 按 [T, C] 行主序；dictionary[idx] 给出字符（idx 0 为 blank）。 +export function ctcGreedyDecode(logitsData, timeSteps, numClasses, dictionary = []) { + let text = ""; + let confSum = 0; + let confCount = 0; + let prevIdx = -1; + for (let t = 0; t < timeSteps; t += 1) { + const base = t * numClasses; + let bestIdx = 0; + let bestVal = -Infinity; + for (let c = 0; c < numClasses; c += 1) { + const v = logitsData[base + c]; + if (v > bestVal) { + bestVal = v; + bestIdx = c; + } + } + if (bestIdx !== prevIdx && bestIdx !== 0) { + const ch = dictionary[bestIdx]; + if (typeof ch === "string" && ch !== "") { + text += ch; + confSum += bestVal; + confCount += 1; + } + } + prevIdx = bestIdx; + } + const confidence = confCount > 0 ? clamp(confSum / confCount, 0, 1) : 0; + return { text, confidence }; +} + +function firstOutput(session, result) { + const name = Array.isArray(session.outputNames) && session.outputNames.length > 0 + ? session.outputNames[0] + : Object.keys(result)[0]; + return result[name]; +} + +function firstInputName(session) { + return Array.isArray(session.inputNames) && session.inputNames.length > 0 + ? session.inputNames[0] + : "x"; +} + +async function runSession(ort, session, { data, dims }) { + const tensor = new ort.Tensor("float32", data, dims); + const feeds = { [firstInputName(session)]: tensor }; + const result = await session.run(feeds); + return firstOutput(session, result); +} + +// 编排器：imageData + 三段 session + 字典 → OCRResult。ort 仅用于构造 Tensor。 +export async function runPaddlePipeline({ + ort, + detSession, + clsSession = null, + recSession, + imageData, + dictionary = [], + options = {}, +} = {}) { + if (!ort || typeof ort.Tensor !== "function") { + throw new ConversionError("runPaddlePipeline requires an onnxruntime namespace with Tensor.", { + category: "validate", + code: "OCR_ENGINE_INVALID", + details: { reason: "missing-ort" }, + }); + } + if (!detSession || !recSession) { + throw new ConversionError("runPaddlePipeline requires det and rec sessions.", { + category: "validate", + code: "OCR_ENGINE_INVALID", + details: { reason: "missing-sessions" }, + }); + } + const startedAt = Date.now(); + + // 去噪：默认 auto——仅当估计噪点比例超过阈值时才中值滤波（中值滤波会软化干净图、 + // 降低清晰文本置信度，所以干净图绝不去噪）。options.denoise: "auto"|true|false。 + const denoiseMode = options.denoise ?? "auto"; + const denoiseThreshold = typeof options.denoiseThreshold === "number" ? options.denoiseThreshold : 0.05; + let noiseLevel = 0; + let denoised = false; + let workImage = imageData; + if (denoiseMode === true) { + workImage = denoiseImageData(imageData, options.denoiseWindow ? { window: options.denoiseWindow } : {}); + denoised = true; + } else if (denoiseMode !== false) { + noiseLevel = estimateNoiseLevel(imageData); + if (noiseLevel > denoiseThreshold) { + workImage = denoiseImageData(imageData, options.denoiseWindow ? { window: options.denoiseWindow } : {}); + denoised = true; + } + } + + // 单次检测：返回 prob 图 + 还原坐标的 scale。 + async function detect(image) { + const detInput = preprocessForDetection(image, options.det || {}); + const detOut = await runSession(ort, detSession, { data: detInput.data, dims: detInput.dims }); + const pd = detOut?.data || detOut; + const dims = detOut?.dims || [1, 1, detInput.resizedHeight, detInput.resizedWidth]; + const mh = dims[dims.length - 2]; + const mw = dims[dims.length - 1]; + return { pd, mw, mh, scaleW: detInput.scaleW * (detInput.resizedWidth / mw), scaleH: detInput.scaleH * (detInput.resizedHeight / mh) }; + } + + let det = await detect(workImage); + // 去倾斜：从 det 概率图估倾斜角，超阈值则把图旋正后重检（仅倾斜图付二次检测代价； + // 正立图估计≈0 不重检）。识别仍只跑一次（在最终图上）。options.deskew: true(默认)|false。 + let skewApplied = 0; + const minSkew = typeof options.minSkew === "number" ? options.minSkew : 3; + if (options.deskew !== false) { + const est = estimateSkewAngle(det.pd, det.mw, det.mh, options.skew || {}); + if (Math.abs(est) >= minSkew) { + workImage = rotateImageDataByAngle(workImage, -est); + skewApplied = est; + det = await detect(workImage); + } + } + const probData = det.pd; + const mapW = det.mw; + const mapH = det.mh; + const boxes = dbPostProcess(probData, mapW, mapH, { + ...(options.db || {}), + scaleW: det.scaleW, + scaleH: det.scaleH, + }); + + const verticalAspect = typeof options.verticalAspect === "number" ? options.verticalAspect : 1.5; + const clsThreshold = typeof options.clsThreshold === "number" ? options.clsThreshold : 0.6; + const lowConfidence = typeof options.lowConfidence === "number" ? options.lowConfidence : 0.6; + + // 对单个裁剪做：可选 cls 180° 校正 → rec → CTC，返回 { text, confidence }。 + async function recognizeCrop(cropImg) { + let img = cropImg; + let orientation = "0"; + if (clsSession) { + try { + const clsPre = preprocessForRecognition(img, options.cls || options.rec || {}); + const clsOut = await runSession(ort, clsSession, { data: clsPre.data, dims: clsPre.dims }); + const { flip } = interpretClsOutput(clsOut?.data || clsOut, clsThreshold); + if (flip) { + img = rotateImageData180(img); + orientation = "180"; + } + } catch (error) { + // 方向分类失败不致命，按原图识别。 + } + } + const recPre = preprocessForRecognition(img, options.rec || {}); + const recOut = await runSession(ort, recSession, { data: recPre.data, dims: recPre.dims }); + const logits = recOut?.data || recOut; + const recDims = recOut?.dims || [1, 0, dictionary.length]; + const decoded = ctcGreedyDecode(logits, recDims[recDims.length - 2], recDims[recDims.length - 1], dictionary); + return { ...decoded, orientation }; + } + + const lines = []; + for (const box of boxes) { + const crop = cropImageData(workImage, box); + // 竖排 / 侧向文本：高宽比偏高的框，额外尝试旋转 90°（cw + ccw），按识别置信度取最优。 + const candidates = [{ img: crop, rot: "0" }]; + if (box.h > box.w * verticalAspect) { + candidates.push({ img: rotateImageData90(crop, "cw"), rot: "90cw" }); + candidates.push({ img: rotateImageData90(crop, "ccw"), rot: "90ccw" }); + } + let best = null; + for (const cand of candidates) { + let decoded; + try { + decoded = await recognizeCrop(cand.img); + } catch (error) { + continue; + } + if (decoded.text.trim().length === 0) continue; + if (!best || decoded.confidence > best.confidence) { + best = { ...decoded, rotation: cand.rot }; + } + } + if (best) { + lines.push({ + text: best.text, + confidence: best.confidence, + bbox: { x: box.x, y: box.y, w: box.w, h: box.h }, + orientation: best.rotation === "0" ? best.orientation : best.rotation, + lowConfidence: best.confidence < lowConfidence, + }); + } + } + + const confs = lines.map((l) => l.confidence); + const averageConfidence = confs.length > 0 ? clamp(confs.reduce((s, c) => s + c, 0) / confs.length, 0, 1) : 0; + const lowConfidenceLines = lines.filter((l) => l.lowConfidence).length; + // 质量把控摘要：整体/最低置信度、低置信行数、是否有旋转校正。 + const quality = { + lineCount: lines.length, + averageConfidence, + minConfidence: confs.length > 0 ? clamp(Math.min(...confs), 0, 1) : 0, + lowConfidenceLines, + rotatedLines: lines.filter((l) => l.orientation && l.orientation !== "0").length, + denoised, + noiseLevel, + skewApplied, + grade: averageConfidence >= 0.9 && lowConfidenceLines === 0 + ? "high" + : (averageConfidence >= 0.7 ? "medium" : "low"), + }; + + const result = createOCRResult({ + language: options.language || "auto", + pages: [ + { + pageIndex: 0, + width: imageData.width, + height: imageData.height, + lines, + }, + ], + fullText: lines.map((l) => l.text).join("\n"), + averageConfidence, + runtimeMs: Date.now() - startedAt, + engine: "paddleocr-v5", + modelVersion: "v5", + warnings: [], + }); + return { ...result, quality }; +} diff --git a/public/core/ocr/paddle-ocr-runtime.js b/public/core/ocr/paddle-ocr-runtime.js new file mode 100644 index 0000000..ce04277 --- /dev/null +++ b/public/core/ocr/paddle-ocr-runtime.js @@ -0,0 +1,95 @@ +// PP-OCRv5 ONNX Runtime 运行时加载器（P9-D.2）。dynamic import 同源 vendor onnxruntime-web， +// WebGPU 优先 / WASM 回退选择执行后端，提供 InferenceSession 创建/释放骨架。数据留在本地、 +// 零云端。真实 det/cls/rec 推理管线 + CTC 解码留给 P9-D.2.b。 + +import { ConversionError } from "../conversion-error.js"; + +export const OCR_VENDOR_LOAD_FAILED = "OCR_VENDOR_LOAD_FAILED"; + +export const PADDLE_VENDOR_PATHS = Object.freeze({ + // ORT 的 ESM 入口；浏览器/Tauri 端从同源 vendor 目录加载，wasm 二进制亦在该目录。 + mainBundle: "/vendor/onnxruntime/ort.min.mjs", + wasmDir: "/vendor/onnxruntime/", +}); + +let cachedNamespace = null; + +function hasWebGPU() { + return typeof globalThis !== "undefined" + && typeof globalThis.navigator === "object" + && globalThis.navigator !== null + && typeof globalThis.navigator.gpu === "object" + && globalThis.navigator.gpu !== null; +} + +// WebGPU 可用 → ["webgpu","wasm"]（webgpu 优先，wasm 回退）；否则 ["wasm"]。 +// Node（无 navigator.gpu）返回 ["wasm"]，纯函数可测。 +export function pickExecutionProviders() { + return hasWebGPU() ? ["webgpu", "wasm"] : ["wasm"]; +} + +export async function loadOnnxRuntime(vendorUrl = PADDLE_VENDOR_PATHS.mainBundle) { + if (cachedNamespace) return cachedNamespace; + try { + const ort = await import(/* @vite-ignore */ vendorUrl); + const namespace = ort?.default && ort.default.InferenceSession ? ort.default : ort; + if (!namespace || !namespace.InferenceSession) { + throw new Error("vendor onnxruntime-web missing InferenceSession"); + } + // 让 ORT 从同源 vendor 目录加载 wasm 二进制，绝不联网。 + if (namespace.env?.wasm) { + namespace.env.wasm.wasmPaths = PADDLE_VENDOR_PATHS.wasmDir; + } + cachedNamespace = namespace; + return cachedNamespace; + } catch (error) { + throw new ConversionError( + `onnxruntime-web vendor 加载失败：${error?.message || error}`, + { + category: "convert", + code: OCR_VENDOR_LOAD_FAILED, + details: { + path: vendorUrl, + cause: String(error?.name || error?.message || "unknown"), + }, + }, + ); + } +} + +export async function createOcrSession({ ort, modelBuffer, providers = pickExecutionProviders() } = {}) { + if (!ort || !ort.InferenceSession) { + throw new ConversionError("onnxruntime namespace 未就位，无法创建 InferenceSession。", { + category: "convert", + code: OCR_VENDOR_LOAD_FAILED, + details: { reason: "namespace-missing" }, + }); + } + if (!modelBuffer) { + throw new ConversionError("createOcrSession requires an ONNX model buffer.", { + category: "validate", + code: "OCR_ENGINE_INVALID", + details: { reason: "missing-model-buffer" }, + }); + } + try { + const data = modelBuffer instanceof ArrayBuffer ? new Uint8Array(modelBuffer) : modelBuffer; + return await ort.InferenceSession.create(data, { executionProviders: providers }); + } catch (error) { + throw new ConversionError(`ONNX InferenceSession 创建失败：${error?.message || error}`, { + category: "convert", + code: "OCR_ENGINE_FAILED", + details: { reason: "session-create-failed", providers, cause: String(error?.name || error?.message || "unknown") }, + }); + } +} + +export async function disposeOcrSession(session) { + if (session && typeof session.release === "function") { + try { await session.release(); } catch (error) { /* ignore */ } + } +} + +export function resetOnnxRuntimeCache() { + cachedNamespace = null; +} diff --git a/public/core/ocr/png-ocr.js b/public/core/ocr/png-ocr.js index 2c64e1c..00a3403 100644 --- a/public/core/ocr/png-ocr.js +++ b/public/core/ocr/png-ocr.js @@ -1,7 +1,7 @@ -import { createParagraph } from "../document-model.js"; import { withWarnings } from "../warnings.js"; import { defaultOCRRegistry } from "./ocr-engine.js"; import { summarizeOCRResult } from "./ocr-result.js"; +import { blocksFromOcrResult, mapLinesToBlockIds } from "./ocr-structure.js"; import { createOCRUnavailableWarning, createOCREngineFailedWarning, @@ -36,19 +36,6 @@ function cloneModel(model) { }; } -function paragraphsFromOCR(result) { - const pages = Array.isArray(result?.pages) ? result.pages : []; - const paragraphs = []; - for (const page of pages) { - const lines = Array.isArray(page.lines) ? page.lines : []; - const text = lines.map((line) => line.text).filter(Boolean).join("\n"); - if (text.trim().length > 0) paragraphs.push(createParagraph(text)); - } - if (paragraphs.length === 0 && typeof result?.fullText === "string" && result.fullText.trim().length > 0) { - paragraphs.push(createParagraph(result.fullText)); - } - return paragraphs; -} export async function enhanceWithOCR(model, { engine = null, registry = defaultOCRRegistry } = {}) { const resolvedEngine = engine || registry.pickForTask("ocr-text"); @@ -106,7 +93,8 @@ export async function enhanceWithOCR(model, { engine = null, registry = defaultO return next; } - const paragraphs = paragraphsFromOCR(result); + // 格式识别增强：按版面（bbox/行高/间距）把识别行归并成标题+段落；几何不足时回退。 + const paragraphs = blocksFromOcrResult(result); const ocrWarnings = []; if (typeof result?.averageConfidence === "number" && result.averageConfidence < LOW_CONFIDENCE_THRESHOLD) { ocrWarnings.push(createOCRLowConfidenceWarning({ @@ -119,6 +107,11 @@ export async function enhanceWithOCR(model, { engine = null, registry = defaultO const enhanced = cloneModel(model); const appendedStart = enhanced.blocks.length; enhanced.blocks = [...enhanced.blocks, ...paragraphs]; + // 给 OCR 追加块预赋稳定 id（绝对索引），让低置信修复能按 block.id 命中。document-audit 的 + // `id: block.id || ...` 会保留它，且 "ocr-block-" 前缀不与审计的 "block-N-hash" 冲突。 + for (let i = appendedStart; i < enhanced.blocks.length; i += 1) { + if (!enhanced.blocks[i].id) enhanced.blocks[i].id = `ocr-block-${i}`; + } enhanced.metadata = withWarnings(enhanced.metadata, ocrWarnings); enhanced.metadata.modelReview = { ...(enhanced.metadata.modelReview || {}), @@ -127,6 +120,8 @@ export async function enhanceWithOCR(model, { engine = null, registry = defaultO tasks: Array.from(new Set([...(enhanced.metadata.modelReview?.tasks || []), "ocr-text-recognition"])), inferenceMode: "local", ocr: summarizeOCRResult(result), + // 质量把控：若引擎提供了质量评估（置信度分级、低置信行、旋转校正数），一并记录。 + ...(result?.quality ? { ocrQuality: result.quality } : {}), }; enhanced.metadata.ocr = collectLineMetadata(result, enhanced.blocks, appendedStart); return enhanced; @@ -134,24 +129,25 @@ export async function enhanceWithOCR(model, { engine = null, registry = defaultO function collectLineMetadata(result, blocks, appendedStart) { const pages = Array.isArray(result?.pages) ? result.pages : []; - const lines = []; + const flat = []; pages.forEach((page, pageIndex) => { const pageLines = Array.isArray(page.lines) ? page.lines : []; pageLines.forEach((line, lineIndex) => { - // Each appended paragraph corresponds to a page; pick the block that - // received the paragraph for this page so repair candidates can refer - // back to it by id. - const block = blocks[appendedStart + pageIndex]; - lines.push({ - pageIndex, - lineIndex, - text: line.text || "", - confidence: typeof line.confidence === "number" ? line.confidence : 0, - bbox: line.bbox || null, - blockId: block?.id || "", - }); + flat.push({ pageIndex, lineIndex, line }); }); }); + // 用文本包含把每行映射到承载它的追加块的 id（处理「多行→一块」与结构归并），而不是按页 + // 索引硬猜（旧 blocks[appendedStart + pageIndex] 在每页多块/标题分块时会错配）。 + const appendedBlocks = blocks.slice(appendedStart); + const blockIds = mapLinesToBlockIds(flat.map((f) => f.line), appendedBlocks); + const lines = flat.map((f, i) => ({ + pageIndex: f.pageIndex, + lineIndex: f.lineIndex, + text: f.line.text || "", + confidence: typeof f.line.confidence === "number" ? f.line.confidence : 0, + bbox: f.line.bbox || null, + blockId: blockIds[i] || "", + })); return { language: result?.language || "auto", pageCount: pages.length, diff --git a/public/core/ocr/scan-pdf-stage.js b/public/core/ocr/scan-pdf-stage.js index 9004695..5c40109 100644 --- a/public/core/ocr/scan-pdf-stage.js +++ b/public/core/ocr/scan-pdf-stage.js @@ -4,6 +4,7 @@ import { defaultOCRRegistry } from "./ocr-engine.js"; import { createOCREngineFailedWarning, createOCRUnavailableWarning, createOCRLowConfidenceWarning } from "./ocr-warnings.js"; import { defaultPdfPageRasterizer } from "./pdf-rasterizer.js"; import { mergeOCRResultsToFixedLayout } from "./ocr-to-fixed-layout.js"; +import { mapLinesToBlockIds } from "./ocr-structure.js"; import { fixedLayoutToSemantic } from "../models/mappers.js"; import { getFixedLayoutSummary } from "../models/fixed-layout.js"; @@ -135,6 +136,10 @@ export async function runScannedPdfOCRStage(model, ctx = {}) { sourceFormat: enhanced.sourceFormat || "pdf", }); enhanced.blocks.push(...(semanticFromLayout.blocks || [])); + // 给追加块预赋稳定 id（绝对索引），供低置信修复按 block.id 命中；document-audit 保留之。 + for (let i = appendedStart; i < enhanced.blocks.length; i += 1) { + if (!enhanced.blocks[i].id) enhanced.blocks[i].id = `ocr-block-${i}`; + } enhanced.metadata = withWarnings(enhanced.metadata, [ createWarning( "info", @@ -151,12 +156,11 @@ export async function runScannedPdfOCRStage(model, ctx = {}) { ]); } - // Re-resolve blockId for each ocr line after blocks were appended via mapper - let assignedFromBlockIndex = appendedStart; - for (const ocrLine of lines) { - const blockSlot = enhanced.blocks[assignedFromBlockIndex]; - if (blockSlot) ocrLine.blockId = blockSlot.id || ""; - } + // 用文本包含把每行映射到承载它的追加块的 id。不能按 lines 顺序硬配索引： + // mergeOCRResultsToFixedLayout 会按阅读顺序（bbox y→x）重排，lines 顺序 ≠ 块顺序。 + const appendedBlocks = enhanced.blocks.slice(appendedStart); + const blockIds = mapLinesToBlockIds(lines, appendedBlocks); + lines.forEach((ocrLine, i) => { ocrLine.blockId = blockIds[i] || ""; }); enhanced.metadata.ocr = { language: language || "auto", diff --git a/public/core/ocr/tesseract-engine.js b/public/core/ocr/tesseract-engine.js index 55a06ee..43894ec 100644 --- a/public/core/ocr/tesseract-engine.js +++ b/public/core/ocr/tesseract-engine.js @@ -16,6 +16,10 @@ export const TESSERACT_MANIFEST_ID = "ocr-text.tesseract.5.0.0"; const TESSDATA_KEY_PREFIX = "tesseract/"; const DEFAULT_LANGUAGES = ["chi_sim", "eng"]; +// 就绪状态放模块级可变变量，而非冻结对象的实例属性（冻结对象在严格模式下无法被 +// ensureProbe 赋值）。引擎对象本身仍可 Object.freeze 防外部篡改。 +let tessdataReady = false; + function vendorReady() { return Boolean(globalThis.__t2fTesseractVendorReady); } @@ -33,6 +37,8 @@ export const tesseractOCREngine = Object.freeze({ id: "tesseract-zh-en", taskCapabilities: ["ocr-text"], manifestId: TESSERACT_MANIFEST_ID, + // 轻量内置引擎：优先级高于 placeholder(0)，低于 PP-OCRv5 高级引擎(20)。 + priority: 10, // OCREngineRegistry expects a synchronous isAvailable. We expose a synchronous // signature backed by a cached probe; the probe is updated by ensureProbe() @@ -40,20 +46,19 @@ export const tesseractOCREngine = Object.freeze({ // false. isAvailable() { if (!vendorReady()) return false; - return Boolean(tesseractOCREngine._tessdataReady); + return Boolean(tessdataReady); }, - _tessdataReady: false, _storage: defaultOCRStorage, async ensureProbe() { if (!vendorReady()) { - this._tessdataReady = false; + tessdataReady = false; return false; } const language = await hasAnyTessdata(this._storage, DEFAULT_LANGUAGES); - this._tessdataReady = Boolean(language); - return this._tessdataReady; + tessdataReady = Boolean(language); + return tessdataReady; }, async recognize({ image, options } = {}) { diff --git a/public/core/repair-engine.js b/public/core/repair-engine.js index 4af2f54..612665b 100644 --- a/public/core/repair-engine.js +++ b/public/core/repair-engine.js @@ -3,36 +3,11 @@ import { validateRepairAction, summarizeAction } from "./repair-actions.js"; import { DEFAULT_HANDLERS } from "./repair-handlers.js"; import { DEFAULT_VALIDATORS } from "./repair-validators.js"; import { detectOCRLowConfidence } from "./ocr/ocr-validator.js"; +import { ROUND_TRIP_FORMATS, modelFingerprint } from "./verification/block-fingerprint.js"; import { createWarning, withWarnings } from "./warnings.js"; export const MIN_CONFIDENCE = 0.6; -const ROUND_TRIP_FORMATS = new Set(["md", "html", "json", "csv", "txt", "xml"]); - -function isPlainObject(value) { - return Boolean(value) && typeof value === "object" && !Array.isArray(value); -} - -function blockFingerprint(block) { - if (!isPlainObject(block)) return ""; - if (block.type === "heading") return `h${block.level}|${block.text || ""}`; - if (block.type === "paragraph" || block.type === "quote") return `${block.type}|${block.text || ""}`; - if (block.type === "code") return `code|${block.language || ""}|${block.code || ""}`; - if (block.type === "list") return `list|${block.ordered ? "ol" : "ul"}|${(block.items || []).join("")}`; - if (block.type === "table") { - return `table|${(block.headers || []).join("")}|${(block.rows || []).map((row) => (row || []).join("")).join("")}`; - } - if (block.type === "image" || block.type === "asset") { - return `${block.type}|${block.src || ""}|${block.alt || ""}|${block.assetId || ""}`; - } - if (block.type === "raw") return `raw|${block.format || ""}|${block.content || ""}`; - return block.type || ""; -} - -function modelFingerprint(model) { - return (model.blocks || []).map(blockFingerprint).join(""); -} - function summarizeQuality(model) { const report = model.metadata?.qualityReport || {}; return { diff --git a/public/core/verification/block-fingerprint.js b/public/core/verification/block-fingerprint.js new file mode 100644 index 0000000..bb9d514 --- /dev/null +++ b/public/core/verification/block-fingerprint.js @@ -0,0 +1,79 @@ +// 共享指纹模块：原 repair-engine.js 的 blockFingerprint / modelFingerprint 抽出， +// 行为字节级不变；额外暴露 getBlockKey / extractBlockFields / BLOCK_FIELDS_BY_TYPE +// 给 verification-stage 的字段级 diff 用。ROUND_TRIP_FORMATS 也搬到这里作为单一来源。 + +export const ROUND_TRIP_FORMATS = new Set(["md", "html", "json", "csv", "txt", "xml"]); + +export const BLOCK_FIELDS_BY_TYPE = { + heading: ["type", "level", "text"], + paragraph: ["type", "text"], + quote: ["type", "text"], + code: ["type", "language", "code"], + list: ["type", "ordered", "items"], + table: ["type", "headers", "rows"], + image: ["type", "src", "alt"], + asset: ["type", "assetId", "alt"], + raw: ["type", "format", "content"], +}; + +function isPlainObject(value) { + return Boolean(value) && typeof value === "object" && !Array.isArray(value); +} + +function stableHash(value) { + const text = String(value ?? ""); + let hash = 2166136261; + for (let index = 0; index < text.length; index += 1) { + hash ^= text.charCodeAt(index); + hash = Math.imul(hash, 16777619); + } + return (hash >>> 0).toString(36).padStart(8, "0").slice(0, 8); +} + +export function blockFingerprint(block) { + if (!isPlainObject(block)) return ""; + if (block.type === "heading") return `h${block.level}|${block.text || ""}`; + if (block.type === "paragraph" || block.type === "quote") return `${block.type}|${block.text || ""}`; + if (block.type === "code") return `code|${block.language || ""}|${block.code || ""}`; + if (block.type === "list") return `list|${block.ordered ? "ol" : "ul"}|${(block.items || []).join("")}`; + if (block.type === "table") { + return `table|${(block.headers || []).join("")}|${(block.rows || []).map((row) => (row || []).join("")).join("")}`; + } + if (block.type === "image" || block.type === "asset") { + return `${block.type}|${block.src || ""}|${block.alt || ""}|${block.assetId || ""}`; + } + if (block.type === "raw") return `raw|${block.format || ""}|${block.content || ""}`; + return block.type || ""; +} + +export function modelFingerprint(model) { + return (model?.blocks || []).map(blockFingerprint).join(""); +} + +export function extractBlockFields(block) { + if (!isPlainObject(block)) return { type: "" }; + const fields = BLOCK_FIELDS_BY_TYPE[block.type] || ["type"]; + const subset = {}; + for (const field of fields) { + const value = block[field]; + if (Array.isArray(value)) { + subset[field] = value.map((entry) => Array.isArray(entry) ? entry.map(String) : (entry === undefined || entry === null ? "" : String(entry))); + } else if (value === undefined || value === null) { + subset[field] = ""; + } else if (typeof value === "boolean" || typeof value === "number") { + subset[field] = value; + } else { + subset[field] = String(value); + } + } + return subset; +} + +export function getBlockKey(block, index) { + if (isPlainObject(block) && typeof block.id === "string" && block.id.length > 0) { + return block.id; + } + const fields = extractBlockFields(block); + const fingerprint = stableHash(JSON.stringify(fields)); + return `${fields.type || "unknown"}-${index}-${fingerprint}`; +} diff --git a/public/core/verification/ocr-readback.js b/public/core/verification/ocr-readback.js new file mode 100644 index 0000000..c2fac49 --- /dev/null +++ b/public/core/verification/ocr-readback.js @@ -0,0 +1,176 @@ +// OCR 回读：P9-C 三层检验第三层。把转换输出（PDF）栅格化后用 OCR 引擎读回文本， +// 与原始 SemanticDoc 文本做字符级多重集相似度，写入 qualityReport.ocrReadback。 +// engine / rasterizer 复用已注册的 ocr-text 资源；Node 默认不可用 → eligible:false。 + +import { createWarning } from "../warnings.js"; +import { defaultOCRRegistry } from "../ocr/ocr-engine.js"; +import { defaultPdfPageRasterizer } from "../ocr/pdf-rasterizer.js"; + +export const OCR_READBACK_DRIFT = "OCR_READBACK_DRIFT"; +export const OCR_READBACK_FAILED = "OCR_READBACK_FAILED"; +export const DEFAULT_OCR_READBACK_THRESHOLD = 0.7; + +// 当前唯一可栅格化的文本 writer。 +const OCR_READBACK_OUTPUT_FORMATS = new Set(["pdf"]); + +export function normalizeText(value) { + let text = String(value ?? ""); + if (typeof text.normalize === "function") text = text.normalize("NFKC"); + return text.toLowerCase().replace(/\s+/g, ""); +} + +function charMultiset(normalized) { + const counts = new Map(); + for (const ch of normalized) { + counts.set(ch, (counts.get(ch) || 0) + 1); + } + return counts; +} + +// 字符级多重集 recall / precision / f1，跨中英文与 OCR 噪声稳健。 +export function compareText(original, recognized) { + const normOriginal = normalizeText(original); + const normRecognized = normalizeText(recognized); + const originalCounts = charMultiset(normOriginal); + const recognizedCounts = charMultiset(normRecognized); + + let intersection = 0; + for (const [ch, count] of originalCounts) { + const other = recognizedCounts.get(ch) || 0; + intersection += Math.min(count, other); + } + + const originalLength = normOriginal.length; + const recognizedLength = normRecognized.length; + const recall = originalLength > 0 ? intersection / originalLength : (recognizedLength === 0 ? 1 : 0); + const precision = recognizedLength > 0 ? intersection / recognizedLength : (originalLength === 0 ? 1 : 0); + const f1 = (precision + recall) > 0 ? (2 * precision * recall) / (precision + recall) : 0; + + return { + recall, + precision, + f1, + originalLength, + recognizedLength, + intersection, + }; +} + +function textOfBlock(block) { + if (!block || typeof block !== "object") return ""; + if (typeof block.text === "string") return block.text; + if (Array.isArray(block.items)) return block.items.join("\n"); + if (Array.isArray(block.rows)) { + const head = Array.isArray(block.headers) ? block.headers.join(" ") : ""; + return [head, ...block.rows.map((row) => (Array.isArray(row) ? row.join(" ") : ""))].join("\n"); + } + if (typeof block.code === "string") return block.code; + if (typeof block.content === "string") return block.content; + if (typeof block.alt === "string") return block.alt; + return ""; +} + +export function extractModelText(model) { + const blocks = Array.isArray(model?.blocks) ? model.blocks : []; + return blocks.map(textOfBlock).filter((text) => text && text.trim().length > 0).join("\n"); +} + +function recognizedTextOf(ocrResult) { + if (typeof ocrResult?.fullText === "string" && ocrResult.fullText.trim().length > 0) { + return ocrResult.fullText; + } + const pages = Array.isArray(ocrResult?.pages) ? ocrResult.pages : []; + return pages + .flatMap((page) => (Array.isArray(page.lines) ? page.lines.map((line) => line.text) : [])) + .filter(Boolean) + .join("\n"); +} + +function nowMs() { + if (typeof performance !== "undefined" && typeof performance.now === "function") { + return performance.now(); + } + return Date.now(); +} + +export async function runOcrReadbackLayer({ + model, + output, + ctx, + engine = null, + rasterizer = defaultPdfPageRasterizer, + registry = defaultOCRRegistry, +} = {}) { + const start = nowMs(); + const skip = (reason, warnings = []) => ({ eligible: false, reason, ocrReadback: null, warnings, runtimeMs: nowMs() - start }); + + if (!OCR_READBACK_OUTPUT_FORMATS.has(ctx?.to)) { + return skip("output-not-rasterizable-for-ocr"); + } + const originalText = extractModelText(model); + if (originalText.trim().length === 0) { + return skip("no-source-text"); + } + + const resolvedEngine = engine || registry.pickForTask("ocr-text"); + let available = false; + try { + available = Boolean(resolvedEngine) && resolvedEngine.isAvailable() === true; + } catch (error) { + available = false; + } + if (!available) { + return skip("ocr-engine-unavailable"); + } + + const threshold = typeof ctx?.options?.verification?.ocrReadbackThreshold === "number" + ? ctx.options.verification.ocrReadbackThreshold + : DEFAULT_OCR_READBACK_THRESHOLD; + const language = ctx?.options?.ocr?.language || "auto"; + + let recognized; + try { + const raster = await rasterizer.rasterize({ content: output?.data, pageIndex: 0 }); + recognized = await resolvedEngine.recognize({ image: raster.dataUrl, options: { language } }); + } catch (error) { + const cause = error?.code || error?.message || "unknown"; + if (cause === "OCR_RASTERIZER_UNAVAILABLE") { + return skip("rasterizer-unavailable"); + } + return skip(`readback-failed:${cause}`, [ + createWarning("info", OCR_READBACK_FAILED, `OCR 回读失败：${cause}.`, { from: ctx?.from, to: ctx?.to, cause }), + ]); + } + + const recognizedText = recognizedTextOf(recognized); + const similarity = compareText(originalText, recognizedText); + const passed = similarity.f1 >= threshold; + const ocrReadback = { + recall: similarity.recall, + precision: similarity.precision, + f1: similarity.f1, + threshold, + passed, + engineId: resolvedEngine.id, + originalLength: similarity.originalLength, + recognizedLength: similarity.recognizedLength, + averageConfidence: typeof recognized?.averageConfidence === "number" ? recognized.averageConfidence : null, + pageIndex: 0, + }; + const warnings = passed + ? [] + : [createWarning( + "info", + OCR_READBACK_DRIFT, + `OCR 回读 ${ctx?.from} → ${ctx?.to} 低于阈值（f1 ${similarity.f1.toFixed(3)} < ${threshold}）。`, + { from: ctx?.from, to: ctx?.to, f1: similarity.f1, recall: similarity.recall, precision: similarity.precision, threshold }, + )]; + + return { + eligible: true, + reason: "completed", + ocrReadback, + warnings, + runtimeMs: nowMs() - start, + }; +} diff --git a/public/core/verification/page-image-source-browser.js b/public/core/verification/page-image-source-browser.js new file mode 100644 index 0000000..de98dd0 --- /dev/null +++ b/public/core/verification/page-image-source-browser.js @@ -0,0 +1,96 @@ +// 浏览器/Tauri 端像素源实现：PDF 经 vendor pdfjs rasterize 得 PNG dataUrl，PNG 直接用 +// 其 dataUrl/bytes，统一通过 Image → canvas → getImageData 取 RGBA 像素。仅在 DOM runtime +// 可用；Node 测试用注入 stub。本文件不联网，所有资源走同源 vendor / blob / dataUrl。 + +import { ConversionError } from "../conversion-error.js"; +import { createBrowserPdfPageRasterizer } from "../ocr/pdf-rasterizer-browser.js"; + +function ensureBrowserRuntime() { + if (typeof globalThis === "undefined" || typeof globalThis.document?.createElement !== "function") { + throw new ConversionError("Browser page image source needs a DOM runtime.", { + category: "convert", + code: "VERIFICATION_IMAGE_SOURCE_UNAVAILABLE", + details: { reason: "missing-document" }, + }); + } +} + +function toPngDataUrl(content) { + if (typeof content === "string") { + if (content.startsWith("data:")) return content; + // 裸 base64 / 二进制字符串：包成 png dataUrl 让浏览器解码。 + return `data:image/png;base64,${globalThis.btoa(content)}`; + } + if (content instanceof Uint8Array || content instanceof ArrayBuffer) { + const bytes = content instanceof ArrayBuffer ? new Uint8Array(content) : content; + let binary = ""; + for (let i = 0; i < bytes.length; i += 1) binary += String.fromCharCode(bytes[i]); + return `data:image/png;base64,${globalThis.btoa(binary)}`; + } + throw new ConversionError("Unsupported PNG content type for browser image source.", { + category: "validate", + code: "VERIFICATION_IMAGE_SOURCE_FAILED", + details: { reason: "unsupported-content-type" }, + }); +} + +function loadImage(dataUrl) { + return new Promise((resolve, reject) => { + const image = new globalThis.Image(); + image.onload = () => resolve(image); + image.onerror = () => reject(new ConversionError("Image 解码失败。", { + category: "convert", + code: "VERIFICATION_IMAGE_SOURCE_FAILED", + details: { reason: "image-decode-failed" }, + })); + image.src = dataUrl; + }); +} + +function drawToPixels(image, width, height) { + const canvas = globalThis.document.createElement("canvas"); + canvas.width = width; + canvas.height = height; + const ctx = canvas.getContext("2d"); + if (!ctx) { + throw new ConversionError("Canvas 2d context 不可用。", { + category: "convert", + code: "VERIFICATION_IMAGE_SOURCE_FAILED", + details: { reason: "canvas-context-missing" }, + }); + } + ctx.drawImage(image, 0, 0, width, height); + const imageData = ctx.getImageData(0, 0, width, height); + return { pixels: imageData.data, width, height }; +} + +export function createBrowserPageImageSource({ dpi = 144 } = {}) { + let pdfRasterizer = null; + function getPdfRasterizer() { + if (!pdfRasterizer) pdfRasterizer = createBrowserPdfPageRasterizer(); + return pdfRasterizer; + } + + return Object.freeze({ + async getPageImage({ format, content, pageIndex = 0, dpi: dpiOverride } = {}) { + ensureBrowserRuntime(); + const normalized = String(format || "").toLowerCase(); + if (normalized === "pdf") { + const raster = await getPdfRasterizer().rasterize({ content, pageIndex, dpi: dpiOverride || dpi }); + const image = await loadImage(raster.dataUrl); + return drawToPixels(image, raster.width, raster.height); + } + if (normalized === "png") { + const image = await loadImage(toPngDataUrl(content)); + const width = image.naturalWidth || image.width; + const height = image.naturalHeight || image.height; + return drawToPixels(image, width, height); + } + throw new ConversionError(`像素源不支持格式：${normalized}`, { + category: "convert", + code: "VERIFICATION_IMAGE_SOURCE_FAILED", + details: { reason: "format-not-rasterizable", format: normalized }, + }); + }, + }); +} diff --git a/public/core/verification/page-image-source.js b/public/core/verification/page-image-source.js new file mode 100644 index 0000000..3356c3f --- /dev/null +++ b/public/core/verification/page-image-source.js @@ -0,0 +1,75 @@ +// 像素源抽象：SSIM 视觉回环层需要把某个格式的某一页栅格化为 RGBA 像素缓冲。 +// 与 OCR 的 pdf-rasterizer 分离关注点（OCR 要 PNG dataUrl，SSIM 要原始像素）。 +// Node 默认不可用（抛错）；浏览器/Tauri 首次调用 dynamic import canvas 实现； +// 测试通过 setPageImageSource 注入 stub。 + +import { ConversionError } from "../conversion-error.js"; + +export const VERIFICATION_IMAGE_SOURCE_UNAVAILABLE = "VERIFICATION_IMAGE_SOURCE_UNAVAILABLE"; +export const VERIFICATION_IMAGE_SOURCE_FAILED = "VERIFICATION_IMAGE_SOURCE_FAILED"; + +// 当前视觉回环支持的可栅格化格式（有源图 / 输出可渲染）。 +export const RASTERIZABLE_FORMATS = new Set(["pdf", "png"]); + +function isBrowserRuntime() { + return typeof globalThis !== "undefined" + && typeof globalThis.document?.createElement === "function"; +} + +let _injectedSource = null; +let _autoBrowserImpl = null; +let _autoBrowserLoadFailed = false; + +async function tryLoadBrowserSource() { + if (_autoBrowserImpl) return _autoBrowserImpl; + if (_autoBrowserLoadFailed) return null; + if (!isBrowserRuntime()) { + _autoBrowserLoadFailed = true; + return null; + } + try { + const mod = await import("./page-image-source-browser.js"); + _autoBrowserImpl = mod.createBrowserPageImageSource(); + return _autoBrowserImpl; + } catch (error) { + _autoBrowserLoadFailed = true; + return null; + } +} + +function throwUnavailable(operation) { + throw new ConversionError( + `验证阶段像素源在当前运行时不可用（${operation}）。请用 setPageImageSource 注入实现，或在浏览器/Tauri 端启用 vendor pdfjs + canvas。`, + { + category: "convert", + code: VERIFICATION_IMAGE_SOURCE_UNAVAILABLE, + details: { reason: "no-runtime-image-source", operation }, + }, + ); +} + +export const defaultPageImageSource = Object.freeze({ + async getPageImage(args) { + if (_injectedSource) return _injectedSource.getPageImage(args); + const browserImpl = await tryLoadBrowserSource(); + if (browserImpl) return browserImpl.getPageImage(args); + throwUnavailable("getPageImage"); + }, +}); + +export function setPageImageSource(impl) { + if (!impl || typeof impl.getPageImage !== "function") { + throw new ConversionError("setPageImageSource requires a { getPageImage } function.", { + category: "validate", + code: "VERIFICATION_IMAGE_SOURCE_INVALID", + details: { reason: "missing-methods" }, + }); + } + _injectedSource = impl; +} + +export function resetPageImageSource() { + _injectedSource = null; + _autoBrowserImpl = null; + _autoBrowserLoadFailed = false; +} diff --git a/public/core/verification/rule-diff.js b/public/core/verification/rule-diff.js new file mode 100644 index 0000000..56dae2e --- /dev/null +++ b/public/core/verification/rule-diff.js @@ -0,0 +1,224 @@ +// 规则 diff：在两个 SemanticDoc model（原始 + writer→reader 回读）之间产生 +// 字段级差异，输出 qualityReport.ruleDiff 标准结构。属 P9-C 三层检验的第一层。 + +import { getBlockKey, extractBlockFields, BLOCK_FIELDS_BY_TYPE } from "./block-fingerprint.js"; + +export const MAJOR_WEIGHT = 0.4; +export const MINOR_WEIGHT = 0.05; +export const STRUCTURAL_PENALTY = 0.5; + +const MAJOR_FIELDS = new Set([ + "level", + "ordered", + "headers", + "rows", + "code", + "language", + "src", + "assetId", + "format", +]); + +function clamp(value, min, max) { + if (Number.isNaN(value)) return min; + return Math.min(Math.max(value, min), max); +} + +function firstWords(text, count = 8) { + if (typeof text !== "string") return ""; + return text.trim().split(/\s+/).slice(0, count).join(" "); +} + +function blockSnippet(block) { + if (!block) return ""; + if (typeof block.text === "string") return firstWords(block.text, 12); + if (typeof block.code === "string") return firstWords(block.code, 12); + if (Array.isArray(block.items) && block.items.length > 0) return firstWords(block.items[0], 12); + if (typeof block.alt === "string") return firstWords(block.alt, 12); + if (typeof block.assetId === "string") return block.assetId; + if (typeof block.content === "string") return firstWords(block.content, 12); + return block.type || ""; +} + +function isWhitespaceOrPunctOnlyDelta(beforeStr, afterStr) { + if (typeof beforeStr !== "string" || typeof afterStr !== "string") return false; + const normalize = (value) => value.replace(/[\s\p{P}]+/gu, "").toLowerCase(); + return normalize(beforeStr) === normalize(afterStr); +} + +function arraysEqual(a, b) { + if (a === b) return true; + if (!Array.isArray(a) || !Array.isArray(b)) return false; + if (a.length !== b.length) return false; + for (let index = 0; index < a.length; index += 1) { + const left = a[index]; + const right = b[index]; + if (Array.isArray(left) || Array.isArray(right)) { + if (!arraysEqual(left, right)) return false; + } else if (left !== right) { + return false; + } + } + return true; +} + +function classifyFieldSeverity(field, beforeValue, afterValue) { + if (MAJOR_FIELDS.has(field)) { + if (field === "headers" || field === "rows") { + if (Array.isArray(beforeValue) && Array.isArray(afterValue) && beforeValue.length !== afterValue.length) { + return "major"; + } + } + return "major"; + } + if (field === "text") { + if (isWhitespaceOrPunctOnlyDelta(beforeValue, afterValue)) return "minor"; + return "major"; + } + if (typeof beforeValue === "string" && typeof afterValue === "string") { + if (isWhitespaceOrPunctOnlyDelta(beforeValue, afterValue)) return "minor"; + } + return "minor"; +} + +function diffBlockPair(before, after) { + const fields = BLOCK_FIELDS_BY_TYPE[before?.type] || BLOCK_FIELDS_BY_TYPE[after?.type] || ["type"]; + const fieldsDiffered = []; + for (const field of fields) { + const beforeValue = extractBlockFields(before)[field]; + const afterValue = extractBlockFields(after)[field]; + let equal; + if (Array.isArray(beforeValue) || Array.isArray(afterValue)) { + equal = arraysEqual(beforeValue, afterValue); + } else { + equal = beforeValue === afterValue; + } + if (!equal) { + fieldsDiffered.push({ + field, + severity: classifyFieldSeverity(field, beforeValue, afterValue), + before: beforeValue, + after: afterValue, + }); + } + } + return fieldsDiffered; +} + +function buildAlignmentKey(block, index) { + const fields = extractBlockFields(block); + const head = firstWords(typeof block?.text === "string" ? block.text : (Array.isArray(block?.items) ? block.items[0] || "" : "")); + return `${fields.type || "?"}|${head}|${index}`; +} + +export function diffSemanticDocs(original, readBack) { + const originalBlocks = Array.isArray(original?.blocks) ? original.blocks : []; + const readBackBlocks = Array.isArray(readBack?.blocks) ? readBack.blocks : []; + + const originalKeys = originalBlocks.map((block, index) => getBlockKey(block, index)); + const readBackKeys = readBackBlocks.map((block, index) => getBlockKey(block, index)); + + const matchedOriginalIdx = new Set(); + const matchedReadBackIdx = new Set(); + const changedBlocks = []; + + for (let i = 0; i < originalBlocks.length; i += 1) { + const j = readBackKeys.indexOf(originalKeys[i]); + if (j >= 0 && !matchedReadBackIdx.has(j)) { + matchedOriginalIdx.add(i); + matchedReadBackIdx.add(j); + const fieldsDiffered = diffBlockPair(originalBlocks[i], readBackBlocks[j]); + if (fieldsDiffered.length > 0) { + changedBlocks.push({ + id: originalKeys[i], + type: originalBlocks[i]?.type || "", + fieldsDiffered, + severity: fieldsDiffered.some((entry) => entry.severity === "major") ? "major" : "minor", + }); + } + } + } + + // LCS-lite 二次对齐：按 (type, firstWords) 启发匹配剩余块 + for (let i = 0; i < originalBlocks.length; i += 1) { + if (matchedOriginalIdx.has(i)) continue; + const heuristic = buildAlignmentKey(originalBlocks[i], i).split("|").slice(0, 2).join("|"); + for (let j = 0; j < readBackBlocks.length; j += 1) { + if (matchedReadBackIdx.has(j)) continue; + const candidate = buildAlignmentKey(readBackBlocks[j], j).split("|").slice(0, 2).join("|"); + if (candidate === heuristic) { + matchedOriginalIdx.add(i); + matchedReadBackIdx.add(j); + const fieldsDiffered = diffBlockPair(originalBlocks[i], readBackBlocks[j]); + if (fieldsDiffered.length > 0) { + changedBlocks.push({ + id: originalKeys[i], + type: originalBlocks[i]?.type || "", + fieldsDiffered, + severity: fieldsDiffered.some((entry) => entry.severity === "major") ? "major" : "minor", + }); + } + break; + } + } + } + + const removedBlocks = []; + for (let i = 0; i < originalBlocks.length; i += 1) { + if (matchedOriginalIdx.has(i)) continue; + removedBlocks.push({ + id: originalKeys[i], + type: originalBlocks[i]?.type || "", + snippet: blockSnippet(originalBlocks[i]), + }); + } + + const addedBlocks = []; + for (let j = 0; j < readBackBlocks.length; j += 1) { + if (matchedReadBackIdx.has(j)) continue; + addedBlocks.push({ + id: readBackKeys[j], + type: readBackBlocks[j]?.type || "", + snippet: blockSnippet(readBackBlocks[j]), + }); + } + + const majorFieldCount = changedBlocks.reduce( + (sum, entry) => sum + entry.fieldsDiffered.filter((field) => field.severity === "major").length, + 0, + ); + const minorFieldCount = changedBlocks.reduce( + (sum, entry) => sum + entry.fieldsDiffered.filter((field) => field.severity === "minor").length, + 0, + ); + const structuralDelta = addedBlocks.length + removedBlocks.length; + const denominator = Math.max(1, originalBlocks.length); + const penalty = MAJOR_WEIGHT * majorFieldCount + MINOR_WEIGHT * minorFieldCount + STRUCTURAL_PENALTY * structuralDelta; + const overallScore = clamp(1 - penalty / denominator, 0, 1); + + const identical = changedBlocks.length === 0 && addedBlocks.length === 0 && removedBlocks.length === 0; + let fidelity; + if (identical) { + fidelity = "exact"; + } else if (structuralDelta / denominator > 0.3 || readBackBlocks.length === 0) { + fidelity = "broken"; + } else if (majorFieldCount > 0) { + fidelity = "major-drift"; + } else { + fidelity = "minor-drift"; + } + + return { + identical, + blockCounts: { + original: originalBlocks.length, + readBack: readBackBlocks.length, + delta: readBackBlocks.length - originalBlocks.length, + }, + changedBlocks, + addedBlocks, + removedBlocks, + fidelity, + overallScore, + }; +} diff --git a/public/core/verification/ssim.js b/public/core/verification/ssim.js new file mode 100644 index 0000000..29d45a3 --- /dev/null +++ b/public/core/verification/ssim.js @@ -0,0 +1,127 @@ +// SSIM 视觉对比核心：纯函数，零依赖，操作灰度像素缓冲。P9-C 三层检验的第二层 +// （视觉回环）用它对比输入页与输出页的结构相似度。Node / 浏览器均可运行。 + +export const SSIM_C1 = (0.01 * 255) ** 2; // 6.5025 +export const SSIM_C2 = (0.03 * 255) ** 2; // 58.5225 +export const DEFAULT_WINDOW_SIZE = 8; +export const DEFAULT_TARGET_WIDTH = 256; + +function toClampedArray(value) { + if (value instanceof Uint8ClampedArray) return value; + if (value instanceof Uint8Array || Array.isArray(value)) return Uint8ClampedArray.from(value); + throw new TypeError("ssim: pixel buffer must be Uint8ClampedArray / Uint8Array / number[]."); +} + +// RGBA Uint8 buffer (length w*h*4) → 灰度 Uint8ClampedArray (length w*h)。 +export function rgbaToGrayscale(rgba) { + const buffer = toClampedArray(rgba); + const pixelCount = Math.floor(buffer.length / 4); + const gray = new Uint8ClampedArray(pixelCount); + for (let i = 0; i < pixelCount; i += 1) { + const o = i * 4; + gray[i] = Math.round(0.299 * buffer[o] + 0.587 * buffer[o + 1] + 0.114 * buffer[o + 2]); + } + return gray; +} + +// box 平均重采样：把 srcW×srcH 灰度图缩放到 dstW×dstH。 +export function resampleGrayscale(gray, srcW, srcH, dstW, dstH) { + const source = toClampedArray(gray); + if (srcW <= 0 || srcH <= 0 || dstW <= 0 || dstH <= 0) { + throw new RangeError("ssim: resample dimensions must be positive."); + } + if (srcW === dstW && srcH === dstH) return source; + const out = new Uint8ClampedArray(dstW * dstH); + for (let dy = 0; dy < dstH; dy += 1) { + const sy0 = Math.floor((dy * srcH) / dstH); + const sy1 = Math.max(sy0 + 1, Math.floor(((dy + 1) * srcH) / dstH)); + for (let dx = 0; dx < dstW; dx += 1) { + const sx0 = Math.floor((dx * srcW) / dstW); + const sx1 = Math.max(sx0 + 1, Math.floor(((dx + 1) * srcW) / dstW)); + let sum = 0; + let count = 0; + for (let sy = sy0; sy < sy1 && sy < srcH; sy += 1) { + for (let sx = sx0; sx < sx1 && sx < srcW; sx += 1) { + sum += source[sy * srcW + sx]; + count += 1; + } + } + out[dy * dstW + dx] = count > 0 ? Math.round(sum / count) : 0; + } + } + return out; +} + +// 非重叠窗口均值 SSIM。grayA / grayB 必须同尺寸 width×height。 +export function computeSSIM(grayA, grayB, width, height, options = {}) { + const a = toClampedArray(grayA); + const b = toClampedArray(grayB); + if (a.length !== width * height || b.length !== width * height) { + throw new RangeError("ssim: grayscale buffers must match width*height."); + } + const windowSize = Math.max(2, Math.floor(options.windowSize || DEFAULT_WINDOW_SIZE)); + const c1 = typeof options.c1 === "number" ? options.c1 : SSIM_C1; + const c2 = typeof options.c2 === "number" ? options.c2 : SSIM_C2; + + let ssimSum = 0; + let windowCount = 0; + + for (let wy = 0; wy + windowSize <= height; wy += windowSize) { + for (let wx = 0; wx + windowSize <= width; wx += windowSize) { + let sumA = 0; + let sumB = 0; + let sumAA = 0; + let sumBB = 0; + let sumAB = 0; + const n = windowSize * windowSize; + for (let y = 0; y < windowSize; y += 1) { + const row = (wy + y) * width + wx; + for (let x = 0; x < windowSize; x += 1) { + const va = a[row + x]; + const vb = b[row + x]; + sumA += va; + sumB += vb; + sumAA += va * va; + sumBB += vb * vb; + sumAB += va * vb; + } + } + const meanA = sumA / n; + const meanB = sumB / n; + const varA = sumAA / n - meanA * meanA; + const varB = sumBB / n - meanB * meanB; + const covAB = sumAB / n - meanA * meanB; + const numerator = (2 * meanA * meanB + c1) * (2 * covAB + c2); + const denominator = (meanA * meanA + meanB * meanB + c1) * (varA + varB + c2); + ssimSum += denominator === 0 ? 1 : numerator / denominator; + windowCount += 1; + } + } + + const score = windowCount > 0 ? ssimSum / windowCount : 1; + return { score, windowCount, windowSize, width, height }; +} + +// 端到端：两张 { pixels: RGBA, width, height } → 归一到公共网格后算 SSIM。 +export function compareImages(imageA, imageB, options = {}) { + if (!imageA || !imageB || !imageA.pixels || !imageB.pixels) { + throw new TypeError("ssim: compareImages requires { pixels, width, height } for both images."); + } + const targetWidth = Math.max(8, Math.floor(options.targetWidth || DEFAULT_TARGET_WIDTH)); + const aspect = imageA.height > 0 && imageA.width > 0 ? imageA.height / imageA.width : 1; + const dstW = Math.min(targetWidth, Math.max(imageA.width, imageB.width)); + const dstH = Math.max(8, Math.round(dstW * aspect)); + + const grayA = resampleGrayscale(rgbaToGrayscale(imageA.pixels), imageA.width, imageA.height, dstW, dstH); + const grayB = resampleGrayscale(rgbaToGrayscale(imageB.pixels), imageB.width, imageB.height, dstW, dstH); + + const result = computeSSIM(grayA, grayB, dstW, dstH, options); + return { + score: result.score, + width: dstW, + height: dstH, + windowCount: result.windowCount, + windowSize: result.windowSize, + dimensionsMatched: imageA.width === imageB.width && imageA.height === imageB.height, + }; +} diff --git a/public/core/verification/verification-stage.js b/public/core/verification/verification-stage.js new file mode 100644 index 0000000..db0f487 --- /dev/null +++ b/public/core/verification/verification-stage.js @@ -0,0 +1,294 @@ +// 验证阶段编排：在 Repair Engine cycle 之后跑，组合 P9-C 三层检验结果到统一 envelope。 +// 本批仅实现第一层（rule-diff）；P9-C.2 SSIM、P9-C.3 OCR 回读以后按相同 envelope 接入。 + +import { createWarning } from "../warnings.js"; +import { ROUND_TRIP_FORMATS } from "./block-fingerprint.js"; +import { diffSemanticDocs } from "./rule-diff.js"; +import { compareImages } from "./ssim.js"; +import { + defaultPageImageSource, + RASTERIZABLE_FORMATS, +} from "./page-image-source.js"; + +export const RULE_DIFF_DRIFT = "RULE_DIFF_DRIFT"; +export const RULE_DIFF_READBACK_FAILED = "RULE_DIFF_READBACK_FAILED"; +export const SSIM_VISUAL_DRIFT = "SSIM_VISUAL_DRIFT"; +export const SSIM_SOURCE_UNAVAILABLE = "SSIM_SOURCE_UNAVAILABLE"; + +export const DEFAULT_SSIM_THRESHOLD = 0.85; + +const CROSS_FORMAT_LOOPBACK_PAIRS = new Set([ + "md->html", + "html->md", +]); + +function nowMs() { + if (typeof performance !== "undefined" && typeof performance.now === "function") { + return performance.now(); + } + return Date.now(); +} + +function skippedEntry(layer, reason) { + return { layer, reason }; +} + +function buildEmptyEnvelope(reason, runtimeMs) { + return { + eligible: false, + reason, + layers: [], + skipped: [skippedEntry("rule-diff", reason)], + ruleDiff: null, + warnings: [], + runtimeMs, + }; +} + +function shouldRunRuleDiff(ctx, output) { + if (!ROUND_TRIP_FORMATS.has(ctx?.from) || !ROUND_TRIP_FORMATS.has(ctx?.to)) { + return { ok: false, reason: "writer-not-text-canonical" }; + } + if (typeof output?.data !== "string") { + return { ok: false, reason: "output-not-string" }; + } + return { ok: true }; +} + +function safeRead(ctx, payload, fromFormat) { + try { + const readBack = ctx.read({ + content: payload, + from: fromFormat, + title: ctx?.title || "verification-readback", + }); + return { ok: true, model: readBack }; + } catch (error) { + return { + ok: false, + error: error?.code || error?.message || "unknown", + }; + } +} + +function safeCrossLoopback(ctx, payload) { + // payload 在 ctx.to 格式中：先反向 prepareConversionModel(payload, from = ctx.to, to = ctx.from)， + // 用 ctx.write 把它写回原格式，再 read 一次以拿到与 original 同源格式的 SemanticDoc。 + if (typeof ctx?.prepareConversionModel !== "function" || typeof ctx?.write !== "function") { + return { ok: false, error: "ctx-missing-pipeline" }; + } + try { + const reverseModel = ctx.prepareConversionModel({ + content: payload, + from: ctx.to, + to: ctx.from, + title: ctx?.title || "verification-readback", + fileName: "", + options: { repair: false }, + }); + const reverseOutput = ctx.write({ + model: reverseModel, + to: ctx.from, + title: ctx?.title || "verification-readback", + options: {}, + }); + if (typeof reverseOutput?.data !== "string") { + return { ok: false, error: "reverse-output-not-string" }; + } + const readBack = ctx.read({ + content: reverseOutput.data, + from: ctx.from, + title: ctx?.title || "verification-readback", + }); + return { ok: true, model: readBack }; + } catch (error) { + return { ok: false, error: error?.code || error?.message || "unknown" }; + } +} + +export function runVerificationStage({ model, output, ctx } = {}) { + const start = nowMs(); + const gating = shouldRunRuleDiff(ctx, output); + if (!gating.ok) { + return buildEmptyEnvelope(gating.reason, nowMs() - start); + } + if (typeof ctx?.read !== "function") { + return buildEmptyEnvelope("ctx-missing-read", nowMs() - start); + } + + let readBackResult; + const pairKey = `${ctx.from}->${ctx.to}`; + + if (ctx.from === ctx.to) { + readBackResult = safeRead(ctx, output.data, ctx.to); + } else if (CROSS_FORMAT_LOOPBACK_PAIRS.has(pairKey)) { + readBackResult = safeCrossLoopback(ctx, output.data); + } else { + return buildEmptyEnvelope("cross-format-loopback-not-enabled", nowMs() - start); + } + + if (!readBackResult.ok) { + const warning = createWarning( + "info", + RULE_DIFF_READBACK_FAILED, + `Rule-diff readback failed for ${pairKey}: ${readBackResult.error}.`, + { from: ctx.from, to: ctx.to, cause: readBackResult.error }, + ); + return { + eligible: true, + reason: "readback-failed", + layers: [], + skipped: [skippedEntry("rule-diff", `readback-failed:${readBackResult.error}`)], + ruleDiff: null, + warnings: [warning], + runtimeMs: nowMs() - start, + }; + } + + const ruleDiff = diffSemanticDocs(model, readBackResult.model); + const warnings = []; + if (ruleDiff.fidelity !== "exact") { + warnings.push(createWarning( + "info", + RULE_DIFF_DRIFT, + `Rule-diff detected ${ruleDiff.fidelity} for ${pairKey} (score ${ruleDiff.overallScore.toFixed(3)}).`, + { + from: ctx.from, + to: ctx.to, + fidelity: ruleDiff.fidelity, + score: ruleDiff.overallScore, + addedCount: ruleDiff.addedBlocks.length, + removedCount: ruleDiff.removedBlocks.length, + changedCount: ruleDiff.changedBlocks.length, + }, + )); + } + + return { + eligible: true, + reason: "completed", + layers: ["rule-diff"], + skipped: [], + ruleDiff, + warnings, + runtimeMs: nowMs() - start, + }; +} + +// ---- SSIM 视觉回环层（P9-C.2，异步） ---- + +function ssimGate(ctx) { + if (!RASTERIZABLE_FORMATS.has(ctx?.from)) { + return { ok: false, reason: ctx?.from ? "source-not-rasterizable" : "no-source-format" }; + } + if (!RASTERIZABLE_FORMATS.has(ctx?.to)) { + return { ok: false, reason: "output-not-rasterizable" }; + } + return { ok: true }; +} + +export async function runSsimLayer({ ctx, output, imageSource = defaultPageImageSource } = {}) { + const start = nowMs(); + const gate = ssimGate(ctx); + if (!gate.ok) { + return { + eligible: false, + reason: gate.reason, + ssim: null, + warnings: [], + runtimeMs: nowMs() - start, + }; + } + + const threshold = typeof ctx?.options?.verification?.ssimThreshold === "number" + ? ctx.options.verification.ssimThreshold + : DEFAULT_SSIM_THRESHOLD; + + let sourceImage; + let outputImage; + try { + sourceImage = await imageSource.getPageImage({ format: ctx.from, content: ctx.content, pageIndex: 0 }); + outputImage = await imageSource.getPageImage({ format: ctx.to, content: output?.data, pageIndex: 0 }); + } catch (error) { + const cause = error?.code || error?.message || "unknown"; + const reason = cause === "VERIFICATION_IMAGE_SOURCE_UNAVAILABLE" ? "image-source-unavailable" : `image-source-failed:${cause}`; + return { + eligible: false, + reason, + ssim: null, + warnings: cause === "VERIFICATION_IMAGE_SOURCE_UNAVAILABLE" + ? [] + : [createWarning("info", SSIM_SOURCE_UNAVAILABLE, `SSIM 视觉对比跳过：${reason}.`, { from: ctx.from, to: ctx.to, cause })], + runtimeMs: nowMs() - start, + }; + } + + const comparison = compareImages(sourceImage, outputImage, ctx?.options?.verification || {}); + const passed = comparison.score >= threshold; + const ssim = { + score: comparison.score, + threshold, + passed, + width: comparison.width, + height: comparison.height, + pageIndex: 0, + sourceFormat: ctx.from, + outputFormat: ctx.to, + dimensionsMatched: comparison.dimensionsMatched, + }; + const warnings = passed + ? [] + : [createWarning( + "info", + SSIM_VISUAL_DRIFT, + `SSIM 视觉对比 ${ctx.from} → ${ctx.to} 低于阈值（score ${comparison.score.toFixed(3)} < ${threshold}）。`, + { from: ctx.from, to: ctx.to, score: comparison.score, threshold }, + )]; + + return { + eligible: true, + reason: "completed", + ssim, + warnings, + runtimeMs: nowMs() - start, + }; +} + +// 异步编排：同步 rule-diff 基底 + 异步 SSIM 视觉回环 + 异步 OCR 回读，合并为统一 envelope。 +export async function runVerificationStageAsync({ model, output, ctx, imageSource, ocrEngine, ocrRasterizer } = {}) { + const base = runVerificationStage({ model, output, ctx }); + const ssimLayer = await runSsimLayer({ ctx, output, imageSource }); + + let ocrLayer = { eligible: false, reason: "ocr-readback-not-loaded", ocrReadback: null, warnings: [], runtimeMs: 0 }; + try { + const mod = await import("./ocr-readback.js"); + ocrLayer = await mod.runOcrReadbackLayer({ model, output, ctx, engine: ocrEngine, rasterizer: ocrRasterizer }); + } catch (error) { + ocrLayer = { eligible: false, reason: `ocr-readback-load-failed:${error?.code || error?.message || "unknown"}`, ocrReadback: null, warnings: [], runtimeMs: 0 }; + } + + const layers = [...base.layers]; + const skipped = [...base.skipped]; + if (ssimLayer.eligible) { + layers.push("ssim"); + } else { + skipped.push({ layer: "ssim", reason: ssimLayer.reason }); + } + if (ocrLayer.eligible) { + layers.push("ocr-readback"); + } else { + skipped.push({ layer: "ocr-readback", reason: ocrLayer.reason }); + } + + return { + eligible: base.eligible || ssimLayer.eligible || ocrLayer.eligible, + reason: base.reason, + layers, + skipped, + ruleDiff: base.ruleDiff, + ssim: ssimLayer.ssim, + ocrReadback: ocrLayer.ocrReadback, + warnings: [...base.warnings, ...ssimLayer.warnings, ...ocrLayer.warnings], + runtimeMs: base.runtimeMs + ssimLayer.runtimeMs + ocrLayer.runtimeMs, + }; +} diff --git a/public/formats/inline-tokens.js b/public/formats/inline-tokens.js index 45cb643..87af827 100644 --- a/public/formats/inline-tokens.js +++ b/public/formats/inline-tokens.js @@ -54,6 +54,35 @@ export function parseInlineMarkdown(text) { while (index < source.length) { const ch = source[index]; + // LaTeX 数学：$$...$$（块级）/ $...$（行内）。内容逐字保留，不递归、不转义（须在转义 + // 处理之前，避免 \frac 的反斜杠被吃掉）。行内启发式：定界符内侧不得为空白，避免把 + // "$5 ... $10" 这类货币误判为数学。 + if (ch === "$") { + if (source.startsWith("$$", index)) { + const end = source.indexOf("$$", index + 2); + if (end > index + 2) { + const inner = source.slice(index + 2, end); + if (inner.trim()) { + pushText(); + tokens.push({ type: "math", display: true, value: inner }); + index = end + 2; + continue; + } + } + } else { + const end = source.indexOf("$", index + 1); + if (end > index + 1) { + const inner = source.slice(index + 1, end); + if (inner && !inner.includes("\n") && !/^\s/.test(inner) && !/\s$/.test(inner)) { + pushText(); + tokens.push({ type: "math", display: false, value: inner }); + index = end + 1; + continue; + } + } + } + } + // 转义 if (ch === "\\" && index + 1 < source.length) { buffer += source[index + 1]; diff --git a/public/index.html b/public/index.html index 5d1f07a..7f9343b 100644 --- a/public/index.html +++ b/public/index.html @@ -7,6 +7,8 @@ + +
@@ -225,6 +227,18 @@

Trans2Former

+
diff --git a/public/katex-render.js b/public/katex-render.js new file mode 100644 index 0000000..6e5fb1f --- /dev/null +++ b/public/katex-render.js @@ -0,0 +1,23 @@ +// LaTeX 渲染：把 inline 渲染器产出的 `` +// 用 KaTeX 排版。KaTeX 经
diff --git a/public/preview.js b/public/preview.js index d30b89f..614561a 100644 --- a/public/preview.js +++ b/public/preview.js @@ -3,6 +3,7 @@ import { renderPreviewHtml, toDocumentModel, } from "./browser-transformer.js"; +import { renderMathIn } from "./katex-render.js"; const TEXT_LIKE_FORMATS = new Set(["md", "html", "txt", "json", "csv", "xml"]); const IMAGE_FORMATS = new Set(["png"]); @@ -99,6 +100,7 @@ function renderTextLike(content, format) { wrap.className = "preview-canvas preview-markdown"; try { wrap.innerHTML = renderPreviewHtml(content, format, payload?.source?.fileName || "preview"); + renderMathIn(wrap); } catch (error) { wrap.textContent = String(content || ""); } diff --git a/public/security-center.js b/public/security-center.js index 170da06..dd403e4 100644 --- a/public/security-center.js +++ b/public/security-center.js @@ -10,6 +10,10 @@ import { markTesseractVendorReady, sha256Hex, tesseractOCREngine, + paddleOcrEngine, + markPaddleOcrVendorReady, + PADDLE_OCR_MODEL_FILES, + PADDLE_OCR_REQUIRED_FILES, } from "/browser-transformer.js"; const ORIGIN = location.origin; @@ -225,7 +229,9 @@ function renderModelCache(dialog) { `; const actionsHtml = entry.manifest.task === "ocr-text" && entry.manifest.engine === "tesseract" ? renderTesseractActions(entry) - : ""; + : (entry.manifest.task === "ocr-text" && entry.manifest.engine === "paddleocr" + ? renderPaddleActions(entry) + : ""); li.innerHTML = headerHtml + actionsHtml; list.appendChild(li); } @@ -249,6 +255,19 @@ function renderTesseractActions(entry) { `; } +function renderPaddleActions(entry) { + const ready = entry.status === STATUS_AVAILABLE; + const importButtons = PADDLE_OCR_MODEL_FILES.map((file) => + ``, + ).join(""); + return ` +
+ ${importButtons} + +
+ `; +} + function setStatusMessage(dialog, text, level = "info") { const target = dialog.querySelector("[data-model-cache-status]"); if (!target) return; @@ -328,6 +347,91 @@ async function clearTessdata(dialog, button) { } } +async function importPaddleModel(dialog, button) { + const file = button.dataset.file || "det.onnx"; + const manifestId = button.dataset.manifestId; + const fileInput = dialog.querySelector("#modelCacheFileInput"); + if (!fileInput) { + setStatusMessage(dialog, "无法找到文件选择器", "error"); + return; + } + await new Promise((resolve) => { + const handler = async () => { + fileInput.removeEventListener("change", handler); + const picked = fileInput.files?.[0]; + fileInput.value = ""; + if (!picked) { + resolve(); + return; + } + try { + defaultModelCache.setStatus(manifestId, STATUS_VERIFYING, { message: `校验 ${picked.name}…` }); + setStatusMessage(dialog, `正在校验 ${picked.name} (${(picked.size / 1024).toFixed(0)} KB)…`, "info"); + const buffer = await picked.arrayBuffer(); + const sha256 = await sha256Hex(buffer); + await defaultOCRStorage.put(`paddleocr/v5/${file}`, buffer, { sha256 }); + // 先置位 vendor-ready（用户已选用 PP-OCRv5），再 probe；否则 ensureProbe 在 vendor + // 未置位时恒返回 false，状态永远翻不过去。真正的 onnxruntime 运行时加载仍在 + // recognize() 时把关。对齐 paddle-default-models.js / tesseract 导入流程的顺序。 + markPaddleOcrVendorReady(true); + const ready = typeof paddleOcrEngine.ensureProbe === "function" + ? await paddleOcrEngine.ensureProbe() + : false; + if (ready) { + defaultModelCache.setStatus(manifestId, STATUS_AVAILABLE, { + message: `PP-OCRv5 必选模型 (det/rec) 就位 (最近导入 ${file}, sha256=${sha256.slice(0, 12)}…)`, + file, + sha256, + size: buffer.byteLength, + }); + setStatusMessage(dialog, `${file} 已导入，PP-OCRv5 必选模型齐全 ✅（cls 可选）`, "success"); + } else { + const missing = await missingPaddleFiles(); + defaultModelCache.setStatus(manifestId, STATUS_VERIFYING, { + message: `已导入 ${file}；还需导入：${missing.join(", ") || "(无)"}`, + }); + setStatusMessage(dialog, `${file} 已导入；还需导入：${missing.join(", ")}`, "info"); + } + } catch (error) { + defaultModelCache.setStatus(manifestId, STATUS_NOT_DOWNLOADED, { + message: `导入失败：${error?.message || error}`, + }); + setStatusMessage(dialog, `导入 ${file} 失败：${error?.message || error}`, "error"); + } + resolve(); + }; + fileInput.addEventListener("change", handler); + fileInput.click(); + }); +} + +async function missingPaddleFiles() { + // 只报必选缺失（det/rec）；cls 为可选，不算缺。 + const missing = []; + for (const file of PADDLE_OCR_REQUIRED_FILES) { + if (!(await defaultOCRStorage.has(`paddleocr/v5/${file}`))) missing.push(file); + } + return missing; +} + +async function clearPaddleModels(dialog, button) { + const manifestId = button.dataset.manifestId; + try { + for (const file of PADDLE_OCR_MODEL_FILES) { + await defaultOCRStorage.delete(`paddleocr/v5/${file}`); + } + if (typeof paddleOcrEngine.ensureProbe === "function") { + await paddleOcrEngine.ensureProbe(); + } + defaultModelCache.setStatus(manifestId, STATUS_NOT_DOWNLOADED, { + message: "已清除本地 PP-OCRv5 模型；下次启用需重新导入 det/rec（cls 可选）。", + }); + setStatusMessage(dialog, "PP-OCRv5 模型已清除", "info"); + } catch (error) { + setStatusMessage(dialog, `清除失败：${error?.message || error}`, "error"); + } +} + function formatBundleSize(bytes) { if (!Number.isFinite(bytes) || bytes <= 0) return "未声明体积"; const units = ["B", "KB", "MB", "GB"]; @@ -383,6 +487,12 @@ function init() { } else if (target.matches("[data-clear-tessdata]")) { event.preventDefault(); clearTessdata(dialog, target); + } else if (target.matches("[data-import-paddle]")) { + event.preventDefault(); + importPaddleModel(dialog, target); + } else if (target.matches("[data-clear-paddle]")) { + event.preventDefault(); + clearPaddleModels(dialog, target); } }); } diff --git a/public/styles.css b/public/styles.css index dc9fd81..d4aa35b 100644 --- a/public/styles.css +++ b/public/styles.css @@ -1420,6 +1420,100 @@ button:disabled { color: #ffe5eb; } +/* P9-C.4 转换检验报告：呈现规则 diff + SSIM + OCR 回读三层检验结果 */ +.verification-report { + margin: 10px; + padding: 8px 10px; + border: 1px solid var(--border); + border-radius: var(--radius); + background: var(--surface); + font-size: 0.78rem; +} + +.verification-report[hidden] { + display: none; +} + +.verification-report > summary { + cursor: pointer; + font-weight: 600; + color: var(--text); + list-style: revert; +} + +.verification-badge { + margin-left: 6px; + padding: 1px 8px; + border-radius: 999px; + font-size: 0.68rem; + font-weight: 500; + background: rgba(45, 156, 142, 0.14); + color: #1f6f64; +} + +.verification-badge[data-state="skip"] { + background: rgba(120, 132, 148, 0.16); + color: #586172; +} + +.verification-note { + margin: 8px 0 6px; + color: var(--muted, #6b7280); + font-size: 0.7rem; +} + +.verification-grid { + display: grid; + gap: 6px; + margin: 0; +} + +.verification-row { + display: grid; + grid-template-columns: 7.5rem minmax(0, 1fr); + align-items: baseline; + gap: 8px; + padding: 5px 8px; + border: 1px 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io{constructor(e,t){this.mode=void 0,this.gullet=void 0,this.settings=void 0,this.leftrightDepth=void 0,this.nextToken=void 0,this.mode="math",this.gullet=new to(e,t,this.mode),this.settings=t,this.leftrightDepth=0,this.nextToken=null}expect(e,t){if(void 0===t&&(t=!0),this.fetch().text!==e)throw new n("Expected '"+e+"', got '"+this.fetch().text+"'",this.fetch());t&&this.consume()}consume(){this.nextToken=null}fetch(){return null==this.nextToken&&(this.nextToken=this.gullet.expandNextToken()),this.nextToken}switchMode(e){this.mode=e,this.gullet.switchMode(e)}parse(){this.settings.globalGroup||this.gullet.beginGroup(),this.settings.colorIsTextColor&&this.gullet.macros.set("\\color","\\textcolor");try{const e=this.parseExpression(!1);return this.expect("EOF"),this.settings.globalGroup||this.gullet.endGroup(),e}finally{this.gullet.endGroups()}}subparse(e){const t=this.nextToken;this.consume(),this.gullet.pushToken(new en("}")),this.gullet.pushTokens(e);const r=this.parseExpression(!1);return this.expect("}"),this.nextToken=t,r}parseExpression(e,t){const r=[];for(;;){"math"===this.mode&&this.consumeSpaces();const n=this.fetch();if(io.endOfExpression.has(n.text))break;if(t&&n.text===t)break;if(e&&Ln[n.text]&&Ln[n.text].infix)break;const o=this.parseAtom(t);if(!o)break;"internal"!==o.type&&r.push(o)}return"text"===this.mode&&this.formLigatures(r),this.handleInfixNodes(r)}handleInfixNodes(e){let t,r=-1;for(let o=0;o=128))return null;this.settings.strict&&(T(t.charCodeAt(0))?"math"===this.mode&&this.settings.reportNonstrict("unicodeTextInMathMode",'Unicode text character "'+t[0]+'" used in math mode',e):this.settings.reportNonstrict("unknownSymbol",'Unrecognized Unicode character "'+t[0]+'" ('+t.charCodeAt(0)+")",e)),o={type:"textord",mode:"text",loc:Qr.range(e),text:t}}if(this.consume(),r)for(let t=0;t t.trim()).filter(Boolean) || args.tiers; + else if (argv[i] === "--out") args.out = argv[++i] || args.out; + } + return args; +} + +function decodeDataUrlToBuffer(dataUrl) { + const comma = dataUrl.indexOf(","); + const base64 = dataUrl.slice(comma + 1); + return Buffer.from(base64, "base64"); +} + +function toBinaryBuffer(result) { + const data = result?.data ?? result; + if (typeof data === "string" && data.startsWith("data:")) return decodeDataUrlToBuffer(data); + if (data instanceof Uint8Array) return Buffer.from(data); + throw new Error("unexpected binary writer output"); +} + +// 每个 tier 的文本源 builder scale。 +function scaleForTier(tier, builderKey) { + if (tier === "large") { + return buildToTargetBytes(TEXT_BUILDERS[builderKey], LARGE_TARGET_BYTES).scale; + } + return SIZE_TIERS[tier]; +} + +// 大尺寸 PNG（>3MB 原始像素 → 压缩后视图案而定）。 +const PNG_DIMS = { small: [96, 64], medium: [640, 480], large: [1600, 1600] }; + +async function emit(manifest, outDir, format, tier, buffer, source) { + const dir = path.join(outDir, tier); + await mkdir(dir, { recursive: true }); + const fileName = `${format}-${tier}.${format}`; + const filePath = path.join(dir, fileName); + await writeFile(filePath, buffer); + manifest.files.push({ + format, + tier, + path: path.relative(".", filePath).replaceAll("\\", "/"), + bytes: buffer.length, + source, + }); + const mb = (buffer.length / (1024 * 1024)).toFixed(2); + console.log(` ${format.padEnd(5)} ${tier.padEnd(6)} ${String(buffer.length).padStart(9)} B (${mb} MB) ${fileName}`); +} + +async function generateTier(manifest, outDir, tier) { + console.log(`\n[tier: ${tier}]`); + + // 1) 文本原生格式：md / html / json / xml / csv / txt + const textSources = {}; + for (const key of Object.keys(TEXT_BUILDERS)) { + const scale = scaleForTier(tier, key); + const content = TEXT_BUILDERS[key](scale); + textSources[key] = content; + await emit(manifest, outDir, key, tier, Buffer.from(content, "utf8"), `builder:${key}@scale=${scale}`); + } + + // 2) 重格式经项目自带 writer 程序化产出（输入用上面的文本源）。 + const binaryJobs = [ + { format: "docx", from: "md", source: () => textSources.md }, + { format: "pptx", from: "md", source: () => textSources.md }, + { format: "epub", from: "md", source: () => textSources.md }, + { format: "pdf", from: "md", source: () => textSources.md }, + { format: "xlsx", from: "csv", source: () => textSources.csv }, + ]; + for (const job of binaryJobs) { + try { + const result = convertContent({ + content: job.source(), + from: job.from, + to: job.format, + title: `sample-${job.format}-${tier}`, + options: { repair: false }, + }); + await emit(manifest, outDir, job.format, tier, toBinaryBuffer(result), `convert:${job.from}->${job.format}`); + } catch (error) { + console.log(` ${job.format.padEnd(5)} ${tier.padEnd(6)} SKIPPED (${error.message})`); + manifest.skipped.push({ format: job.format, tier, reason: error.message }); + } + } + + // 3) PNG：程序化棋盘+渐变图（无 writer，直接编码）。 + const [pw, ph] = PNG_DIMS[tier] || PNG_DIMS.small; + await emit(manifest, outDir, "png", tier, buildPatternPng(pw, ph), `png-encode:${pw}x${ph}`); +} + +async function main() { + const { tiers, out } = parseArgs(process.argv.slice(2)); + const outDir = path.resolve(out); + console.log(`Trans2Former sample generator → ${path.relative(".", outDir) || outDir}`); + console.log(`tiers: ${tiers.join(", ")}`); + + await rm(outDir, { recursive: true, force: true }); + await mkdir(outDir, { recursive: true }); + + const manifest = { + schema: "trans2former.sample-corpus.v1", + generatedAt: new Date().toISOString(), + tiers, + note: "Programmatically regenerated fixtures. Binaries are git-ignored; rerun `npm run samples:generate`.", + coverageGaps: [ + { format: "doc", reason: "legacy Word binary has no writer; reader is best-effort only" }, + { format: "ofd", reason: "OFD writer not implemented (reader is L0); see docs/OFD_RESEARCH.md" }, + ], + files: [], + skipped: [], + }; + + for (const tier of tiers) { + if (!(tier in SIZE_TIERS)) { + console.log(`(skip unknown tier: ${tier})`); + continue; + } + await generateTier(manifest, outDir, tier); + } + + await writeFile(path.join(outDir, "MANIFEST.json"), JSON.stringify(manifest, null, 2)); + + const largest = manifest.files.reduce((max, f) => Math.max(max, f.bytes), 0); + console.log(`\nDone. ${manifest.files.length} files, ${manifest.skipped.length} skipped. Largest: ${(largest / (1024 * 1024)).toFixed(2)} MB.`); + console.log(`Manifest: ${path.relative(".", path.join(outDir, "MANIFEST.json")).replaceAll("\\", "/")}`); +} + +main().catch((error) => { + console.error("Sample generation failed:", error); + process.exit(1); +}); diff --git a/scripts/latex-math-test.js b/scripts/latex-math-test.js new file mode 100644 index 0000000..a70500b --- /dev/null +++ b/scripts/latex-math-test.js @@ -0,0 +1,80 @@ +import assert from "node:assert/strict"; + +import { + convertContent, +} from "../public/browser-transformer.js"; +import { parseInlineMarkdown } from "../public/formats/inline-tokens.js"; +import { + inlinesToHtml, + inlinesToMarkdown, + inlinesToPlainText, + createInlineMath, +} from "../public/core/models/semantic-inlines.js"; + +const BACKSLASH = String.fromCharCode(92); +const frac = `${BACKSLASH}frac{a}{b}`; // \frac{a}{b} +const sum = `${BACKSLASH}sum_{i=1}^{n}`; // \sum_{i=1}^{n} + +// 1. Inline $...$ recognized; backslash + underscore preserved verbatim +{ + const toks = parseInlineMarkdown(`pre $x^2 + y_0$ post`); + const math = toks.find((t) => t.type === "math"); + assert.ok(math, "inline $...$ should produce a math token"); + assert.equal(math.display, false); + assert.equal(math.value, "x^2 + y_0"); +} + +// 2. Display $$...$$ preserves backslashes (no markdown escaping eats \frac / \sum) +{ + const toks = parseInlineMarkdown(`$$${frac} = ${sum} c_i$$`); + const math = toks.find((t) => t.type === "math"); + assert.ok(math, "display $$...$$ should produce a math token"); + assert.equal(math.display, true); + assert.equal(math.value.charCodeAt(0), 92, "value must start with a literal backslash"); + assert.ok(math.value.includes(frac), "\\frac must be preserved verbatim"); + assert.ok(math.value.includes(sum), "\\sum must be preserved verbatim"); +} + +// 3. Currency is NOT treated as math (heuristic: no inner-edge whitespace) +{ + const toks = parseInlineMarkdown("pay $5 and $10 today"); + assert.equal(toks.some((t) => t.type === "math"), false, "currency $5 / $10 must not become math"); +} + +// 4. HTML output emits a katex-targetable span carrying raw tex in data-tex +{ + const html = inlinesToHtml(parseInlineMarkdown(`$${frac}$`)); + assert.ok(html.includes('class="t2f-math"'), "math should render a .t2f-math span"); + assert.ok(html.includes('data-display="false"')); + assert.ok(html.includes(`data-tex="${frac}"`), "data-tex must carry the raw tex (backslash preserved)"); +} + +// 5. Markdown round-trip preserves $...$ and $$...$$ verbatim +{ + const md = `inline $x^2$ and block:\n\n$$${frac}$$\n`; + const toks = parseInlineMarkdown(`inline $x^2$ and block: $$${frac}$$`); + const rendered = inlinesToMarkdown(toks); + assert.ok(rendered.includes("$x^2$"), "inline math round-trips"); + assert.ok(rendered.includes(`$$${frac}$$`), "display math round-trips with backslash"); + + const result = convertContent({ content: md, from: "md", to: "md", options: { repair: false } }); + assert.ok(result.data.includes("$x^2$")); + assert.ok(result.data.includes(`$$${frac}$$`)); +} + +// 6. Plain text keeps delimited tex; createInlineMath factory shape +{ + const node = createInlineMath("E=mc^2", false); + assert.deepEqual(node, { type: "math", value: "E=mc^2", display: false }); + assert.equal(inlinesToPlainText([node]), "$E=mc^2$"); + assert.equal(inlinesToPlainText([createInlineMath("x", true)]), "$$x$$"); +} + +// 7. End-to-end md -> html conversion emits math spans (not from underscores) +{ + const result = convertContent({ content: `$$a_b + ${frac}$$`, from: "md", to: "html", options: { repair: false } }); + assert.ok(result.data.includes("t2f-math"), "html conversion should contain a math span"); + assert.ok(!result.data.includes("b"), "underscore inside math must not become "); +} + +console.log("LaTeX math test passed: inline/display tokenization (backslash + underscore preserved), currency exclusion, katex-targetable html span, markdown round-trip, plain-text + factory verified."); diff --git a/scripts/lib/png-encode.js b/scripts/lib/png-encode.js new file mode 100644 index 0000000..506795e --- /dev/null +++ b/scripts/lib/png-encode.js @@ -0,0 +1,80 @@ +// 最小 PNG 编码器（Node 端，仅用于生成测试样例，不进入 public/ 运行时）。 +// 用 node:zlib deflate 压缩，输出真实可读的 RGBA PNG。支持生成大尺寸图（>3MB）。 + +import zlib from "node:zlib"; + +const PNG_SIGNATURE = Buffer.from([0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a]); + +const CRC_TABLE = (() => { + const table = new Uint32Array(256); + for (let n = 0; n < 256; n += 1) { + let c = n; + for (let k = 0; k < 8; k += 1) { + c = c & 1 ? 0xedb88320 ^ (c >>> 1) : c >>> 1; + } + table[n] = c >>> 0; + } + return table; +})(); + +function crc32(buffer) { + let crc = 0xffffffff; + for (let i = 0; i < buffer.length; i += 1) { + crc = CRC_TABLE[(crc ^ buffer[i]) & 0xff] ^ (crc >>> 8); + } + return (crc ^ 0xffffffff) >>> 0; +} + +function chunk(type, data) { + const typeBuf = Buffer.from(type, "ascii"); + const lengthBuf = Buffer.alloc(4); + lengthBuf.writeUInt32BE(data.length, 0); + const crcBuf = Buffer.alloc(4); + crcBuf.writeUInt32BE(crc32(Buffer.concat([typeBuf, data])), 0); + return Buffer.concat([lengthBuf, typeBuf, data, crcBuf]); +} + +// pixelFn(x, y) -> [r, g, b, a] (0-255). 生成 width×height RGBA PNG Buffer。 +export function encodePng(width, height, pixelFn) { + const ihdr = Buffer.alloc(13); + ihdr.writeUInt32BE(width, 0); + ihdr.writeUInt32BE(height, 4); + ihdr.writeUInt8(8, 8); // bit depth + ihdr.writeUInt8(6, 9); // color type RGBA + ihdr.writeUInt8(0, 10); // compression + ihdr.writeUInt8(0, 11); // filter + ihdr.writeUInt8(0, 12); // interlace + + const stride = width * 4; + const raw = Buffer.alloc((stride + 1) * height); + for (let y = 0; y < height; y += 1) { + raw[y * (stride + 1)] = 0; // filter type none + for (let x = 0; x < width; x += 1) { + const [r, g, b, a] = pixelFn(x, y); + const offset = y * (stride + 1) + 1 + x * 4; + raw[offset] = r & 0xff; + raw[offset + 1] = g & 0xff; + raw[offset + 2] = b & 0xff; + raw[offset + 3] = a & 0xff; + } + } + const idatData = zlib.deflateSync(raw, { level: 6 }); + + return Buffer.concat([ + PNG_SIGNATURE, + chunk("IHDR", ihdr), + chunk("IDAT", idatData), + chunk("IEND", Buffer.alloc(0)), + ]); +} + +// 生成一张确定性的彩色棋盘 + 渐变图，便于视觉/OCR 占位测试。 +export function buildPatternPng(width, height) { + return encodePng(width, height, (x, y) => { + const checker = ((x >> 4) + (y >> 4)) % 2 === 0; + const r = Math.floor((x / width) * 255); + const g = Math.floor((y / height) * 255); + const b = checker ? 200 : 60; + return [r, g, b, 255]; + }); +} diff --git a/scripts/lib/sample-content.js b/scripts/lib/sample-content.js new file mode 100644 index 0000000..d784745 --- /dev/null +++ b/scripts/lib/sample-content.js @@ -0,0 +1,181 @@ +// 优质测试样例内容生成器（纯函数，确定性）。供 generate-samples.js 写盘和 +// sample-corpus-test.js 小规模回归共用。每个 builder 接受 scale（章节重复次数）， +// 用来产出大小不一的复杂样例：scale=1 小，scale≈120 中（~300KB），scale≈1300 大（≥3MB）。 + +export const SIZE_TIERS = Object.freeze({ + small: 1, + medium: 120, + large: 1300, +}); + +// 复杂文本素材：中英文、RTL、emoji、标点、实体、长词。确定性、无随机。 +const PARAGRAPH_SNIPPETS = [ + "Trans2Former 是一个**本地优先**、_零上传_的多格式文档转换工作台，强调确定性算法转换、本地 OCR 与转换后质量检验。", + "The quick brown fox jumps over the lazy dog while 中文、日本語、한국어 and emoji 🚀📄✅ coexist in one paragraph.", + "数学近似：E = mc^2，π ≈ 3.14159，∑(1/n^2) = π²/6；货币 $1,234.56 / €987,65 / ¥10000。", + "RTL 混排：العربية والعبرية טקסט مع English inline，验证双向文本不破坏块结构。", + "特殊字符与实体：< > & \" ' © ® ™ — – … « » 「」『』，以及 HTML 实体 & < © 的往返保真。", + "Edge tokens: supercalifragilisticexpialidocious, a_very_long_snake_case_identifier_that_should_not_wrap_oddly, and URLs like https://example.com/path?query=1&lang=zh#frag.", +]; + +const CODE_SAMPLES = [ + { lang: "javascript", code: "export function convert(input) {\n const model = read(input);\n return write(model); // round-trip\n}" }, + { lang: "python", code: "def fib(n):\n a, b = 0, 1\n for _ in range(n):\n a, b = b, a + b\n return a # 斐波那契" }, + { lang: "json", code: "{\n \"name\": \"trans2former\",\n \"local\": true,\n \"formats\": [\"md\", \"pdf\", \"docx\"]\n}" }, + { lang: "sql", code: "SELECT id, name FROM docs WHERE lang = 'zh-CN' ORDER BY created_at DESC;" }, +]; + +function repeatedField(base, index) { + return `${base}-${String(index).padStart(5, "0")}`; +} + +export function buildComplexMarkdown(scale = 1) { + const parts = []; + parts.push("# Trans2Former 综合能力测试样例\n"); + parts.push("> 本文件由 `scripts/generate-samples.js` 程序化生成，用于压力测试转换、版面与检验能力。\n"); + parts.push("[TOC]\n"); + for (let s = 0; s < scale; s += 1) { + const n = s + 1; + parts.push(`## 第 ${n} 章 · 复杂排版段落\n`); + for (const snippet of PARAGRAPH_SNIPPETS) { + parts.push(`${snippet}\n`); + } + parts.push(`### ${n}.1 列表与任务\n`); + parts.push("- 无序项 A\n - 嵌套项 A.1\n - 深层项 A.1.a\n- 无序项 B\n"); + parts.push("1. 有序项一\n2. 有序项二\n 1. 子项 2.1\n 2. 子项 2.2\n"); + parts.push("- [x] 已完成任务\n- [ ] 待办任务\n"); + parts.push(`### ${n}.2 表格（含对齐 + 中文 + 数字）\n`); + parts.push("| 左对齐 | 居中 | 右对齐 |\n| :--- | :---: | ---: |\n"); + for (let r = 0; r < 6; r += 1) { + parts.push(`| ${repeatedField("项目", n * 10 + r)} | 状态-${r} | ${(r * 1234.5).toFixed(2)} |\n`); + } + parts.push("\n"); + const code = CODE_SAMPLES[s % CODE_SAMPLES.length]; + parts.push(`### ${n}.3 代码块（${code.lang}）\n`); + parts.push("```" + code.lang + "\n" + code.code + "\n```\n"); + parts.push("> 引用块：转换核心围绕 `input -> canonical model -> mapper route -> QualityReport -> output`。\n>> 嵌套引用：规则 diff + SSIM + OCR 回读 三层检验。\n"); + parts.push(`![示意图 ${n}](https://example.com/img/${n}.png "图 ${n}")\n`); + parts.push("脚注引用[^note" + n + "]，行内 `code`、**粗体**、*斜体*、~~删除线~~ 与 [链接](https://example.com)。\n"); + parts.push(`[^note${n}]: 第 ${n} 章脚注内容，验证脚注往返。\n`); + parts.push("\n---\n\n"); + } + return parts.join("\n"); +} + +export function buildComplexHtml(scale = 1) { + const parts = []; + parts.push("\n综合 HTML 样例"); + parts.push("

Trans2Former HTML 能力测试

"); + for (let s = 0; s < scale; s += 1) { + const n = s + 1; + parts.push(`

第 ${n} 节

`); + for (const snippet of PARAGRAPH_SNIPPETS) { + parts.push(`

${snippet.replace(/&/g, "&").replace(/`); + } + parts.push("

  • 无序 A
    • 嵌套 A.1
  • 无序 B
"); + parts.push("
  1. 有序一
  2. 有序二
    1. 子 2.1
"); + parts.push(""); + for (let r = 0; r < 6; r += 1) { + parts.push(``); + } + parts.push("
列1列2列3
${repeatedField("单元", n * 10 + r)}${r}${(r * 99.9).toFixed(2)}
"); + const code = CODE_SAMPLES[s % CODE_SAMPLES.length]; + parts.push(`
${code.code.replace(/
`); + parts.push("

引用：本地优先、零上传。

"); + parts.push(`
图 ${n}
图 ${n}
`); + } + parts.push(""); + return parts.join("\n"); +} + +export function buildComplexJson(scale = 1) { + const records = []; + for (let s = 0; s < scale; s += 1) { + records.push({ + id: repeatedField("doc", s), + title: `文档 ${s + 1} · Document ${s + 1}`, + tags: ["中文", "english", "العربية", "emoji-🚀"], + meta: { + author: `作者-${s}`, + nested: { level: 3, values: [s, s * 2, s * 3], note: "深层嵌套 nested object" }, + unicode: "特殊字符 < > & \" ' © — …", + }, + sections: PARAGRAPH_SNIPPETS.map((text, i) => ({ index: i, text })), + }); + } + return JSON.stringify({ schema: "trans2former.sample.v1", count: records.length, records }, null, 2); +} + +export function buildComplexXml(scale = 1) { + const parts = []; + parts.push(""); + parts.push(""); + for (let s = 0; s < scale; s += 1) { + const n = s + 1; + parts.push(` `); + parts.push(` 复杂书目 ${n} & Title ${n}`); + parts.push(` 作者 ${n}`); + parts.push(` 与 & 符号的 CDATA 段，第 ${n} 条。 ]]>`); + parts.push(" 中文englishemoji-🚀"); + parts.push(` ${(n * 12.5).toFixed(2)}`); + parts.push(" "); + } + parts.push(""); + return parts.join("\n"); +} + +export function buildComplexCsv(scale = 1) { + const rows = []; + rows.push("id,名称,description,price,tags,note"); + for (let s = 0; s < scale; s += 1) { + for (let r = 0; r < 6; r += 1) { + const idx = s * 6 + r; + const desc = `含逗号, 引号"和换行\n的字段 ${idx}`; + const tags = "中文;english;🚀"; + rows.push(`${idx},"产品 ${idx}","${desc.replace(/"/g, "\"\"")}",${(idx * 3.14).toFixed(2)},"${tags}","note ${idx} — 特殊字符 < > &"`); + } + } + return rows.join("\n"); +} + +export function buildComplexText(scale = 1) { + const parts = []; + parts.push("Trans2Former 纯文本能力测试样例"); + parts.push("=".repeat(60)); + for (let s = 0; s < scale; s += 1) { + const n = s + 1; + parts.push(`\n[第 ${n} 段]`); + for (const snippet of PARAGRAPH_SNIPPETS) { + // 去掉 markdown 标记，纯文本 + parts.push(snippet.replace(/[*_~`#>]/g, "")); + } + parts.push("超长单行：" + "长词".repeat(200) + " end-of-line-" + n); + parts.push("制表符\t分隔\t列1\t列2\t列3"); + } + return parts.join("\n"); +} + +// 把某个 builder 反复扩到至少 targetBytes 字节（用于精确逼近 3MB）。 +export function buildToTargetBytes(builder, targetBytes) { + let scale = 1; + let content = builder(scale); + const perScale = Buffer.byteLength(builder(2), "utf8") - Buffer.byteLength(builder(1), "utf8"); + if (perScale > 0) { + scale = Math.max(1, Math.ceil(targetBytes / perScale)); + content = builder(scale); + while (Buffer.byteLength(content, "utf8") < targetBytes) { + scale = Math.ceil(scale * 1.15) + 1; + content = builder(scale); + } + } + return { content, scale }; +} + +export const TEXT_BUILDERS = Object.freeze({ + md: buildComplexMarkdown, + html: buildComplexHtml, + json: buildComplexJson, + xml: buildComplexXml, + csv: buildComplexCsv, + txt: buildComplexText, +}); diff --git a/scripts/local-model-direction-test.js b/scripts/local-model-direction-test.js index b34aadb..2c8733f 100644 --- a/scripts/local-model-direction-test.js +++ b/scripts/local-model-direction-test.js @@ -41,6 +41,7 @@ assertIncludes("tasks", "model-cache"); assertIncludes("tasks", "30–80 MB"); assertIncludes("tasks", "默认包不含 GB 级模型"); assertIncludes("tasks", "OCR 模型按需下载"); +assertIncludes("tasks", "qualityReport.ruleDiff"); assertExcludes("tasks", "不依赖 Office、LibreOffice、Pandoc、云端转换或 OCR/AI"); assertExcludesPattern( "tasks", @@ -146,6 +147,22 @@ assertIncludes("multiModel", "ocrResultToFixedLayoutPage"); assertIncludes("multiModel", "mergeOCRResultsToFixedLayout"); assertIncludes("multiModel", "createBrowserPdfPageRasterizer"); assertIncludes("multiModel", "MODEL_TEXT_ORDER_HEURISTIC"); +assertIncludes("multiModel", "runVerificationStage"); +assertIncludes("multiModel", "diffSemanticDocs"); +assertIncludes("multiModel", "RULE_DIFF_DRIFT"); +assertIncludes("multiModel", "computeSSIM"); +assertIncludes("multiModel", "runVerificationStageAsync"); +assertIncludes("multiModel", "SSIM_VISUAL_DRIFT"); +assertIncludes("multiModel", "runOcrReadbackLayer"); +assertIncludes("multiModel", "compareText"); +assertIncludes("multiModel", "OCR_READBACK_DRIFT"); +assertIncludes("multiModel", "PP-OCRv5"); +assertIncludes("multiModel", "ONNX"); +assertIncludes("multiModel", "WebGPU"); +assertIncludes("multiModel", "paddleOcrEngine"); +assertIncludes("multiModel", "onnxruntime-web"); +assertIncludes("multiModel", "runPaddlePipeline"); +assertIncludes("multiModel", "ctcGreedyDecode"); assertIncludes("budget", "model-cache///"); assertIncludes("budget", "SHA-256"); assertExcludes("multiModel", "external engine 一律插件化"); diff --git a/scripts/local-security-test.js b/scripts/local-security-test.js index cb880bd..c8fa17f 100644 --- a/scripts/local-security-test.js +++ b/scripts/local-security-test.js @@ -42,18 +42,54 @@ const ALLOWED_PUBLIC_FILES = new Set([ // scan-pdf-stage 串联 enhanceWithOCR 异步多页路径。两者均不联网。 path.normalize("public/core/ocr/pdf-rasterizer.js"), path.normalize("public/core/ocr/scan-pdf-stage.js"), + // P9-D.1/D.2/D.2.b PP-OCRv5 高级 OCR：engine 实现 OCREngine 契约；bootstrap 注册 engine + + // ONNX manifest；runtime 通过同源 vendor 加载 onnxruntime-web + WebGPU/WASM 后端；pipeline + // 是纯前后处理（预处理/DB 后处理/CTC 解码）+ 编排器；default-models fetch 同源 vendor 随包 + // 模型 → 本地缓存（开箱即用）。均不联网、不上传，仅访问 /vendor/ 同源资源。 + path.normalize("public/core/ocr/paddle-ocr-engine.js"), + path.normalize("public/core/ocr/paddle-ocr-bootstrap.js"), + path.normalize("public/core/ocr/paddle-ocr-runtime.js"), + path.normalize("public/core/ocr/paddle-ocr-pipeline.js"), + path.normalize("public/core/ocr/paddle-default-models.js"), // P9-B FixedLayoutModel + 浏览器 rasterize：ocr-to-fixed-layout 仅做数据映射； // pdf-rasterizer-browser dynamic import 同源 vendor pdfjs，运行时画布在浏览器/Tauri。 path.normalize("public/core/ocr/ocr-to-fixed-layout.js"), path.normalize("public/core/ocr/pdf-rasterizer-browser.js"), + // P9-C.1 转换后检验三层（规则 diff 层）：block-fingerprint 共享指纹；rule-diff 字段级 + // 结构对比；verification-stage 编排 writer→reader 回读 diff。三者均为纯函数，不联网、 + // 不持久化，下方 STRICT_LOCAL_ONLY_FILES 守门它们不得出现任何远程协议。 + path.normalize("public/core/verification/block-fingerprint.js"), + path.normalize("public/core/verification/rule-diff.js"), + path.normalize("public/core/verification/verification-stage.js"), + // P9-C.2 转换后检验三层（SSIM 视觉回环层）：ssim 纯算法；page-image-source 像素源抽象； + // page-image-source-browser 通过同源 vendor pdfjs + canvas 取像素。三者不联网。 + path.normalize("public/core/verification/ssim.js"), + path.normalize("public/core/verification/page-image-source.js"), + path.normalize("public/core/verification/page-image-source-browser.js"), + // P9-C.3 转换后检验三层（OCR 回读层）：ocr-readback 复用已注册 ocr-text engine + + // OCR pdf-rasterizer 把输出 PDF 读回文本做字符级相似度。纯逻辑，不联网。 + path.normalize("public/core/verification/ocr-readback.js"), ]); function isLocalVendorAsset(normalizedPath, content) { + // onnxruntime-web 是第三方运行时 bundle，其 minified 代码内含 CDN/源映射等远程 URL + // 字符串（无法在静态扫描层面剔除）。本项目对 ORT 的"零联网"保证来自两层运行时控制： + // (1) paddle-ocr-runtime.loadOnnxRuntime 把 ort.env.wasm.wasmPaths 钉到同源 vendor 目录， + // wasm 不走 CDN； + // (2) Tauri CSP `connect-src 'self'` 阻断任何远程连接。 + // 因此 onnxruntime vendor 整目录视为可信，不做"无远程 URL 字符串"硬扫描。 + if (normalizedPath.startsWith(path.normalize("public/vendor/onnxruntime/"))) { + return true; + } + // KaTeX 是纯同步数学排版库，运行时零网络 I/O。其 min.js 内的 http(s) 字符串仅为 W3C + // MathML/SVG 命名空间标识（createElementNS 用），非网络请求，故整目录视为可信。 + if (normalizedPath.startsWith(path.normalize("public/vendor/katex/"))) { + return true; + } const isVendor = normalizedPath.startsWith(path.normalize("public/vendor/pdfjs/")) || normalizedPath.startsWith(path.normalize("public/vendor/tesseract/")); if (!isVendor) return false; - // Vendor 资源（pdfjs / tesseract）允许内部 fetch / XHR 之类访问同源 wasm/worker； - // 但禁止任何远程 URL（http(s):// / ws(s)://）。 + // pdfjs / tesseract vendor：允许内部 fetch / XHR 访问同源 wasm/worker，但禁止任何远程 URL。 return !content.includes("http://") && !content.includes("https://") && !content.includes("ws://") @@ -112,6 +148,18 @@ const STRICT_LOCAL_ONLY_FILES = new Set([ path.normalize("public/core/ocr/scan-pdf-stage.js"), path.normalize("public/core/ocr/ocr-to-fixed-layout.js"), path.normalize("public/core/ocr/pdf-rasterizer-browser.js"), + path.normalize("public/core/ocr/paddle-ocr-engine.js"), + path.normalize("public/core/ocr/paddle-ocr-bootstrap.js"), + path.normalize("public/core/ocr/paddle-ocr-runtime.js"), + path.normalize("public/core/ocr/paddle-ocr-pipeline.js"), + path.normalize("public/core/ocr/paddle-default-models.js"), + path.normalize("public/core/verification/block-fingerprint.js"), + path.normalize("public/core/verification/rule-diff.js"), + path.normalize("public/core/verification/verification-stage.js"), + path.normalize("public/core/verification/ssim.js"), + path.normalize("public/core/verification/page-image-source.js"), + path.normalize("public/core/verification/page-image-source-browser.js"), + path.normalize("public/core/verification/ocr-readback.js"), ]); function assertNoRemoteUrlsInStrictFiles(filePath, content) { diff --git a/scripts/ocr-baseline-test.js b/scripts/ocr-baseline-test.js index 7e85747..6602772 100644 --- a/scripts/ocr-baseline-test.js +++ b/scripts/ocr-baseline-test.js @@ -50,6 +50,13 @@ import { MODEL_TEXT_ORDER_HEURISTIC, getFixedLayoutSummary, fixedLayoutToSemantic, + paddleOcrEngine, + PADDLE_OCR_MANIFEST_ID, + markPaddleOcrVendorReady, + ensurePaddleOcrBootstrap, + loadOnnxRuntime, + pickExecutionProviders, + PADDLE_VENDOR_PATHS, } from "../public/browser-transformer.js"; import { ConversionError } from "../public/core/conversion-error.js"; @@ -218,9 +225,9 @@ function makeStubEngine(overrides = {}) { // registered. With both isAvailable()=false, pickForTask falls back to the last // registered engine. Both ids are acceptable here. const picked = defaultOCRRegistry.pickForTask("ocr-text"); - assert.ok(picked, "pickForTask should return either placeholder or tesseract"); + assert.ok(picked, "pickForTask should return a fallback engine"); assert.equal( - ["placeholder", "tesseract-zh-en"].includes(picked.id), + ["placeholder", "tesseract-zh-en", "paddleocr-v5"].includes(picked.id), true, `pickForTask returned unexpected engine: ${picked.id}`, ); @@ -236,9 +243,9 @@ function makeStubEngine(overrides = {}) { assert.ok(ocrWarning, "PNG reader should attach OCR_UNAVAILABLE warning"); assert.equal(ocrWarning.severity, "info"); assert.equal( - ["placeholder", "tesseract-zh-en"].includes(ocrWarning.details?.engineId), + ["placeholder", "tesseract-zh-en", "paddleocr-v5"].includes(ocrWarning.details?.engineId), true, - `expected engineId to be placeholder or tesseract-zh-en, got ${ocrWarning.details?.engineId}`, + `expected engineId to be placeholder/tesseract/paddle, got ${ocrWarning.details?.engineId}`, ); } @@ -270,6 +277,13 @@ function makeStubEngine(overrides = {}) { const status = defaultModelCache.getStatus(TESSERACT_MANIFEST_ID); assert.ok(status, "tesseract manifest should be registered in defaultModelCache"); assert.equal(status.status, STATUS_NOT_DOWNLOADED); + + // ensureProbe must not throw on the frozen engine (readiness lives in module state, + // not a frozen instance prop) — otherwise the security-center import flow fails silently. + markTesseractVendorReady(true); + await assert.doesNotReject(() => tesseractOCREngine.ensureProbe(), "tesseract.ensureProbe must not throw on frozen engine"); + markTesseractVendorReady(false); + assert.equal(await tesseractOCREngine.ensureProbe(), false); } // 12. tesseractOCREngine.recognize rejects with OCR_UNAVAILABLE/OCR_ENGINE_FAILED depending on stage @@ -509,6 +523,18 @@ function makeStubEngine(overrides = {}) { options: { repair: false }, }); assert.equal(result.data.includes("ASYNC-STUB-TEXT"), true, "convertContentAsync should append OCR text into markdown output"); + + // Regression: the repair cycle must not clobber the OCR modelReview (ocr/ocrQuality) + // — convertContentAsync without repair:false should still surface OCR recognition quality. + const withRepair = await convertContentAsync({ + content: tinyPng, + from: "png", + to: "txt", + title: "async-stub-repair.png", + options: {}, + }); + assert.ok(withRepair.quality?.modelReview?.ocr, "result.quality.modelReview.ocr must survive the repair cycle for the UI"); + assert.equal(withRepair.quality.modelReview.ocr.engine, "async-stub"); } finally { defaultOCRRegistry.unregister(stubEngine.id); } @@ -544,6 +570,13 @@ function makeStubEngine(overrides = {}) { assert.equal(enhanced.metadata.ocr.lineCount, 1); assert.equal(enhanced.metadata.ocr.lines[0].text, "stage-line"); assert.equal(typeof enhanced.metadata.ocr.lines[0].confidence, "number"); + // blockId must resolve to a real appended OCR block that CONTAINS the line text, + // which is the precondition for low-confidence replaceTextRun repair to target it. + const lineBlockId = enhanced.metadata.ocr.lines[0].blockId; + assert.ok(lineBlockId && lineBlockId.startsWith("ocr-block-"), "ocr line should carry a stable ocr-block id"); + const target = enhanced.blocks.find((b) => b.id === lineBlockId); + assert.ok(target, "blockId should resolve to a real block in enhanced.blocks"); + assert.ok((target.text || "").includes("stage-line"), "target block text should contain the line text"); } finally { defaultOCRRegistry.unregister(stubEngine.id); } @@ -850,6 +883,16 @@ function makeStubEngine(overrides = {}) { warnings.find((w) => w.code === MODEL_TEXT_ORDER_HEURISTIC), "stage should emit MODEL_TEXT_ORDER_HEURISTIC info warning", ); + // Each ocr line must resolve to a real appended block CONTAINING its text — even though + // mergeOCRResultsToFixedLayout re-sorts by reading order (so lines order != block order). + const ocrLines = enhanced.metadata?.ocr?.lines || []; + assert.equal(ocrLines.length, 2, "two scanned pages => two ocr lines"); + for (const ln of ocrLines) { + assert.ok(ln.blockId && ln.blockId.startsWith("ocr-block-"), "scan-pdf ocr line should carry a stable ocr-block id"); + const target = enhanced.blocks.find((b) => b.id === ln.blockId); + assert.ok(target, "scan-pdf blockId should resolve to a real block"); + assert.ok((target.text || "").includes((ln.text || "").trim()), "target block should contain the line text"); + } } finally { defaultOCRRegistry.unregister(stubEngine.id); resetPdfPageRasterizer(); @@ -883,4 +926,160 @@ function makeStubEngine(overrides = {}) { ); } -console.log("OCR baseline test passed: contracts, registry, bootstraps, storage, png reader/async stage, repair validator, scan PDF detection + rasterizer skeleton + multi-page OCR stage + FixedLayoutModel mapping + browser rasterizer fallback all verified."); +// 35. PP-OCRv5 advanced OCR engine skeleton (P9-D.1): registered, unavailable in Node, +// manifest registered, recognize three-stage rejection. +{ + ensurePaddleOcrBootstrap(); + ensurePaddleOcrBootstrap(); + assert.equal(defaultOCRRegistry.has(paddleOcrEngine.id), true, "paddle engine should be registered after bootstrap"); + assert.equal(paddleOcrEngine.id, "paddleocr-v5"); + assert.equal(paddleOcrEngine.taskCapabilities.includes("ocr-text"), true); + assert.equal(paddleOcrEngine.taskCapabilities.includes("ocr-layout"), true); + assert.equal(paddleOcrEngine.isAvailable(), false, "paddle engine should report unavailable until P9-D.2 wires onnxruntime"); + + const status = defaultModelCache.getStatus(PADDLE_OCR_MANIFEST_ID); + assert.ok(status, "paddle manifest should be registered in defaultModelCache"); + assert.equal(status.status, STATUS_NOT_DOWNLOADED); + + // vendor not ready => OCR_UNAVAILABLE / vendor-not-ready + markPaddleOcrVendorReady(false); + await assert.rejects( + () => paddleOcrEngine.recognize({ image: { width: 10, height: 10 } }), + (err) => err instanceof ConversionError && err.code === OCR_UNAVAILABLE && err.details?.reason === "vendor-not-ready", + ); + + // vendor ready but models missing => OCR_UNAVAILABLE / model-missing + markPaddleOcrVendorReady(true); + try { + await assert.rejects( + () => paddleOcrEngine.recognize({ image: { width: 10, height: 10 } }), + (err) => err instanceof ConversionError && err.code === OCR_UNAVAILABLE && err.details?.reason === "model-missing", + ); + } finally { + markPaddleOcrVendorReady(false); + } +} + +// 36. PP-OCRv5 onnxruntime-web runtime loader (P9-D.2): EP selection + Node vendor-load reject. +{ + // Node has no navigator.gpu => wasm-only execution providers. + assert.deepEqual(pickExecutionProviders(), ["wasm"], "Node should pick wasm-only execution provider"); + assert.equal(PADDLE_VENDOR_PATHS.mainBundle, "/vendor/onnxruntime/ort.min.mjs"); + + // loadOnnxRuntime dynamic-imports a same-origin vendor path that does not resolve in Node => throws. + await assert.rejects( + () => loadOnnxRuntime(), + (err) => err instanceof ConversionError && err.code === OCR_VENDOR_LOAD_FAILED, + "loadOnnxRuntime should reject with OCR_VENDOR_LOAD_FAILED when vendor onnxruntime-web is absent (Node)", + ); + + // With vendor + models simulated ready, recognize reaches the runtime loader and surfaces + // the vendor-load failure (rather than the earlier vendor-not-ready / model-missing stages). + markPaddleOcrVendorReady(true); + for (const file of ["det.onnx", "cls.onnx", "rec.onnx"]) { + await paddleOcrEngine._storage.put(`paddleocr/v5/${file}`, new Uint8Array([1]).buffer, { sha256: "x" }); + } + try { + await assert.rejects( + () => paddleOcrEngine.recognize({ image: { width: 4, height: 4 } }), + (err) => err instanceof ConversionError && err.code === OCR_VENDOR_LOAD_FAILED, + "paddle recognize should reach loadOnnxRuntime and reject with OCR_VENDOR_LOAD_FAILED in Node", + ); + } finally { + for (const file of ["det.onnx", "cls.onnx", "rec.onnx"]) { + await paddleOcrEngine._storage.delete(`paddleocr/v5/${file}`); + } + markPaddleOcrVendorReady(false); + } +} + +// 37. PP-OCRv5 model import availability flip (P9-D.3): required det+rec present + vendor ready +// => isAvailable() true; cls is OPTIONAL (removing it stays ready); removing a required +// model (rec) => false. Mirrors security-center import/clear with cls optional. +{ + const det = "paddleocr/v5/det.onnx"; + const cls = "paddleocr/v5/cls.onnx"; + const rec = "paddleocr/v5/rec.onnx"; + markPaddleOcrVendorReady(true); + try { + // partial: det present but required rec missing => not ready (cls present but optional) + await paddleOcrEngine._storage.put(det, new Uint8Array([1]).buffer, { sha256: "a" }); + await paddleOcrEngine._storage.put(cls, new Uint8Array([2]).buffer, { sha256: "b" }); + assert.equal(await paddleOcrEngine.ensureProbe(), false, "det without required rec should not be ready"); + assert.equal(paddleOcrEngine.isAvailable(), false); + + // required det+rec present => ready + await paddleOcrEngine._storage.put(rec, new Uint8Array([3]).buffer, { sha256: "c" }); + assert.equal(await paddleOcrEngine.ensureProbe(), true, "required det+rec present => ready"); + assert.equal(paddleOcrEngine.isAvailable(), true); + + // vendor flag off => unavailable even with models + markPaddleOcrVendorReady(false); + assert.equal(paddleOcrEngine.isAvailable(), false, "vendor not ready => unavailable regardless of models"); + + // remove OPTIONAL cls => still ready (det+rec remain) + markPaddleOcrVendorReady(true); + await paddleOcrEngine._storage.delete(cls); + assert.equal(await paddleOcrEngine.ensureProbe(), true, "removing optional cls keeps readiness"); + + // remove a REQUIRED model (rec) => not ready + await paddleOcrEngine._storage.delete(rec); + assert.equal(await paddleOcrEngine.ensureProbe(), false, "removing required rec should drop readiness"); + } finally { + for (const key of [det, cls, rec]) await paddleOcrEngine._storage.delete(key); + markPaddleOcrVendorReady(false); + await paddleOcrEngine.ensureProbe(); + } +} + +// 38. Priority-aware pickForTask (P9-D.4): higher-priority available engine wins; PP-OCRv5 +// preferred over tesseract when both available. +{ + const reg = new OCREngineRegistry(); + const stub = (id, priority, available) => ({ + id, taskCapabilities: ["ocr-text"], priority, isAvailable: () => available, recognize: async () => ({}), + }); + reg.register(stub("low-pri", 5, true)); + reg.register(stub("high-pri", 20, true)); + reg.register(stub("mid-pri", 10, true)); + assert.equal(reg.pickForTask("ocr-text").id, "high-pri", "highest-priority available engine should win"); + + // Only a low-priority engine available => it is picked even if a higher-priority one is unavailable. + const reg2 = new OCREngineRegistry(); + reg2.register(stub("hi-unavail", 20, false)); + reg2.register(stub("lo-avail", 5, true)); + assert.equal(reg2.pickForTask("ocr-text").id, "lo-avail", "available lower-priority engine should win over unavailable higher-priority"); + + // Default registry: both tesseract + paddle available => paddle (priority 20) preferred. + markTesseractVendorReady(true); + await tesseractOCREngine._storage.put("tesseract/eng.traineddata", new Uint8Array([1]).buffer, { sha256: "x" }); + await tesseractOCREngine.ensureProbe(); + markPaddleOcrVendorReady(true); + for (const file of ["det.onnx", "cls.onnx", "rec.onnx"]) { + await paddleOcrEngine._storage.put(`paddleocr/v5/${file}`, new Uint8Array([1]).buffer, { sha256: "x" }); + } + await paddleOcrEngine.ensureProbe(); + try { + assert.equal(tesseractOCREngine.isAvailable(), true); + assert.equal(paddleOcrEngine.isAvailable(), true); + assert.equal(defaultOCRRegistry.pickForTask("ocr-text").id, "paddleocr-v5", "PP-OCRv5 should be preferred over tesseract when both available"); + + // Remove paddle models => tesseract wins. + for (const file of ["det.onnx", "cls.onnx", "rec.onnx"]) { + await paddleOcrEngine._storage.delete(`paddleocr/v5/${file}`); + } + await paddleOcrEngine.ensureProbe(); + assert.equal(defaultOCRRegistry.pickForTask("ocr-text").id, "tesseract-zh-en", "tesseract should win when paddle unavailable"); + } finally { + await tesseractOCREngine._storage.delete("tesseract/eng.traineddata"); + for (const file of ["det.onnx", "cls.onnx", "rec.onnx"]) { + await paddleOcrEngine._storage.delete(`paddleocr/v5/${file}`); + } + markTesseractVendorReady(false); + markPaddleOcrVendorReady(false); + await tesseractOCREngine.ensureProbe(); + await paddleOcrEngine.ensureProbe(); + } +} + +console.log("OCR baseline test passed: contracts, registry, bootstraps, storage, png reader/async stage, repair validator, scan PDF detection + rasterizer skeleton + multi-page OCR stage + FixedLayoutModel mapping + browser rasterizer fallback + PP-OCRv5 advanced engine skeleton + onnxruntime-web runtime loader + model import availability flip + priority-aware route preference all verified."); diff --git a/scripts/ocr-readback-test.js b/scripts/ocr-readback-test.js new file mode 100644 index 0000000..0b125d8 --- /dev/null +++ b/scripts/ocr-readback-test.js @@ -0,0 +1,183 @@ +import assert from "node:assert/strict"; + +import { + compareText, + normalizeText, + extractModelText, + runOcrReadbackLayer, + runVerificationStageAsync, + convertContentAsync, + OCR_READBACK_DRIFT, + DEFAULT_OCR_READBACK_THRESHOLD, +} from "../public/browser-transformer.js"; + +function stubEngine(fullText, { available = true, averageConfidence = 0.9 } = {}) { + return { + id: "stub-ocr", + taskCapabilities: ["ocr-text"], + isAvailable: () => available, + recognize: async () => ({ fullText, averageConfidence, pages: [] }), + }; +} + +function stubRasterizer({ throwCode = null } = {}) { + return { + async rasterize() { + if (throwCode) { + const error = new Error("stub rasterizer failure"); + error.code = throwCode; + throw error; + } + return { dataUrl: "data:image/png;base64,AAAA", width: 16, height: 16 }; + }, + async countPages() { return 1; }, + }; +} + +function model(blocks) { + return { + schemaVersion: "trans2former.document.v1", + title: "ocr-readback", + sourceFormat: "md", + blocks, + assets: [], + metadata: { warnings: [], qualityReport: {} }, + }; +} + +// 1. compareText identical -> all 1 +{ + const r = compareText("Hello World", "Hello World"); + assert.equal(r.recall, 1); + assert.equal(r.precision, 1); + assert.equal(r.f1, 1); +} + +// 2. compareText subset -> recall < 1, precision = 1 +{ + const r = compareText("Hello World", "Hello"); + assert.ok(r.recall < 1, "recall should drop when text missing"); + assert.equal(r.precision, 1); + assert.ok(r.f1 < 1 && r.f1 > 0); +} + +// 3. compareText CJK (char-level multiset works without spaces) +{ + const r = compareText("你好世界", "你好世"); + assert.equal(r.recall, 0.75); + assert.equal(r.precision, 1); +} + +// 4. compareText empty original + empty recognized -> 1; empty original + text -> precision 0 +{ + assert.equal(compareText("", "").f1, 1); + const r = compareText("", "noise"); + assert.equal(r.precision, 0); +} + +// 5. normalizeText strips whitespace + lowercases +{ + assert.equal(normalizeText(" He llo\nWORLD "), "helloworld"); +} + +// 6. extractModelText joins block text incl. list/table +{ + const text = extractModelText(model([ + { type: "heading", text: "Title" }, + { type: "paragraph", text: "Body" }, + { type: "list", ordered: false, items: ["a", "b"] }, + { type: "table", headers: ["h1"], rows: [["c1"]] }, + ])); + assert.ok(text.includes("Title") && text.includes("Body") && text.includes("a") && text.includes("c1")); +} + +// 7. runOcrReadbackLayer happy path with stub engine + rasterizer +{ + const layer = await runOcrReadbackLayer({ + model: model([{ type: "heading", text: "Title" }, { type: "paragraph", text: "Body" }]), + output: { data: "" }, + ctx: { from: "md", to: "pdf", options: {} }, + engine: stubEngine("Title Body"), + rasterizer: stubRasterizer(), + }); + assert.equal(layer.eligible, true); + assert.equal(layer.ocrReadback.passed, true); + assert.equal(layer.ocrReadback.engineId, "stub-ocr"); + assert.ok(layer.ocrReadback.f1 >= DEFAULT_OCR_READBACK_THRESHOLD); +} + +// 8. runOcrReadbackLayer drift -> OCR_READBACK_DRIFT warning +{ + const layer = await runOcrReadbackLayer({ + model: model([{ type: "paragraph", text: "The quick brown fox jumps over the lazy dog" }]), + output: { data: "" }, + ctx: { from: "md", to: "pdf", options: {} }, + engine: stubEngine("zzzzz"), + rasterizer: stubRasterizer(), + }); + assert.equal(layer.eligible, true); + assert.equal(layer.ocrReadback.passed, false); + assert.equal(layer.warnings[0].code, OCR_READBACK_DRIFT); +} + +// 9. not eligible: non-pdf output +{ + const layer = await runOcrReadbackLayer({ + model: model([{ type: "paragraph", text: "x" }]), + output: { data: "text" }, + ctx: { from: "md", to: "md", options: {} }, + engine: stubEngine("x"), + rasterizer: stubRasterizer(), + }); + assert.equal(layer.eligible, false); + assert.equal(layer.reason, "output-not-rasterizable-for-ocr"); +} + +// 10. not eligible: engine unavailable (via registry returning null) +{ + const layer = await runOcrReadbackLayer({ + model: model([{ type: "paragraph", text: "x" }]), + output: { data: "" }, + ctx: { from: "md", to: "pdf", options: {} }, + engine: null, + registry: { pickForTask: () => null }, + rasterizer: stubRasterizer(), + }); + assert.equal(layer.eligible, false); + assert.equal(layer.reason, "ocr-engine-unavailable"); +} + +// 11. rasterizer unavailable -> reason rasterizer-unavailable (no throw) +{ + const layer = await runOcrReadbackLayer({ + model: model([{ type: "paragraph", text: "x" }]), + output: { data: "" }, + ctx: { from: "md", to: "pdf", options: {} }, + engine: stubEngine("x"), + rasterizer: stubRasterizer({ throwCode: "OCR_RASTERIZER_UNAVAILABLE" }), + }); + assert.equal(layer.eligible, false); + assert.equal(layer.reason, "rasterizer-unavailable"); +} + +// 12. runVerificationStageAsync merges three layers; default (no stub) ocr-readback skipped +{ + const env = await runVerificationStageAsync({ + model: model([{ type: "paragraph", text: "Body" }]), + output: { data: "" }, + ctx: { from: "md", to: "pdf", content: "Body", read: () => model([{ type: "paragraph", text: "Body" }]), options: {} }, + }); + // md->pdf: rule-diff skipped (pdf not text-canonical), ssim skipped (md not rasterizable), + // ocr-readback skipped in Node (no engine available) + assert.ok(env.skipped.some((s) => s.layer === "ocr-readback")); + assert.equal(env.ocrReadback, null); +} + +// 13. End-to-end convertContentAsync md->md: ocrReadback null (sync-like text path) +{ + const result = await convertContentAsync({ content: "# Title\n\nBody", from: "md", to: "md", title: "e2e" }); + assert.equal(result.quality.qualityReport.ocrReadback, null); + assert.equal(result.quality.qualityReport.ruleDiff.identical, true); +} + +console.log("OCR readback test passed: compareText (identical/subset/CJK/empty), normalizeText, extractModelText, readback layer gating/drift/unavailable/rasterizer-fail, async three-layer merge, end-to-end null-on-text covered."); diff --git a/scripts/ocr-structure-test.js b/scripts/ocr-structure-test.js new file mode 100644 index 0000000..509a411 --- /dev/null +++ b/scripts/ocr-structure-test.js @@ -0,0 +1,74 @@ +import assert from "node:assert/strict"; + +import { deriveOcrStructure, blocksFromOcrResult } from "../public/browser-transformer.js"; + +const line = (text, x, y, w, h) => ({ text, bbox: { x, y, w, h } }); + +// 1. Larger-font line becomes a heading; body lines group into a paragraph +{ + const lines = [ + line("产品标题", 10, 10, 200, 40), // tall => heading + line("第一行正文", 10, 60, 200, 18), + line("第二行正文", 10, 82, 200, 18), + ]; + const blocks = deriveOcrStructure(lines); + assert.equal(blocks[0].type, "heading"); + assert.equal(blocks[0].text, "产品标题"); + assert.ok(blocks[0].level >= 1 && blocks[0].level <= 6); + // the two close body lines merge into one paragraph + const paras = blocks.filter((b) => b.type === "paragraph"); + assert.equal(paras.length, 1); + assert.ok(paras[0].text.includes("第一行正文") && paras[0].text.includes("第二行正文")); +} + +// 2. A large vertical gap splits paragraphs +{ + const lines = [ + line("段落一行一", 10, 10, 200, 18), + line("段落一行二", 10, 30, 200, 18), + line("段落二行一", 10, 200, 200, 18), // big gap => new paragraph + ]; + const blocks = deriveOcrStructure(lines); + assert.equal(blocks.filter((b) => b.type === "paragraph").length, 2, "large gap should split into two paragraphs"); +} + +// 3. CJK lines join without spaces; latin lines join with a space +{ + const cjk = deriveOcrStructure([line("你好", 0, 0, 50, 18), line("世界", 0, 20, 50, 18)]); + assert.equal(cjk[0].text, "你好世界", "adjacent CJK lines should join without a space"); + const latin = deriveOcrStructure([line("hello", 0, 0, 50, 18), line("world", 0, 20, 50, 18)]); + assert.equal(latin[0].text, "hello world", "latin lines should join with a space"); +} + +// 4. Reading order: out-of-order (but close) lines are sorted top->bottom before joining +{ + const blocks = deriveOcrStructure([ + line("下面", 0, 28, 50, 18), + line("上面", 0, 6, 50, 18), + ]); + assert.equal(blocks[0].text, "上面下面"); +} + +// 5. No-geometry fallback: lines without bbox collapse to a single paragraph (legacy behavior) +{ + const blocks = deriveOcrStructure([{ text: "a" }, { text: "b" }]); + assert.equal(blocks.length, 1); + assert.equal(blocks[0].type, "paragraph"); + assert.equal(blocks[0].text, "a\nb"); +} + +// 6. blocksFromOcrResult walks pages; empty falls back to fullText +{ + const result = { pages: [{ lines: [line("标题大字", 0, 0, 100, 40), line("正文", 0, 50, 100, 16)] }] }; + const blocks = blocksFromOcrResult(result); + assert.ok(blocks.some((b) => b.type === "heading")); + assert.equal(blocksFromOcrResult({ pages: [], fullText: "only text" })[0].text, "only text"); + assert.equal(blocksFromOcrResult({ pages: [] }).length, 0); +} + +// 7. Empty / whitespace lines are ignored +{ + assert.equal(deriveOcrStructure([{ text: " ", bbox: { x: 0, y: 0, w: 1, h: 1 } }]).length, 0); +} + +console.log("OCR structure test passed: heading detection by font size, paragraph grouping by vertical gap, CJK/latin line joining, reading-order sort, no-geometry fallback, and blocksFromOcrResult page walk verified."); diff --git a/scripts/paddle-ocr-integration-test.js b/scripts/paddle-ocr-integration-test.js new file mode 100644 index 0000000..ff8b1e4 --- /dev/null +++ b/scripts/paddle-ocr-integration-test.js @@ -0,0 +1,61 @@ +// 真实 PP-OCRv5 ONNX 集成测试：用 onnxruntime-node 在 Node 端跑真实 rec 模型，验证 +// 整条识别管线（预处理 + CTC + 字典）对真实模型确实正确。 +// +// 依赖 onnxruntime-node + pngjs（重型/原生，非项目运行时依赖）+ 本地 vendor 模型 + +// 字典 + 词图 fixture。任一缺失则**优雅跳过**（exit 0），所以默认 `npm test` 在未安装 +// 这些开发依赖 / 未下载模型的环境下不会失败。 +// +// 本机启用：npm i -D onnxruntime-node pngjs && npm run vendor:onnx + 下载 PP-OCRv5 模型。 + +import assert from "node:assert/strict"; +import { readFileSync, existsSync } from "node:fs"; +import { createRequire } from "node:module"; + +const require = createRequire(import.meta.url); + +function tryRequire(name) { + try { return require(name); } catch { return null; } +} + +const ort = tryRequire("onnxruntime-node"); +const pngjs = tryRequire("pngjs"); +const REC = "public/vendor/paddleocr/rec.onnx"; +const DICT = "public/vendor/paddleocr/dict.txt"; +const FIXTURE = "samples/ocr/word-PAIN.png"; + +if (!ort || !pngjs) { + console.log("PP-OCRv5 integration test skipped: onnxruntime-node / pngjs not installed (dev-only). Install with `npm i -D onnxruntime-node pngjs`."); + process.exit(0); +} +if (!existsSync(REC) || !existsSync(DICT)) { + console.log("PP-OCRv5 integration test skipped: vendor models absent. Run `npm run vendor:onnx` + download PP-OCRv5 ONNX into public/vendor/paddleocr/."); + process.exit(0); +} +if (!existsSync(FIXTURE)) { + console.log(`PP-OCRv5 integration test skipped: fixture ${FIXTURE} missing.`); + process.exit(0); +} + +const P = await import("../public/core/ocr/paddle-ocr-pipeline.js"); + +const png = pngjs.PNG.sync.read(readFileSync(FIXTURE)); +const img = { data: new Uint8ClampedArray(png.data), width: png.width, height: png.height }; +const dict = P.parseCharDictionary(readFileSync(DICT, "utf8")); + +const rec = await ort.InferenceSession.create(REC); +const pre = P.preprocessForRecognition(img, {}); +const out = await rec.run({ [rec.inputNames[0]]: new ort.Tensor("float32", pre.data, pre.dims) }); +const o = out[rec.outputNames[0]]; +const C = o.dims[o.dims.length - 1]; +const T = o.dims[o.dims.length - 2]; + +// rec 输出类别数必须等于字典长度（blank + chars + space），否则对齐错位。 +assert.equal(C, dict.length, `rec output classes (${C}) must equal dictionary length (${dict.length})`); + +const decoded = P.ctcGreedyDecode(o.data, T, C, dict); +const text = decoded.text.toUpperCase().replace(/\s+/g, ""); +// fixture word-PAIN.png 的 ground-truth 是 "PAIN" +assert.equal(text, "PAIN", `expected rec to read "PAIN", got "${decoded.text}"`); +assert.ok(decoded.confidence > 0.8, `expected high confidence, got ${decoded.confidence}`); + +console.log(`PP-OCRv5 integration test passed: real rec model decodes fixture -> "${decoded.text}" (conf ${decoded.confidence.toFixed(3)}, C=${C} matches dict).`); diff --git a/scripts/paddle-ocr-pipeline-test.js b/scripts/paddle-ocr-pipeline-test.js new file mode 100644 index 0000000..c41d0de --- /dev/null +++ b/scripts/paddle-ocr-pipeline-test.js @@ -0,0 +1,327 @@ +import assert from "node:assert/strict"; + +import { + parseCharDictionary, + preprocessForDetection, + preprocessForRecognition, + dbPostProcess, + ctcGreedyDecode, + cropImageData, + resizeRgba, + rotateImageData90, + rotateImageData180, + rotateImageDataByAngle, + estimateSkewAngle, + interpretClsOutput, + denoiseImageData, + estimateNoiseLevel, + runPaddlePipeline, + DET_LIMIT_SIDE_LEN, + REC_IMAGE_HEIGHT, +} from "../public/browser-transformer.js"; + +function solidRgba(value, width, height) { + const data = new Uint8ClampedArray(width * height * 4); + for (let i = 0; i < width * height; i += 1) { + data[i * 4] = value; + data[i * 4 + 1] = value; + data[i * 4 + 2] = value; + data[i * 4 + 3] = 255; + } + return { data, width, height }; +} + +// Mock onnxruntime namespace + sessions for end-to-end orchestration without real models. +const mockOrt = { Tensor: class { constructor(type, data, dims) { this.type = type; this.data = data; this.dims = dims; } } }; + +function mockSession(outputName, produce) { + return { + inputNames: ["x"], + outputNames: [outputName], + run: async (feeds) => ({ [outputName]: produce(feeds.x) }), + }; +} + +// 1. parseCharDictionary: blank at 0, lines preserved, trailing space appended +{ + const dict = parseCharDictionary("你\n好\nA"); + assert.deepEqual(dict, ["", "你", "好", "A", " "]); + assert.deepEqual(parseCharDictionary(""), ["", " "]); + // 字典文件已显式以空格行结尾（如 ppu ppocrv5_dict）→ 不重复追加，避免类别数比模型多 1。 + assert.deepEqual(parseCharDictionary("你\n好\n "), ["", "你", "好", " "]); + // 全角空格 U+3000 是合法 token，必须保留（不可用 trim() 误删）。 + assert.deepEqual(parseCharDictionary("　\nA"), ["", "　", "A", " "]); +} + +// 2. preprocessForDetection: NCHW float, dims multiple of 32, scale ratios +{ + const det = preprocessForDetection(solidRgba(255, 20, 10)); + assert.equal(det.dims[0], 1); + assert.equal(det.dims[1], 3); + assert.equal(det.dims[2] % 32, 0); + assert.equal(det.dims[3] % 32, 0); + assert.equal(det.data.length, 3 * det.dims[2] * det.dims[3]); + assert.ok(det.scaleW > 0 && det.scaleH > 0); + // limit side len respected + const big = preprocessForDetection(solidRgba(0, 4000, 100)); + assert.ok(big.resizedWidth <= DET_LIMIT_SIDE_LEN + 32); +} + +// 3. preprocessForRecognition: fixed height 48, normalized to [-1,1] +{ + const rec = preprocessForRecognition(solidRgba(255, 100, 32)); + assert.equal(rec.dims[2], REC_IMAGE_HEIGHT); + assert.equal(rec.height, REC_IMAGE_HEIGHT); + // white pixel -> (255/255 - 0.5)/0.5 = 1 + assert.ok(Math.abs(rec.data[0] - 1) < 1e-6); +} + +// 4. resizeRgba + cropImageData +{ + const img = solidRgba(120, 10, 10); + const small = resizeRgba(img, 5, 5); + assert.equal(small.width, 5); + assert.equal(small.data.length, 5 * 5 * 4); + const crop = cropImageData(img, { x: 2, y: 2, w: 4, h: 4 }); + assert.equal(crop.width, 4); + assert.equal(crop.height, 4); + // crop clamps when out of range + const clamped = cropImageData(img, { x: 8, y: 8, w: 10, h: 10 }); + assert.ok(clamped.width <= 2 && clamped.height <= 2); +} + +// 5. dbPostProcess: connected component => one box; sub-threshold => none +{ + const prob = new Float32Array(36).fill(0); // 6x6 + // hot 3x3 block at (1,1)-(3,3) + for (let y = 1; y <= 3; y += 1) for (let x = 1; x <= 3; x += 1) prob[y * 6 + x] = 0.9; + // unclipRatio:0 关闭外扩，校验连通域 bbox 精确坐标 + const boxes = dbPostProcess(prob, 6, 6, { thresh: 0.3, boxThresh: 0.5, minSize: 2, unclipRatio: 0, scaleW: 1, scaleH: 1 }); + assert.equal(boxes.length, 1); + assert.equal(boxes[0].x, 1); + assert.equal(boxes[0].y, 1); + assert.equal(boxes[0].w, 3); + assert.equal(boxes[0].h, 3); + + // 默认 unclip>0 时框应向外扩（覆盖原 bbox 且更大），不切字符 + const unclipped = dbPostProcess(prob, 6, 6, { thresh: 0.3, boxThresh: 0.5, minSize: 2, scaleW: 1, scaleH: 1 }); + assert.equal(unclipped.length, 1); + assert.ok(unclipped[0].w >= 3 && unclipped[0].h >= 3, "unclip should not shrink the box"); + assert.ok(unclipped[0].x <= 1 && unclipped[0].y <= 1, "unclip should expand the box outward"); + + const none = dbPostProcess(new Float32Array(36).fill(0.1), 6, 6, { thresh: 0.3 }); + assert.equal(none.length, 0); +} + +// 6. dbPostProcess two separate blocks => two boxes sorted top->bottom +{ + const prob = new Float32Array(64).fill(0); // 8x8 + for (let y = 0; y <= 2; y += 1) for (let x = 0; x <= 2; x += 1) prob[y * 8 + x] = 0.8; // top-left + for (let y = 5; y <= 7; y += 1) for (let x = 5; x <= 7; x += 1) prob[y * 8 + x] = 0.8; // bottom-right + const boxes = dbPostProcess(prob, 8, 8, { thresh: 0.3, boxThresh: 0.5, minSize: 2, scaleW: 1, scaleH: 1 }); + assert.equal(boxes.length, 2); + assert.ok(boxes[0].y <= boxes[1].y, "boxes should be sorted top-to-bottom"); +} + +// 7. ctcGreedyDecode: collapse repeats + drop blank(0) +{ + const dict = ["", "a", "b", "c"]; + // T=5, C=4; argmax sequence: a,a,blank,b,c -> "abc" + const logits = new Float32Array([ + 0, 9, 0, 0, + 0, 9, 0, 0, + 9, 0, 0, 0, + 0, 0, 9, 0, + 0, 0, 0, 9, + ]); + const { text, confidence } = ctcGreedyDecode(logits, 5, 4, dict); + assert.equal(text, "abc"); + assert.ok(confidence > 0); + // all blank => empty + const blank = new Float32Array([9, 0, 0, 0, 9, 0, 0, 0]); + assert.equal(ctcGreedyDecode(blank, 2, 4, dict).text, ""); +} + +// 8. runPaddlePipeline end-to-end with mock ort + mock sessions => OCRResult with decoded text +{ + const dict = ["", "H", "I"]; + // det produces a prob map (same size as resized det input) with a hot block. + const detSession = mockSession("det_out", (tensor) => { + const [, , H, W] = tensor.dims; + const data = new Float32Array(H * W).fill(0); + // hot region in the middle covering >= minSize + for (let y = Math.floor(H / 2) - 4; y < Math.floor(H / 2) + 4; y += 1) { + for (let x = Math.floor(W / 2) - 4; x < Math.floor(W / 2) + 4; x += 1) { + if (y >= 0 && y < H && x >= 0 && x < W) data[y * W + x] = 0.9; + } + } + return { data, dims: [1, 1, H, W] }; + }); + const clsSession = mockSession("cls_out", () => ({ data: new Float32Array([0.9, 0.1]), dims: [1, 2] })); + // rec produces logits decoding to "HI": T=3, C=3 -> H, I, blank + const recSession = mockSession("rec_out", () => ({ + data: new Float32Array([0, 9, 0, 0, 0, 9, 9, 0, 0]), + dims: [1, 3, 3], + })); + + const imageData = solidRgba(200, 64, 64); + const result = await runPaddlePipeline({ + ort: mockOrt, + detSession, + clsSession, + recSession, + imageData, + dictionary: dict, + options: { db: { thresh: 0.3, boxThresh: 0.5, minSize: 2 } }, + }); + assert.equal(result.schemaVersion, "trans2former.ocr-result.v1"); + assert.equal(result.engine, "paddleocr-v5"); + assert.ok(result.pages[0].lines.length >= 1, "pipeline should produce at least one recognized line"); + assert.equal(result.pages[0].lines[0].text, "HI"); + assert.ok(result.fullText.includes("HI")); + assert.ok(result.averageConfidence > 0); +} + +// 9. runPaddlePipeline validates ort + sessions +{ + await assert.rejects( + () => runPaddlePipeline({ ort: null, detSession: {}, recSession: {}, imageData: solidRgba(0, 4, 4) }), + (err) => err.code === "OCR_ENGINE_INVALID", + ); +} + +// 10. Rotation helpers: 180 is an involution; 90 swaps dims; corners map correctly +{ + // 2x3 image with a distinct top-left red pixel + const w = 2, h = 3; + const data = new Uint8ClampedArray(w * h * 4); + const setPx = (img, x, y, r) => { const o = (y * img.width + x) * 4; img.data[o] = r; img.data[o + 3] = 255; }; + const img = { data, width: w, height: h }; + setPx(img, 0, 0, 200); // mark top-left + + const r180 = rotateImageData180(img); + assert.equal(r180.width, w); + assert.equal(r180.height, h); + // top-left should now be at bottom-right + assert.equal(r180.data[((h - 1) * w + (w - 1)) * 4], 200); + // 180 is its own inverse + const back = rotateImageData180(r180); + assert.deepEqual(Array.from(back.data), Array.from(img.data)); + + const cw = rotateImageData90(img, "cw"); + assert.equal(cw.width, h); // dims swapped + assert.equal(cw.height, w); + // top-left (0,0) under CW goes to (height-1, 0) = (2,0) + assert.equal(cw.data[(0 * cw.width + (h - 1)) * 4], 200); + const ccw = rotateImageData90(img, "ccw"); + assert.equal(ccw.width, h); + assert.equal(ccw.height, w); +} + +// 11. interpretClsOutput: c1 high => flip; c0 high => no flip; below threshold => no flip +{ + assert.equal(interpretClsOutput([0.05, 0.95], 0.6).flip, true); + assert.equal(interpretClsOutput([0.95, 0.05], 0.6).flip, false); + assert.equal(interpretClsOutput([0.45, 0.55], 0.6).flip, false, "below threshold should not flip"); + assert.equal(interpretClsOutput([0.1, 0.9]).confidence, 0.9); +} + +// 12. runPaddlePipeline returns a quality assessment (grade + confidence stats) +{ + const dict = ["", "H", "I"]; + const detSession = mockSession("det_out", (tensor) => { + const [, , H, W] = tensor.dims; + const data = new Float32Array(H * W).fill(0); + for (let y = Math.floor(H / 2) - 4; y < Math.floor(H / 2) + 4; y += 1) + for (let x = Math.floor(W / 2) - 4; x < Math.floor(W / 2) + 4; x += 1) + if (y >= 0 && y < H && x >= 0 && x < W) data[y * W + x] = 0.9; + return { data, dims: [1, 1, H, W] }; + }); + const recSession = mockSession("rec_out", () => ({ data: new Float32Array([0, 9, 0, 0, 0, 9, 9, 0, 0]), dims: [1, 3, 3] })); + const result = await runPaddlePipeline({ + ort: mockOrt, detSession, recSession, imageData: solidRgba(200, 64, 64), dictionary: dict, + options: { db: { thresh: 0.3, boxThresh: 0.5, minSize: 2 } }, + }); + assert.ok(result.quality, "pipeline should attach a quality assessment"); + assert.equal(typeof result.quality.averageConfidence, "number"); + assert.equal(typeof result.quality.minConfidence, "number"); + assert.ok(["high", "medium", "low"].includes(result.quality.grade)); + assert.equal(result.quality.lineCount, result.pages[0].lines.length); +} + +// 13. estimateNoiseLevel: clean ~0; salt-and-pepper => high. denoiseImageData removes speckle. +{ + const w = 32, h = 32; + const clean = solidRgba(128, w, h); + assert.ok(estimateNoiseLevel(clean) < 0.02, "uniform image should have near-zero noise estimate"); + + // sprinkle salt-and-pepper + const noisy = { data: new Uint8ClampedArray(clean.data), width: w, height: h }; + let seed = 7; + const rnd = () => { seed = (seed * 1103515245 + 12345) & 0x7fffffff; return seed / 0x7fffffff; }; + for (let i = 0; i < w * h; i += 1) { + if (rnd() < 0.15) { const v = rnd() < 0.5 ? 0 : 255; noisy.data[i * 4] = v; noisy.data[i * 4 + 1] = v; noisy.data[i * 4 + 2] = v; } + } + assert.ok(estimateNoiseLevel(noisy) > 0.05, "salt-and-pepper image should exceed denoise threshold"); + + // median denoise reduces the speckle measure + const cleaned = denoiseImageData(noisy); + assert.equal(cleaned.width, w); + assert.ok(estimateNoiseLevel(cleaned) < estimateNoiseLevel(noisy), "denoise should reduce the noise estimate"); +} + +// 14. auto-denoise gating: clean stays untouched; quality reports denoised flag +{ + const dict = ["", "H", "I"]; + const detSession = mockSession("det_out", (tensor) => { + const [, , H, W] = tensor.dims; + const data = new Float32Array(H * W).fill(0); + for (let y = Math.floor(H / 2) - 4; y < Math.floor(H / 2) + 4; y += 1) + for (let x = Math.floor(W / 2) - 4; x < Math.floor(W / 2) + 4; x += 1) + if (y >= 0 && y < H && x >= 0 && x < W) data[y * W + x] = 0.9; + return { data, dims: [1, 1, H, W] }; + }); + const recSession = mockSession("rec_out", () => ({ data: new Float32Array([0, 9, 0, 0, 0, 9, 9, 0, 0]), dims: [1, 3, 3] })); + const r = await runPaddlePipeline({ + ort: mockOrt, detSession, recSession, imageData: solidRgba(200, 64, 64), dictionary: dict, + options: { db: { thresh: 0.3, boxThresh: 0.5, minSize: 2 } }, + }); + assert.equal(r.quality.denoised, false, "clean uniform image should not be denoised"); + assert.equal(typeof r.quality.noiseLevel, "number"); +} + +// 15. rotateImageDataByAngle: 0deg is identity-ish; expands canvas for non-zero angles +{ + const img = solidRgba(120, 10, 8); + const same = rotateImageDataByAngle(img, 0); + assert.equal(same.width, 10); + assert.equal(same.height, 8); + const rot = rotateImageDataByAngle(img, 30); + assert.ok(rot.width >= 10 && rot.height >= 8, "rotation should expand the canvas"); + assert.equal(rot.data.length, rot.width * rot.height * 4); +} + +// 16. estimateSkewAngle: a synthetic horizontal-lines prob map skewed by +A is detected ~A +{ + const W = 120, H = 120; + // build a prob map with horizontal text rows, then shear it by angle A + const A = 8; + const t = Math.tan((A * Math.PI) / 180); + const prob = new Float32Array(W * H).fill(0); + for (let row = 20; row < H; row += 20) { + for (let x = 10; x < W - 10; x += 1) { + const y = Math.round(row + x * t); // shear -> slanted rows + if (y >= 0 && y < H) prob[y * W + x] = 1; + } + } + const est = estimateSkewAngle(prob, W, H, { maxAngle: 15, step: 1, thresh: 0.3 }); + assert.ok(Math.abs(est) >= 3, `should detect a non-trivial skew, got ${est}`); + assert.ok(Math.sign(est) === Math.sign(A) || est === A || Math.abs(est - A) <= 3, `skew estimate ${est} should be near +${A}`); + + // flat horizontal rows => ~0 skew + const flat = new Float32Array(W * H).fill(0); + for (let row = 20; row < H; row += 20) for (let x = 10; x < W - 10; x += 1) flat[row * W + x] = 1; + assert.ok(Math.abs(estimateSkewAngle(flat, W, H, { maxAngle: 15 })) <= 2, "flat rows should estimate ~0 skew"); +} + +console.log("PP-OCRv5 pipeline test passed: dictionary, det/rec preprocessing, resize/crop, DB postprocess + unclip, CTC greedy decode, rotation helpers + cls interpretation, denoise (noise estimate + median + auto-gating), skew estimation + arbitrary rotation, quality assessment, and mock-session end-to-end runPaddlePipeline verified."); diff --git a/scripts/paddleocr-models.manifest.json b/scripts/paddleocr-models.manifest.json new file mode 100644 index 0000000..0b098aa --- /dev/null +++ b/scripts/paddleocr-models.manifest.json @@ -0,0 +1,34 @@ +{ + "source": { + "repo": "PT-Perkasa-Pilar-Utama/ppu-paddle-ocr-models", + "commit": "3a180da5b1a3bab3371d970f4da42cb9b354a9a7", + "license": "Apache-2.0", + "note": "PP-OCRv5 mobile ONNX (onnx sourced from paddleocr.ai). Direction classifier (cls.onnx) is optional and intentionally NOT bundled; users may import their own via the security center." + }, + "files": [ + { + "target": "det.onnx", + "kind": "lfs", + "remotePath": "detection/PP-OCRv5_mobile_det_infer.onnx", + "required": true, + "size": 4748769, + "sha256": "d7fe3ea74652890722c0f4d02458b7261d9f5ae6c92904d05707c9eb155c7924" + }, + { + "target": "rec.onnx", + "kind": "lfs", + "remotePath": "recognition/PP-OCRv5_mobile_rec_infer.onnx", + "required": true, + "size": 16559278, + "sha256": "d253c3cbee6e507828a5271a30ab0ec8ae7c2a99d0cc8e6f844fe380809d22b3" + }, + { + "target": "dict.txt", + "kind": "raw", + "remotePath": "recognition/ppocrv5_dict.txt", + "required": true, + "size": 74014, + "sha256": "9dfc80c50b6cb07399a47a7cf25d11db475fb4ad0e1fc96b2eff6467c8166ff3" + } + ] +} diff --git a/scripts/release-readiness-test.js b/scripts/release-readiness-test.js index f493878..a7a001d 100644 --- a/scripts/release-readiness-test.js +++ b/scripts/release-readiness-test.js @@ -41,8 +41,10 @@ for (const file of REQUIRED_FILES) { const packageJson = JSON.parse(await readFile("package.json", "utf8")); assert.equal(packageJson.scripts["vendor:pdfjs"], "node scripts/sync-pdfjs-vendor.js"); -assert.equal(packageJson.scripts["release:prepare"], "node scripts/sync-pdfjs-vendor.js && node scripts/sync-tesseract-vendor.js && node scripts/prepare-release.js"); +assert.equal(packageJson.scripts["release:prepare"], "node scripts/sync-pdfjs-vendor.js && node scripts/sync-tesseract-vendor.js && node scripts/sync-onnxruntime-vendor.js && node scripts/sync-paddleocr-vendor.js && node scripts/prepare-release.js"); assert.equal(packageJson.scripts["vendor:tesseract"], "node scripts/sync-tesseract-vendor.js"); +assert.equal(packageJson.scripts["vendor:onnx"], "node scripts/sync-onnxruntime-vendor.js"); +assert.equal(packageJson.scripts["vendor:paddle"], "node scripts/sync-paddleocr-vendor.js"); const releasePrep = await readFile("docs/RELEASE_PREP.md", "utf8"); for (const requiredText of [ diff --git a/scripts/resource-budget-test.js b/scripts/resource-budget-test.js index a997699..8927686 100644 --- a/scripts/resource-budget-test.js +++ b/scripts/resource-budget-test.js @@ -3,14 +3,19 @@ import { readFile, readdir, stat } from "node:fs/promises"; import path from "node:path"; const BUDGETS = [ - { path: "public/core", maxBytes: 256 * 1024 }, + // public/core 是纯 JS 算法核心（转换/路由/Repair/三层检验/OCR 前后处理管线）， + // 不含任何模型权重——模型只进 model-cache、按需导入。P9-C 三层检验 + P9-D PP-OCRv5 + // 推理管线（DB 后处理 + CTC 解码等纯函数）合理扩容到 320KB，仍远小于任何带权重方案。 + { path: "public/core", maxBytes: 320 * 1024 }, { path: "public/formats", maxBytes: 512 * 1024 }, { path: "public/workers", maxBytes: 128 * 1024 }, { path: "scripts", maxBytes: 512 * 1024 }, { path: "public", maxBytes: 2 * 1024 * 1024, exclude: ["public/vendor"] }, - // vendored PDF.js（main + worker + cmaps + standard_fonts）属于按需的可选引擎， - // 不应挤占核心主预算，但本身仍要有上限避免漂移。 - { path: "public/vendor", maxBytes: 6 * 1024 * 1024 }, + // vendored 引擎/模型属于按需的可选资源，不挤占核心主预算，但仍设上限防漂移。 + // 含：pdfjs(~4MB) + onnxruntime-web 最小 JSEP 构建(~25MB) + tesseract.js core 全 SIMD/LSTM + // 变体(~30MB) + PP-OCRv5 mobile det/rec + 字典(~21MB) + KaTeX(~1MB) ≈ 80MB。这些不入 git + // （见 .gitignore），由 vendor 脚本 + 本地下载重建，随应用打包。上限留约 20% 余量防漂移。 + { path: "public/vendor", maxBytes: 96 * 1024 * 1024 }, ]; const FORBIDDEN_DEPENDENCIES = [ diff --git a/scripts/rule-diff-test.js b/scripts/rule-diff-test.js new file mode 100644 index 0000000..9e2c3e4 --- /dev/null +++ b/scripts/rule-diff-test.js @@ -0,0 +1,201 @@ +import assert from "node:assert/strict"; + +import { + convertContent, + diffSemanticDocs, + runVerificationStage, + blockFingerprint, + modelFingerprint, + ROUND_TRIP_FORMATS, + RULE_DIFF_DRIFT, + RULE_DIFF_READBACK_FAILED, +} from "../public/browser-transformer.js"; + +function block(overrides = {}) { + return { + id: overrides.id, + type: "paragraph", + text: "Hello world", + warnings: [], + sourceSpan: { startLine: null, endLine: null, startOffset: null, endOffset: null }, + ...overrides, + }; +} + +function model(blocks) { + return { + schemaVersion: "trans2former.document.v1", + title: "diff-test", + sourceFormat: "md", + blocks, + assets: [], + metadata: { warnings: [], qualityReport: {} }, + }; +} + +// Reference implementation of the legacy fingerprint, kept for byte-level equivalence check. +function legacyBlockFingerprint(b) { + if (!b || typeof b !== "object") return ""; + if (b.type === "heading") return `h${b.level}|${b.text || ""}`; + if (b.type === "paragraph" || b.type === "quote") return `${b.type}|${b.text || ""}`; + if (b.type === "code") return `code|${b.language || ""}|${b.code || ""}`; + if (b.type === "list") return `list|${b.ordered ? "ol" : "ul"}|${(b.items || []).join("")}`; + if (b.type === "table") { + return `table|${(b.headers || []).join("")}|${(b.rows || []).map((row) => (row || []).join("")).join("")}`; + } + if (b.type === "image" || b.type === "asset") { + return `${b.type}|${b.src || ""}|${b.alt || ""}|${b.assetId || ""}`; + } + if (b.type === "raw") return `raw|${b.format || ""}|${b.content || ""}`; + return b.type || ""; +} + +// 1. Identical models → exact / score 1 +{ + const original = model([block({ id: "b1" }), block({ id: "b2", type: "heading", level: 1, text: "Title" })]); + const readBack = model([block({ id: "b1" }), block({ id: "b2", type: "heading", level: 1, text: "Title" })]); + const diff = diffSemanticDocs(original, readBack); + assert.equal(diff.identical, true); + assert.equal(diff.fidelity, "exact"); + assert.equal(diff.overallScore, 1); + assert.equal(diff.changedBlocks.length, 0); + assert.equal(diff.addedBlocks.length, 0); + assert.equal(diff.removedBlocks.length, 0); +} + +// 2. Whitespace/punct-only text delta → minor-drift, severity minor +{ + const original = model([block({ id: "b1", text: "Hello, world!" })]); + const readBack = model([block({ id: "b1", text: "Hello world" })]); + const diff = diffSemanticDocs(original, readBack); + assert.equal(diff.fidelity, "minor-drift"); + assert.equal(diff.changedBlocks.length, 1); + assert.deepEqual(diff.changedBlocks[0].fieldsDiffered.map((f) => f.field), ["text"]); + assert.equal(diff.changedBlocks[0].severity, "minor"); +} + +// 2b. Substantive text change → major (text field semantic change) +{ + const original = model([block({ id: "b1", text: "The quick brown fox" })]); + const readBack = model([block({ id: "b1", text: "Totally different sentence here" })]); + const diff = diffSemanticDocs(original, readBack); + assert.equal(diff.changedBlocks[0].severity, "major"); + assert.equal(diff.fidelity, "major-drift"); +} + +// 3. Heading level change → major-drift +{ + const original = model([block({ id: "h", type: "heading", level: 1, text: "Same" })]); + const readBack = model([block({ id: "h", type: "heading", level: 2, text: "Same" })]); + const diff = diffSemanticDocs(original, readBack); + assert.equal(diff.fidelity, "major-drift"); + assert.ok(diff.changedBlocks[0].fieldsDiffered.some((f) => f.field === "level" && f.severity === "major")); +} + +// 4. Missing + extra block, >30% structural delta → broken +{ + const original = model([ + block({ id: "a", text: "alpha" }), + block({ id: "b", text: "beta" }), + ]); + const readBack = model([ + block({ id: "a", text: "alpha" }), + block({ id: "c", text: "gamma" }), + ]); + const diff = diffSemanticDocs(original, readBack); + assert.equal(diff.removedBlocks.length, 1); + assert.equal(diff.addedBlocks.length, 1); + assert.equal(diff.removedBlocks[0].id, "b"); + assert.equal(diff.addedBlocks[0].id, "c"); + assert.equal(diff.fidelity, "broken"); +} + +// 5. runVerificationStage with mock ctx.read returning identical model → ruleDiff.identical, no warnings +{ + const original = model([block({ id: "b1", text: "stable" })]); + const ctx = { + from: "md", + to: "md", + read: () => model([block({ id: "b1", text: "stable" })]), + }; + const result = runVerificationStage({ model: original, output: { type: "text", format: "md", data: "stable" }, ctx }); + assert.equal(result.eligible, true); + assert.deepEqual(result.layers, ["rule-diff"]); + assert.equal(result.ruleDiff.identical, true); + assert.equal(result.warnings.length, 0); +} + +// 6. runVerificationStage with ctx.read throwing → RULE_DIFF_READBACK_FAILED warning, no throw +{ + const original = model([block({ id: "b1" })]); + const ctx = { + from: "md", + to: "md", + read: () => { throw new Error("boom"); }, + }; + const result = runVerificationStage({ model: original, output: { type: "text", format: "md", data: "x" }, ctx }); + assert.equal(result.eligible, true); + assert.equal(result.ruleDiff, null); + assert.equal(result.warnings.length, 1); + assert.equal(result.warnings[0].code, RULE_DIFF_READBACK_FAILED); +} + +// 7. runVerificationStage not eligible for non-text-canonical writer +{ + const original = model([block({ id: "b1" })]); + const ctx = { + from: "md", + to: "pptx", + read: () => original, + }; + const result = runVerificationStage({ model: original, output: { type: "binary", format: "pptx", data: "" }, ctx }); + assert.equal(result.eligible, false); + assert.equal(result.reason, "writer-not-text-canonical"); + assert.deepEqual(result.layers, []); + assert.equal(result.ruleDiff, null); + assert.equal(result.skipped[0].layer, "rule-diff"); + assert.equal(ROUND_TRIP_FORMATS.has("pptx"), false); +} + +// 8. End-to-end md -> md → ruleDiff.identical, verification.layers +{ + const result = convertContent({ content: "# Title\n\nBody text.", from: "md", to: "md", title: "e2e.md" }); + assert.equal(result.quality.qualityReport.ruleDiff.identical, true); + assert.deepEqual(result.quality.qualityReport.verification.layers, ["rule-diff"]); + assert.equal(result.quality.qualityReport.verification.eligible, true); +} + +// 9. End-to-end md -> html cross-format loopback runs, ruleDiff non-null +{ + const result = convertContent({ content: "# A\n\nB", from: "md", to: "html", title: "e2e.html" }); + assert.equal(result.quality.qualityReport.verification.eligible, true); + assert.notEqual(result.quality.qualityReport.ruleDiff, null); + assert.deepEqual(result.quality.qualityReport.verification.layers, ["rule-diff"]); +} + +// 10. End-to-end md -> pdf not eligible + shared fingerprint byte-equivalence +{ + const result = convertContent({ content: "# Hi", from: "md", to: "pdf", title: "e2e.pdf" }); + assert.equal(result.quality.qualityReport.ruleDiff, null); + assert.equal(result.quality.qualityReport.verification.eligible, false); + assert.equal(result.quality.qualityReport.verification.skipped[0].reason, "writer-not-text-canonical"); + + // shared fingerprint must match legacy implementation byte-for-byte + const samples = [ + block({ id: "p", text: "para" }), + block({ id: "h", type: "heading", level: 3, text: "Head" }), + { type: "code", language: "js", code: "x=1" }, + { type: "list", ordered: true, items: ["one", "two"] }, + { type: "table", headers: ["a", "b"], rows: [["1", "2"], ["3", "4"]] }, + { type: "image", src: "i.png", alt: "img" }, + { type: "raw", format: "html", content: "x" }, + ]; + for (const sample of samples) { + assert.equal(blockFingerprint(sample), legacyBlockFingerprint(sample), `fingerprint drift for ${sample.type}`); + } + const m = model(samples); + assert.equal(modelFingerprint(m), samples.map(legacyBlockFingerprint).join("")); + assert.equal(typeof RULE_DIFF_DRIFT, "string"); +} + +console.log("Rule diff test passed: diffSemanticDocs units, verification-stage gating/readback, end-to-end md->md/html/pdf, fingerprint equivalence covered."); diff --git a/scripts/sample-corpus-test.js b/scripts/sample-corpus-test.js new file mode 100644 index 0000000..a98d5f6 --- /dev/null +++ b/scripts/sample-corpus-test.js @@ -0,0 +1,93 @@ +import assert from "node:assert/strict"; + +import { + TEXT_BUILDERS, + SIZE_TIERS, + buildComplexMarkdown, + buildComplexCsv, + buildToTargetBytes, +} from "./lib/sample-content.js"; +import { buildPatternPng } from "./lib/png-encode.js"; +import { convertContent, getAllowedOutputFormats } from "../public/browser-transformer.js"; + +// 快速门禁：只在 small scale 验证生成器逻辑与跨格式可读性，不写 3MB 文件、不落盘。 +// 真正的大样例语料由 `npm run samples:generate` 产出到 samples/generated/（gitignore）。 + +// 1. 文本 builder 在 small scale 产出非空且确定（同输入同输出）。 +{ + for (const [key, builder] of Object.entries(TEXT_BUILDERS)) { + const a = builder(1); + const b = builder(1); + assert.equal(typeof a, "string"); + assert.ok(a.length > 0, `${key} builder should produce non-empty content`); + assert.equal(a, b, `${key} builder must be deterministic`); + } +} + +// 2. scale 增大 → 内容增大（医用于 size tier）。 +{ + const small = buildComplexMarkdown(SIZE_TIERS.small); + const medium = buildComplexMarkdown(SIZE_TIERS.medium); + assert.ok(medium.length > small.length * 10, "medium markdown should be much larger than small"); +} + +// 3. 复杂 markdown 覆盖关键结构（表格/代码/任务/脚注/CJK/RTL）。 +{ + const md = buildComplexMarkdown(1); + assert.ok(md.includes("|"), "should contain table"); + assert.ok(md.includes("```"), "should contain code fence"); + assert.ok(md.includes("- [x]"), "should contain task list"); + assert.ok(md.includes("[^note1]"), "should contain footnote"); + assert.ok(/[一-鿿]/.test(md), "should contain CJK"); + assert.ok(/[؀-ۿ]/.test(md), "should contain Arabic/RTL"); +} + +// 4. CSV builder 含带引号/逗号/换行的字段（边界 CSV）。 +{ + const csv = buildComplexCsv(1); + assert.ok(csv.includes("\"\""), "CSV should contain escaped quotes"); + assert.ok(csv.split("\n").length > 1, "CSV should have multiple rows"); +} + +// 5. small-scale 文本源能转换到全部产品矩阵目标格式且非空（回归可读性）。 +{ + const md = buildComplexMarkdown(1); + const targets = getAllowedOutputFormats("md"); + assert.ok(targets.length > 0); + for (const to of targets) { + const result = convertContent({ content: md, from: "md", to, title: "corpus", options: { repair: false } }); + const data = result?.data ?? result; + assert.ok(data && (typeof data === "string" ? data.length > 0 : data.length > 0), `md -> ${to} should be non-empty`); + } +} + +// 6. csv -> xlsx/json/md 走得通（结构化数据链）。 +{ + const csv = buildComplexCsv(2); + for (const to of ["xlsx", "json", "md", "html"]) { + const result = convertContent({ content: csv, from: "csv", to, title: "corpus-csv", options: { repair: false } }); + const data = result?.data ?? result; + assert.ok(data, `csv -> ${to} should produce output`); + } +} + +// 7. PNG encoder 产出有效 PNG 签名头 + 随尺寸增大。 +{ + const small = buildPatternPng(16, 16); + const big = buildPatternPng(64, 64); + const signature = [0x89, 0x50, 0x4e, 0x47, 0x0d, 0x0a, 0x1a, 0x0a]; + for (let i = 0; i < signature.length; i += 1) { + assert.equal(small[i], signature[i], "PNG signature byte mismatch"); + } + assert.ok(big.length > small.length, "larger PNG should have more bytes"); +} + +// 8. buildToTargetBytes 能逼近目标字节（用于 large ≥ 3MB 层）。 +{ + const target = 200 * 1024; + const { content, scale } = buildToTargetBytes(buildComplexMarkdown, target); + assert.ok(Buffer.byteLength(content, "utf8") >= target, "should reach target bytes"); + assert.ok(scale > 1, "scale should grow to reach target"); +} + +console.log("Sample corpus test passed: deterministic complex builders, size scaling, CJK/RTL/table/code coverage, cross-format readability, PNG encoder, target-byte scaling verified."); diff --git a/scripts/ssim-verification-test.js b/scripts/ssim-verification-test.js new file mode 100644 index 0000000..45fd340 --- /dev/null +++ b/scripts/ssim-verification-test.js @@ -0,0 +1,181 @@ +import assert from "node:assert/strict"; + +import { + computeSSIM, + compareImages, + rgbaToGrayscale, + resampleGrayscale, + runSsimLayer, + runVerificationStageAsync, + defaultPageImageSource, + setPageImageSource, + resetPageImageSource, + RASTERIZABLE_FORMATS, + SSIM_VISUAL_DRIFT, + VERIFICATION_IMAGE_SOURCE_UNAVAILABLE, + convertContentAsync, +} from "../public/browser-transformer.js"; + +function solidImage(value, width = 32, height = 32) { + const pixels = new Uint8ClampedArray(width * height * 4); + for (let i = 0; i < width * height; i += 1) { + pixels[i * 4] = value; + pixels[i * 4 + 1] = value; + pixels[i * 4 + 2] = value; + pixels[i * 4 + 3] = 255; + } + return { pixels, width, height }; +} + +function gradientImage(width = 32, height = 32, offset = 0) { + // 平滑水平渐变（低频），重采样到不同网格仍稳定。 + const pixels = new Uint8ClampedArray(width * height * 4); + for (let y = 0; y < height; y += 1) { + for (let x = 0; x < width; x += 1) { + const v = Math.min(255, Math.round((x / Math.max(1, width - 1)) * 255) + offset); + const o = (y * width + x) * 4; + pixels[o] = v; + pixels[o + 1] = v; + pixels[o + 2] = v; + pixels[o + 3] = 255; + } + } + return { pixels, width, height }; +} + +// 1. rgbaToGrayscale length + luminance +{ + const gray = rgbaToGrayscale(solidImage(120, 4, 4).pixels); + assert.equal(gray.length, 16); + assert.equal(gray[0], 120); +} + +// 2. computeSSIM identical buffers -> 1 +{ + const gray = rgbaToGrayscale(gradientImage(16, 16).pixels); + const result = computeSSIM(gray, gray, 16, 16, { windowSize: 8 }); + assert.ok(result.score > 0.999, `identical SSIM should be ~1, got ${result.score}`); +} + +// 3. compareImages identical -> ~1, black vs white -> near 0 +{ + const black = solidImage(0); + const white = solidImage(255); + assert.ok(compareImages(black, black).score > 0.999); + assert.ok(compareImages(black, white).score < 0.05, "black vs white should be near zero"); +} + +// 4. compareImages monotonic: closer image scores higher than further +{ + const base = gradientImage(32, 32, 0); + const near = gradientImage(32, 32, 8); + const far = solidImage(0, 32, 32); + const nearScore = compareImages(base, near, { targetWidth: 32 }).score; + const farScore = compareImages(base, far, { targetWidth: 32 }).score; + assert.ok(nearScore > farScore, `near (${nearScore}) should beat far (${farScore})`); + assert.ok(nearScore < 1, "a perturbed image should be below 1"); +} + +// 5. resampleGrayscale resizes to requested grid + same-size passthrough +{ + const gray = rgbaToGrayscale(gradientImage(16, 16).pixels); + const down = resampleGrayscale(gray, 16, 16, 8, 8); + assert.equal(down.length, 64); + const same = resampleGrayscale(gray, 16, 16, 16, 16); + assert.equal(same.length, 256); +} + +// 6. compareImages handles mismatched dimensions by normalizing to a common grid +{ + const big = gradientImage(64, 64); + const small = gradientImage(16, 16); + const cmp = compareImages(big, small, { targetWidth: 32 }); + assert.equal(cmp.dimensionsMatched, false); + assert.ok(cmp.score > 0.5, "same gradient at different sizes should still be fairly similar"); +} + +// 7. runSsimLayer with stub image source -> eligible, score, passed +{ + setPageImageSource({ getPageImage: async ({ format }) => (format === "pdf" ? solidImage(100) : solidImage(104)) }); + const layer = await runSsimLayer({ ctx: { from: "png", to: "pdf", content: "", options: {} }, output: { data: "" } }); + assert.equal(layer.eligible, true); + assert.equal(typeof layer.ssim.score, "number"); + assert.equal(layer.ssim.sourceFormat, "png"); + assert.equal(layer.ssim.outputFormat, "pdf"); + resetPageImageSource(); +} + +// 8. runSsimLayer drift below threshold -> SSIM_VISUAL_DRIFT warning +{ + setPageImageSource({ getPageImage: async ({ format }) => (format === "pdf" ? solidImage(0) : solidImage(255)) }); + const layer = await runSsimLayer({ ctx: { from: "png", to: "pdf", content: "", options: { verification: { ssimThreshold: 0.9 } } }, output: { data: "" } }); + assert.equal(layer.eligible, true); + assert.equal(layer.ssim.passed, false); + assert.equal(layer.warnings.length, 1); + assert.equal(layer.warnings[0].code, SSIM_VISUAL_DRIFT); + resetPageImageSource(); +} + +// 9. runSsimLayer not eligible for non-rasterizable path +{ + const layer = await runSsimLayer({ ctx: { from: "md", to: "pdf", content: "# Hi", options: {} }, output: { data: "" } }); + assert.equal(layer.eligible, false); + assert.equal(layer.reason, "source-not-rasterizable"); + assert.equal(layer.ssim, null); + assert.equal(RASTERIZABLE_FORMATS.has("md"), false); + assert.equal(RASTERIZABLE_FORMATS.has("pdf"), true); +} + +// 10. defaultPageImageSource throws image-source-unavailable in Node (no DOM) +{ + resetPageImageSource(); + await assert.rejects( + () => defaultPageImageSource.getPageImage({ format: "pdf", content: "" }), + (err) => err.code === VERIFICATION_IMAGE_SOURCE_UNAVAILABLE, + "Node default image source must report unavailable", + ); + // and runSsimLayer surfaces that as eligible:false without throwing + const layer = await runSsimLayer({ ctx: { from: "png", to: "pdf", content: "", options: {} }, output: { data: "" } }); + assert.equal(layer.eligible, false); + assert.equal(layer.reason, "image-source-unavailable"); +} + +// 11. runVerificationStageAsync merges rule-diff base + ssim layer +{ + setPageImageSource({ getPageImage: async ({ format }) => (format === "pdf" ? solidImage(100) : solidImage(100)) }); + const env = await runVerificationStageAsync({ + model: { blocks: [] }, + output: { data: "" }, + ctx: { from: "png", to: "pdf", content: "", read: () => ({ blocks: [] }), options: {} }, + }); + assert.ok(env.layers.includes("ssim")); + // png is not text-canonical so rule-diff is skipped + assert.ok(env.skipped.some((s) => s.layer === "rule-diff")); + assert.notEqual(env.ssim, null); + resetPageImageSource(); +} + +// 12. End-to-end convertContentAsync: sync ssim stays null on text path; pdf->pdf populates ssim via stub +{ + // text path (md->md): ssim must be null, rule-diff present + resetPageImageSource(); + const textResult = await convertContentAsync({ content: "# Title\n\nBody", from: "md", to: "md", title: "e2e" }); + assert.equal(textResult.quality.qualityReport.ssim, null); + assert.equal(textResult.quality.qualityReport.ruleDiff.identical, true); + + // visual path (png->pdf) with stub image source: ssim populated + setPageImageSource({ getPageImage: async ({ format }) => (format === "pdf" ? solidImage(120) : solidImage(125)) }); + const visualResult = await convertContentAsync({ + content: "data:image/png;base64,AAAA", + from: "png", + to: "pdf", + title: "e2e-visual", + options: { ocr: { enabled: false } }, + }); + assert.notEqual(visualResult.quality.qualityReport.ssim, null); + assert.equal(visualResult.quality.qualityReport.ssim.sourceFormat, "png"); + assert.ok(visualResult.quality.qualityReport.verification.layers.includes("ssim")); + resetPageImageSource(); +} + +console.log("SSIM verification test passed: ssim core (grayscale/resample/computeSSIM/compareImages), ssim layer gating/drift/unavailable, async envelope merge, end-to-end null-on-text + populated-on-visual covered."); diff --git a/scripts/sync-onnxruntime-vendor.js b/scripts/sync-onnxruntime-vendor.js new file mode 100644 index 0000000..844f93c --- /dev/null +++ b/scripts/sync-onnxruntime-vendor.js @@ -0,0 +1,60 @@ +import { access, copyFile, mkdir, readdir, stat } from "node:fs/promises"; +import path from "node:path"; + +// 模仿 sync-tesseract-vendor：把 onnxruntime-web 的运行时资源（ort*.mjs + *.wasm）同步到 +// public/vendor/onnxruntime/，供 PP-OCRv5 高级 OCR 在浏览器/Tauri 端同源加载。 +// onnxruntime-web 是 optionalDependency；缺失时 exit 0，不阻塞 release:prepare / 安装。 + +const ROOT = process.cwd(); +const ORT_DIST = path.join(ROOT, "node_modules", "onnxruntime-web", "dist"); +const TARGET_DIR = path.join(ROOT, "public", "vendor", "onnxruntime"); + +async function pathExists(p) { + try { + await access(p); + return true; + } catch { + return false; + } +} + +async function main() { + if (!(await pathExists(ORT_DIST))) { + console.warn("[sync-onnxruntime-vendor] onnxruntime-web is not installed (optionalDependency missing). Skipping vendor sync."); + console.warn("[sync-onnxruntime-vendor] Run `npm install onnxruntime-web` to enable the PP-OCRv5 advanced OCR runtime."); + return; + } + + await mkdir(TARGET_DIR, { recursive: true }); + + // 只同步运行时实际需要的最小集合：`ort.min.mjs` 入口 + 它加载的 JSEP 构建 + // （`ort-wasm-simd-threaded.jsep.{mjs,wasm}`，同时支持 WebGPU 与 WASM 执行后端）。 + // 其余 all/bundle/jspi/asyncify/plain 变体（~68MB 冗余）不进 vendor，避免撑大应用体积。 + const KEEP = new Set([ + "ort.min.mjs", + "ort-wasm-simd-threaded.jsep.mjs", + "ort-wasm-simd-threaded.jsep.wasm", + ]); + const entries = await readdir(ORT_DIST); + let copied = 0; + for (const entry of entries) { + if (!KEEP.has(entry)) continue; + const source = path.join(ORT_DIST, entry); + const info = await stat(source); + if (!info.isFile()) continue; + await copyFile(source, path.join(TARGET_DIR, entry)); + copied += 1; + } + + if (copied === 0) { + console.warn("[sync-onnxruntime-vendor] No onnxruntime-web runtime assets found in dist/. PP-OCRv5 will stay unavailable until installed."); + return; + } + + console.log(`onnxruntime-web vendor synced to public/vendor/onnxruntime/ (${copied} files).`); +} + +main().catch((error) => { + console.warn(`[sync-onnxruntime-vendor] sync failed: ${error?.message || error}`); + process.exitCode = 0; +}); diff --git a/scripts/sync-paddleocr-vendor.js b/scripts/sync-paddleocr-vendor.js new file mode 100644 index 0000000..2c51444 --- /dev/null +++ b/scripts/sync-paddleocr-vendor.js @@ -0,0 +1,106 @@ +import { createHash } from "node:crypto"; +import { mkdir, readFile, rm, stat, writeFile } from "node:fs/promises"; +import path from "node:path"; +import { fileURLToPath } from "node:url"; + +// 把 PP-OCRv5 mobile 模型（det/rec + 字典）从钉定 commit 的 ppu-paddle-ocr-models 仓库下载到 +// public/vendor/paddleocr/，供高级 OCR 启动自动载入、开箱即用。逐文件 SHA-256 校验 +// scripts/paddleocr-models.manifest.json（入库，可复现）。 +// +// 设计与 sync-onnxruntime-vendor 一致的「非阻塞」原则： +// - 已存在且校验通过 → 跳过（幂等）。 +// - 网络/HTTP 失败（离线、源不可达）→ 警告 + exit 0，不阻断 npm install / release:prepare。 +// - 下到字节但 size/SHA-256 不符 → 删除半成品 + 非零退出（完整性问题必须报警，不可静默放行）。 +// +// 注意：本脚本在构建期联网；App 运行期仍零联网（模型已落到同源 vendor）。 +// 方向分类 cls.onnx 为可选，不随包；如需 180° 校正可在安全中心手动导入。 + +const __dirname = path.dirname(fileURLToPath(import.meta.url)); +const ROOT = process.cwd(); +const MANIFEST_PATH = path.join(__dirname, "paddleocr-models.manifest.json"); +const TARGET_DIR = path.join(ROOT, "public", "vendor", "paddleocr"); + +function remoteUrl(source, file) { + const { repo, commit } = source; + if (file.kind === "lfs") { + return `https://media.githubusercontent.com/media/${repo}/${commit}/${file.remotePath}`; + } + return `https://raw.githubusercontent.com/${repo}/${commit}/${file.remotePath}`; +} + +function sha256(buffer) { + return createHash("sha256").update(buffer).digest("hex"); +} + +async function fileMatches(destPath, file) { + try { + const info = await stat(destPath); + if (!info.isFile() || info.size !== file.size) return false; + const buffer = await readFile(destPath); + return sha256(buffer) === file.sha256; + } catch { + return false; + } +} + +async function main() { + let manifest; + try { + manifest = JSON.parse(await readFile(MANIFEST_PATH, "utf8")); + } catch (error) { + console.warn(`[sync-paddleocr-vendor] manifest 读取失败：${error?.message || error}；跳过。`); + return; + } + + await mkdir(TARGET_DIR, { recursive: true }); + + let synced = 0; + let skipped = 0; + for (const file of manifest.files || []) { + const destPath = path.join(TARGET_DIR, file.target); + + if (await fileMatches(destPath, file)) { + skipped += 1; + continue; + } + + const url = remoteUrl(manifest.source, file); + let buffer; + try { + const response = await fetch(url); + if (!response.ok) throw new Error(`HTTP ${response.status}`); + buffer = Buffer.from(await response.arrayBuffer()); + } catch (error) { + // 网络/HTTP 失败：非阻塞退出（与 onnx/tesseract vendor 一致）。 + console.warn(`[sync-paddleocr-vendor] 下载 ${file.target} 失败（${error?.message || error}）。`); + console.warn("[sync-paddleocr-vendor] 离线或源不可达时跳过；高级 OCR 仍可在安全中心手动导入模型。"); + console.warn(`[sync-paddleocr-vendor] 源：${url}`); + return; + } + + // 下到字节后做完整性校验：不符则删半成品 + 非零退出（不可静默放行）。 + const actualSize = buffer.length; + const actualSha = sha256(buffer); + if (actualSize !== file.size || actualSha !== file.sha256) { + await rm(destPath, { force: true }); + console.error(`[sync-paddleocr-vendor] ${file.target} 完整性校验失败：`); + console.error(` 期望 size=${file.size} sha256=${file.sha256}`); + console.error(` 实际 size=${actualSize} sha256=${actualSha}`); + console.error(" 源文件可能已变更/损坏；请核对 manifest 与钉定 commit。"); + process.exit(1); + } + + await writeFile(destPath, buffer); + synced += 1; + console.log(`[sync-paddleocr-vendor] ${file.target} 同步并校验通过 (${(actualSize / (1024 * 1024)).toFixed(2)} MB).`); + } + + console.log( + `PP-OCRv5 vendor synced to public/vendor/paddleocr/ (downloaded=${synced}, cached=${skipped}; cls optional, not bundled).`, + ); +} + +main().catch((error) => { + console.warn(`[sync-paddleocr-vendor] sync failed: ${error?.message || error}`); + process.exitCode = 0; +}); diff --git a/scripts/sync-tesseract-vendor.js b/scripts/sync-tesseract-vendor.js index 9a1788c..c984211 100644 --- a/scripts/sync-tesseract-vendor.js +++ b/scripts/sync-tesseract-vendor.js @@ -1,6 +1,13 @@ -import { access, copyFile, mkdir, readdir, stat } from "node:fs/promises"; +import { access, copyFile, mkdir, readdir, readFile, stat, writeFile } from "node:fs/promises"; import path from "node:path"; +// 本项目 local-only 安全门禁（scripts/local-security-test.js）禁止 public/vendor/ 下任何 +// vendor .js 出现远程协议字符串。tesseract.js bundle 里只内置了 CDN 默认路径 +// （https://cdn.jsdelivr.net/...），而运行时（tesseract-runtime.js）恒以同源 /vendor/ 路径 +// 覆盖 corePath/workerPath/langPath —— 这些 CDN 默认值是死代码。复制后把它们改写成同源相对 +// 路径并去掉 sourceMappingURL 注释，让 served asset 真正 local-only。 +const REMOTE_PROTOCOL_RE = /(https?:|wss?:)\/\//; + const ROOT = process.cwd(); const TESSERACT_DIST = path.join(ROOT, "node_modules", "tesseract.js", "dist"); const TESSERACT_CORE = path.join(ROOT, "node_modules", "tesseract.js-core"); @@ -23,6 +30,32 @@ async function copyIfPresent(source, destination) { return true; } +// 复制后清洗：把 vendor bundle 里的 CDN 默认路径改写成同源 /vendor 路径，并去掉 +// sourceMappingURL 注释（对应 .map 不再随包）。清洗后逐文件断言无残留远程协议， +// 让未来 tesseract 版本若引入新远程 host 时本脚本先行报警而非静默漏过门禁。 +async function sanitizeVendorBundles(dir) { + if (!(await pathExists(dir))) return; + const entries = await readdir(dir); + for (const entry of entries) { + if (!/\.(js|mjs)$/.test(entry)) continue; + const filePath = path.join(dir, entry); + const info = await stat(filePath); + if (!info.isFile()) continue; + const original = await readFile(filePath, "utf8"); + const cleaned = original + .replaceAll("https://cdn.jsdelivr.net", "/vendor") + .replace(/\n?\/\/[#@]\s*sourceMappingURL=.*$/gm, ""); + if (cleaned !== original) await writeFile(filePath, cleaned, "utf8"); + const leftover = cleaned.match(REMOTE_PROTOCOL_RE); + if (leftover) { + throw new Error( + `[sync-tesseract-vendor] ${path.relative(ROOT, filePath).replaceAll("\\", "/")} 清洗后仍含远程协议串 (${leftover[0]}...)；` + + `请扩展 sanitizeVendorBundles 的改写规则后再发布。`, + ); + } + } +} + async function copyDistEntries(sourceDir, destDir) { if (!(await pathExists(sourceDir))) return []; const entries = await readdir(sourceDir); @@ -31,7 +64,7 @@ async function copyDistEntries(sourceDir, destDir) { const fullSource = path.join(sourceDir, entry); const info = await stat(fullSource); if (!info.isFile()) continue; - if (!/\.(js|mjs|wasm|map)$/.test(entry)) continue; + if (!/\.(js|mjs|wasm)$/.test(entry)) continue; if (entry.endsWith(".d.ts")) continue; await copyFile(fullSource, path.join(destDir, entry)); copied.push(entry); @@ -53,7 +86,7 @@ async function main() { let mainCopied = false; let workerCopied = false; for (const entry of distEntries) { - if (!/\.(js|mjs|map)$/.test(entry)) continue; + if (!/\.(js|mjs)$/.test(entry)) continue; if (entry.endsWith(".d.ts")) continue; const source = path.join(TESSERACT_DIST, entry); if (entry.startsWith("worker")) { @@ -84,7 +117,10 @@ async function main() { console.warn("[sync-tesseract-vendor] tesseract.js-core not found; wasm runtime missing. OCR will stay unavailable until installed."); } - console.log(`Tesseract.js vendor synced to public/vendor/tesseract/ (worker=${workerCopied}, core=${coreBundleCopied}).`); + await sanitizeVendorBundles(TARGET_CORE_DIR); + await sanitizeVendorBundles(TARGET_WORKER_DIR); + + console.log(`Tesseract.js vendor synced to public/vendor/tesseract/ (worker=${workerCopied}, core=${coreBundleCopied}); remote URLs sanitized.`); } main().catch((error) => { diff --git a/src-tauri/Cargo.lock b/src-tauri/Cargo.lock index dae71b3..860753d 100644 --- a/src-tauri/Cargo.lock +++ b/src-tauri/Cargo.lock @@ -3625,7 +3625,7 @@ dependencies = [ [[package]] name = "trans2former" -version = "2.2.0" +version = "2.3.0" dependencies = [ "tauri", "tauri-build", diff --git a/src-tauri/Cargo.toml b/src-tauri/Cargo.toml index 2099c3b..76618a7 100644 --- a/src-tauri/Cargo.toml +++ b/src-tauri/Cargo.toml @@ -1,6 +1,6 @@ [package] name = "trans2former" -version = "2.2.0" +version = "2.3.0" description = "Trans2Former Desktop" edition = "2021" diff --git a/src-tauri/tauri.conf.json b/src-tauri/tauri.conf.json index 5a568ee..da6c3f7 100644 --- a/src-tauri/tauri.conf.json +++ b/src-tauri/tauri.conf.json @@ -1,7 +1,7 @@ { "$schema": "https://schema.tauri.app/config/2", "productName": "Trans2Former", - "version": "2.2.0", + "version": "2.3.0", "identifier": "com.vantalens.trans2former", "build": { "beforeDevCommand": "npm start",