diff --git a/.eslintrc.cjs b/.eslintrc.cjs new file mode 100644 index 0000000..d30cacc --- /dev/null +++ b/.eslintrc.cjs @@ -0,0 +1,31 @@ +module.exports = { + root: true, + env: { browser: true, es2020: true, node: true }, + extends: [ + 'eslint:recommended', + 'plugin:@typescript-eslint/recommended', + 'plugin:react-hooks/recommended', + 'plugin:react/recommended', + ], + parser: '@typescript-eslint/parser', + parserOptions: { + ecmaVersion: 'latest', + sourceType: 'module', + ecmaFeatures: { + jsx: true, + }, + }, + settings: { + react: { + version: 'detect', + }, + }, + plugins: ['react-refresh'], + rules: { + 'react/react-in-jsx-scope': 'off', + 'react-refresh/only-export-components': ['warn', { allowConstantExport: true }], + // Warn on `any` types to align with CONTRIBUTING.md + '@typescript-eslint/no-explicit-any': 'warn', + }, + ignorePatterns: ['dist', '.eslintrc.cjs', 'node_modules/', 'backend/', 'public/', 'scripts/'], +}; diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 9ca308d..0391f3f 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -11,9 +11,9 @@ jobs: name: Frontend Lint runs-on: ubuntu-latest steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 - - uses: actions/setup-node@v6 + - uses: actions/setup-node@v4 with: node-version: 20 cache: npm @@ -29,9 +29,9 @@ jobs: runs-on: ubuntu-latest needs: frontend-lint steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 - - uses: actions/setup-node@v6 + - uses: actions/setup-node@v4 with: node-version: 20 cache: npm @@ -52,9 +52,9 @@ jobs: run: working-directory: backend steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 - - uses: actions/setup-python@v6 + - uses: actions/setup-python@v5 with: python-version: "3.12" cache: pip @@ -83,7 +83,7 @@ jobs: outputs: backend: ${{ steps.filter.outputs.backend }} steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 - uses: dorny/paths-filter@v3 id: filter with: @@ -98,7 +98,7 @@ jobs: needs: [backend-lint-and-test, check-backend-changes] runs-on: ubuntu-latest steps: - - uses: actions/checkout@v6 + - uses: actions/checkout@v4 with: fetch-depth: 0 # full history needed for subtree push lfs: true diff --git a/README.md b/README.md index bf5d569..55dc69d 100644 --- a/README.md +++ b/README.md @@ -53,6 +53,7 @@ FreshScanAi/ │ ├── components/ │ ├── pages/ # Scanner, Dashboard, MarketMap │ ├── lib/ # API client and utilities +│ ├── i18n/ # Translations (Hindi, Bengali) │ └── App.tsx ├── public/ # Static assets ├── Models/ # Pre-compiled PyTorch model weights diff --git a/eslint.config.js b/eslint.config.js deleted file mode 100644 index 2cf7575..0000000 --- a/eslint.config.js +++ /dev/null @@ -1,23 +0,0 @@ -import js from '@eslint/js' -import globals from 'globals' -import reactHooks from 'eslint-plugin-react-hooks' -import reactRefresh from 'eslint-plugin-react-refresh' -import tseslint from 'typescript-eslint' -import { defineConfig, globalIgnores } from 'eslint/config' - -export default defineConfig([ - globalIgnores(['dist', '**/._*']), - { - files: ['**/*.{ts,tsx}'], - extends: [ - js.configs.recommended, - tseslint.configs.recommended, - reactHooks.configs.flat.recommended, - reactRefresh.configs.vite, - ], - languageOptions: { - ecmaVersion: 2020, - globals: globals.browser, - }, - }, -]) diff --git a/index.html b/index.html index 5fe3f70..6f05142 100644 --- a/index.html +++ b/index.html @@ -21,4 +21,4 @@ - \ No newline at end of file + diff --git a/package-lock.json b/package-lock.json index 6d801e5..9b2dabc 100644 --- a/package-lock.json +++ b/package-lock.json @@ -8,44 +8,47 @@ "name": "frontend", "version": "1.3.0", "dependencies": { - "@tailwindcss/vite": "^4.2.2", - "framer-motion": "^12.38.0", - "i18next": "^26.3.0", + "framer-motion": "^11.2.10", + "i18next": "^23.11.5", + "i18next-browser-languagedetector": "^8.0.0", "leaflet": "^1.9.4", - "lucide-react": "^1.16.0", - "onnxruntime-web": "^1.26.0", - "posthog-js": "^1.376.2", - "react": "^19.2.4", - "react-dom": "^19.2.4", - "react-hot-toast": "^2.6.0", - "react-i18next": "^17.0.8", - "react-joyride": "^3.1.0", - "react-leaflet": "^5.0.0", - "react-router-dom": "^7.14.0", - "tailwindcss": "^4.2.2" + "lucide-react": "^0.395.0", + "onnxruntime-web": "^1.18.0", + "posthog-js": "^1.141.0", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-hot-toast": "^2.4.1", + "react-i18next": "^14.1.2", + "react-joyride": "^2.8.2", + "react-leaflet": "^4.2.1", + "react-router-dom": "^6.23.1" }, "devDependencies": { - "@eslint/js": "^9.39.4", - "@types/leaflet": "^1.9.21", - "@types/node": "^25.9.1", - "@types/react": "^19.2.14", - "@types/react-dom": "^19.2.3", - "@vitejs/plugin-react": "^6.0.1", - "concurrently": "^9.2.1", - "cross-env": "^10.1.0", - "eslint": "^9.39.4", - "eslint-plugin-react-hooks": "^7.0.1", - "eslint-plugin-react-refresh": "^0.5.2", - "globals": "^17.4.0", - "typescript": "~6.0.3", - "typescript-eslint": "^8.57.0", - 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"dependencies": { @@ -59,6 +62,8 @@ }, "node_modules/@babel/compat-data": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.29.7.tgz", + "integrity": "sha512-locTkQyKvwIEgBzVrn8693ebc97F2U8ZHjbXwDXJ5Fn2TCpNwTlKcaKLkdHop5c/icOFE7qt7Q9JC5hnKNa6Gg==", "dev": true, "license": "MIT", "engines": { @@ -66,19 +71,21 @@ } }, "node_modules/@babel/core": { - "version": "7.29.0", + "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.29.7.tgz", + "integrity": "sha512-RgHBCvtjbOK2gXSNBNIkNoEc9qoVEtau3hj8gEqKQuL3HZAibKarWFEI3Lfm6EYKkLalOh8eSrj9b+ch9H/VBA==", "dev": true, "license": "MIT", "dependencies": { - "@babel/code-frame": "^7.29.0", - "@babel/generator": "^7.29.0", - "@babel/helper-compilation-targets": "^7.28.6", - "@babel/helper-module-transforms": "^7.28.6", - "@babel/helpers": "^7.28.6", - "@babel/parser": "^7.29.0", - "@babel/template": "^7.28.6", - "@babel/traverse": "^7.29.0", - "@babel/types": "^7.29.0", + "@babel/code-frame": "^7.29.7", + "@babel/generator": "^7.29.7", + "@babel/helper-compilation-targets": "^7.29.7", + "@babel/helper-module-transforms": "^7.29.7", + "@babel/helpers": "^7.29.7", + "@babel/parser": "^7.29.7", + "@babel/template": "^7.29.7", + "@babel/traverse": "^7.29.7", + "@babel/types": "^7.29.7", "@jridgewell/remapping": "^2.3.5", "convert-source-map": "^2.0.0", "debug": "^4.1.0", @@ -94,8 +101,20 @@ "url": "https://opencollective.com/babel" } }, + "node_modules/@babel/core/node_modules/semver": { + "version": "6.3.1", + "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.1.tgz", + "integrity": "sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA==", + "dev": true, + "license": "ISC", + "bin": { + "semver": "bin/semver.js" + } + }, "node_modules/@babel/generator": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/generator/-/generator-7.29.7.tgz", + "integrity": 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"node_modules/@babel/helper-compilation-targets/node_modules/semver": { + "version": "6.3.1", + "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.1.tgz", + "integrity": "sha512-BR7VvDCVHO+q2xBEWskxS6DJE1qRnb7DxzUrogb71CWoSficBxYsiAGd+Kl0mmq/MprG9yArRkyrQxTO6XjMzA==", + "dev": true, + "license": "ISC", + "bin": { + "semver": "bin/semver.js" + } + }, "node_modules/@babel/helper-create-class-features-plugin": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/helper-create-class-features-plugin/-/helper-create-class-features-plugin-7.29.7.tgz", + "integrity": "sha512-IY3ZD9Tmooqr3TUhc3DUWxiuo8xx1DWLhd5M7hQ+ZWJamqM2BbalrBJb2MisSLoYorOj75U03qULCxQTY9r3hg==", "dev": true, "license": "MIT", "dependencies": { @@ -155,8 +190,20 @@ "@babel/core": "^7.0.0" } }, + "node_modules/@babel/helper-create-class-features-plugin/node_modules/semver": { + "version": "6.3.1", + "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.1.tgz", + "integrity": 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"node_modules/@babel/helper-define-polyfill-provider": { "version": "0.6.8", + "resolved": "https://registry.npmjs.org/@babel/helper-define-polyfill-provider/-/helper-define-polyfill-provider-0.6.8.tgz", + "integrity": "sha512-47UwBLPpQi1NoWzLuHNjRoHlYXMwIJoBf7MFou6viC/sIHWYygpvr0B6IAyh5sBdA2nr2LPIRww8lfaUVQINBA==", "dev": true, "license": "MIT", "dependencies": { @@ -186,8 +245,32 @@ "@babel/core": "^7.4.0 || ^8.0.0-0 <8.0.0" } }, + "node_modules/@babel/helper-define-polyfill-provider/node_modules/resolve": { + "version": "1.22.12", + "resolved": "https://registry.npmjs.org/resolve/-/resolve-1.22.12.tgz", + "integrity": "sha512-TyeJ1zif53BPfHootBGwPRYT1RUt6oGWsaQr8UyZW/eAm9bKoijtvruSDEmZHm92CwS9nj7/fWttqPCgzep8CA==", + "dev": true, + "license": "MIT", + "dependencies": { + "es-errors": "^1.3.0", + "is-core-module": "^2.16.1", + "path-parse": "^1.0.7", + "supports-preserve-symlinks-flag": "^1.0.0" + }, + "bin": { + "resolve": "bin/resolve" + }, + "engines": { + "node": ">= 0.4" + }, + "funding": { + "url": "https://github.com/sponsors/ljharb" + } + }, "node_modules/@babel/helper-globals": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/helper-globals/-/helper-globals-7.29.7.tgz", + "integrity": "sha512-3nQVUAtvkKH9zahfWgw96Jc/uFOmjACE1kQz82E2lqWmHBgjzbNlsC22nuQTfahmWeQtTq5nQ/4Nnd2A1wj4zA==", "dev": true, "license": "MIT", "engines": { @@ -196,6 +279,8 @@ }, "node_modules/@babel/helper-member-expression-to-functions": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/helper-member-expression-to-functions/-/helper-member-expression-to-functions-7.29.7.tgz", + "integrity": "sha512-j+7JYmk1JYDtACIGj0QJqqWZjoUpMoEikQGADMaHgCMCSDqd2+P32rfcibUNrGOMWrlzK1WJBdxrB3JJQZwWtg==", "dev": true, "license": "MIT", "dependencies": { @@ -208,6 +293,8 @@ }, "node_modules/@babel/helper-module-imports": { "version": "7.29.7", + "resolved": "https://registry.npmjs.org/@babel/helper-module-imports/-/helper-module-imports-7.29.7.tgz", + 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"license": "MIT", "dependencies": { @@ -7732,6 +9618,8 @@ }, "node_modules/workbox-recipes": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-recipes/-/workbox-recipes-7.4.1.tgz", + "integrity": "sha512-gnbVfmV4/TtmQaM4x9AtuXhcdstJsep3XMVeztOrQVPT+R6+6DeBjGTCQ7fFCXm+4GEHUA5VEBTyi5+4gWGeog==", "dev": true, "license": "MIT", "dependencies": { @@ -7745,6 +9633,8 @@ }, "node_modules/workbox-routing": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-routing/-/workbox-routing-7.4.1.tgz", + "integrity": "sha512-yubJGErZOusuidAenaL5ypfhQOa7urxP/f8E0ws7FPb4039RiWXUWBAyUkmUoOL/BcQGen3h0J8872d51IYxtA==", "dev": true, "license": "MIT", "dependencies": { @@ -7753,6 +9643,8 @@ }, "node_modules/workbox-strategies": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-strategies/-/workbox-strategies-7.4.1.tgz", + "integrity": "sha512-GZxpaw9NbmOelj7667uZ2kpk5BFpOGbO4X0qjwh5ls8XQ8C+Lha5LQchTiUzsTFSS+NlUpftYAyOVXvQUrcqOQ==", "dev": true, "license": "MIT", "dependencies": { @@ -7761,6 +9653,8 @@ }, "node_modules/workbox-streams": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-streams/-/workbox-streams-7.4.1.tgz", + "integrity": "sha512-HWWtraKUbJknd9kgqGcpQ3G114HOPYvqs8HaJMDs2ebLNAimDkVDaWfAXE6Ybl+m8U6KsCE6pWyLYuigWmnAXw==", "dev": true, "license": "MIT", "dependencies": { @@ -7770,11 +9664,15 @@ }, "node_modules/workbox-sw": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-sw/-/workbox-sw-7.4.1.tgz", + "integrity": "sha512-fez5f2DUlDJWTFYkCWQpY10N8gtztd849NswCbVFk0QlcSM4HT5A8x4g4ii650yem4I8tHY0R7JZahwp3ltIPw==", "dev": true, "license": "MIT" }, "node_modules/workbox-window": { "version": "7.4.1", + "resolved": "https://registry.npmjs.org/workbox-window/-/workbox-window-7.4.1.tgz", + "integrity": "sha512-notZDH2u8VXaqyuD7xaqIfEFi6SRM4SUSd7ewe9PDsVqADuepxX2ZMY3uvuZGxzY5ZOsGC/vD3A/3smFtJt4/A==", "dev": true, "license": "MIT", "dependencies": { @@ -7784,6 +9682,8 @@ }, "node_modules/wrap-ansi": { "version": "7.0.0", + "resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz", + "integrity": "sha512-YVGIj2kamLSTxw6NsZjoBxfSwsn0ycdesmc4p+Q21c5zPuZ1pl+NfxVdxPtdHvmNVOQ6XSYG4AUtyt/Fi7D16Q==", "dev": true, "license": "MIT", "dependencies": { @@ -7798,8 +9698,17 @@ "url": "https://github.com/chalk/wrap-ansi?sponsor=1" } }, + "node_modules/wrappy": { + "version": "1.0.2", + "resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz", + "integrity": "sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==", + "dev": true, + "license": "ISC" + }, "node_modules/y18n": { "version": "5.0.8", + "resolved": "https://registry.npmjs.org/y18n/-/y18n-5.0.8.tgz", + "integrity": "sha512-0pfFzegeDWJHJIAmTLRP2DwHjdF5s7jo9tuztdQxAhINCdvS+3nGINqPd00AphqJR/0LhANUS6/+7SCb98YOfA==", "dev": true, "license": "ISC", "engines": { @@ -7808,11 +9717,15 @@ }, "node_modules/yallist": { "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", "dev": true, "license": "ISC" }, "node_modules/yargs": { "version": "17.7.2", + "resolved": "https://registry.npmjs.org/yargs/-/yargs-17.7.2.tgz", + "integrity": "sha512-7dSzzRQ++CKnNI/krKnYRV7JKKPUXMEh61soaHKg9mrWEhzFWhFnxPxGl+69cD1Ou63C13NUPCnmIcrvqCuM6w==", "dev": true, "license": "MIT", "dependencies": { @@ -7830,6 +9743,8 @@ }, "node_modules/yargs-parser": { "version": "21.1.1", + "resolved": "https://registry.npmjs.org/yargs-parser/-/yargs-parser-21.1.1.tgz", + "integrity": "sha512-tVpsJW7DdjecAiFpbIB1e3qxIQsE6NoPc5/eTdrbbIC4h0LVsWhnoa3g+m2HclBIujHzsxZ4VJVA+GUuc2/LBw==", "dev": true, "license": "ISC", "engines": { @@ -7838,6 +9753,8 @@ }, "node_modules/yocto-queue": { "version": "0.1.0", + "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz", + "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==", "dev": true, "license": "MIT", "engines": { @@ -7846,25 +9763,6 @@ "funding": { "url": "https://github.com/sponsors/sindresorhus" } - }, - "node_modules/zod": { - "version": "4.3.6", - "dev": true, - "license": "MIT", - "funding": { - "url": "https://github.com/sponsors/colinhacks" - } - }, - "node_modules/zod-validation-error": { - "version": "4.0.2", - "dev": true, - "license": "MIT", - "engines": { - "node": ">=18.0.0" - }, - "peerDependencies": { - "zod": "^3.25.0 || ^4.0.0" - } } } } diff --git a/package.json b/package.json index 1525380..000d436 100644 --- a/package.json +++ b/package.json @@ -16,39 +16,40 @@ "supabase:reset": "cd backend && supabase db reset" }, "dependencies": { - "@tailwindcss/vite": "^4.2.2", - "framer-motion": "^12.38.0", - "i18next": "^26.3.0", + "framer-motion": "^11.2.10", + "i18next": "^23.11.5", + "i18next-browser-languagedetector": "^8.0.0", "leaflet": "^1.9.4", - "lucide-react": "^1.16.0", - "onnxruntime-web": "^1.26.0", - "posthog-js": "^1.376.2", - "react": "^19.2.4", - "react-dom": "^19.2.4", - "react-hot-toast": "^2.6.0", - "react-i18next": "^17.0.8", - "react-joyride": "^3.1.0", - "react-leaflet": "^5.0.0", - "react-router-dom": "^7.14.0", - "tailwindcss": "^4.2.2" + "lucide-react": "^0.395.0", + "onnxruntime-web": "^1.18.0", + "posthog-js": "^1.141.0", + "react": "^18.3.1", + "react-dom": "^18.3.1", + "react-hot-toast": "^2.4.1", + "react-i18next": "^14.1.2", + "react-joyride": "^2.8.2", + "react-leaflet": "^4.2.1", + "react-router-dom": "^6.23.1" }, "devDependencies": { - "@eslint/js": "^9.39.4", - "@types/leaflet": "^1.9.21", - "@types/node": "^25.9.1", - "@types/react": "^19.2.14", - "@types/react-dom": "^19.2.3", - "@vitejs/plugin-react": "^6.0.1", - "concurrently": "^9.2.1", - "cross-env": "^10.1.0", - "eslint": "^9.39.4", - "eslint-plugin-react-hooks": "^7.0.1", - "eslint-plugin-react-refresh": "^0.5.2", - "globals": "^17.4.0", - "typescript": "~6.0.3", - "typescript-eslint": "^8.57.0", - "vite": "^8.0.1", - "vite-plugin-pwa": "^1.3.0", - "workbox-window": "^7.4.1" + "@types/leaflet": "^1.9.12", + "@types/node": "^20.14.2", + "@types/react": "^18.3.3", + "@types/react-dom": "^18.3.0", + "@tailwindcss/vite": "^4.0.0-alpha.13", + "tailwindcss": "^4.0.0-alpha.13", + "@vitejs/plugin-react": "^4.3.1", + "concurrently": "^8.2.2", + "cross-env": "^7.0.3", + "eslint": "^8.57.0", + "eslint-plugin-react-hooks": "^4.6.2", + "eslint-plugin-react": "^7.34.2", + "eslint-plugin-react-refresh": "^0.4.7", + "@typescript-eslint/eslint-plugin": "^6.21.0", + "@typescript-eslint/parser": "^6.21.0", + "typescript": "~5.3.3", + "vite": "^5.3.1", + "vite-plugin-pwa": "^0.20.0", + "workbox-window": "^7.1.0" } } diff --git a/src/App.tsx b/src/App.tsx index cf051cb..96ce0bc 100644 --- a/src/App.tsx +++ b/src/App.tsx @@ -58,4 +58,4 @@ useEffect(() => { ); -} \ No newline at end of file +} diff --git a/src/components/BottomNav.tsx b/src/components/BottomNav.tsx index db85f8f..f4b46dd 100644 --- a/src/components/BottomNav.tsx +++ b/src/components/BottomNav.tsx @@ -1,14 +1,17 @@ import { Link, useLocation } from 'react-router-dom'; +import { useTranslation } from 'react-i18next'; import { ScanLine, Map, Layers } from 'lucide-react'; -const navItems = [ - { to: '/scanner', icon: ScanLine, label: 'SCANNER' }, - { to: '/map', icon: Map, label: 'MAP' }, - { to: '/mode', icon: Layers, label: 'MODE' }, -]; - export default function BottomNav() { - const location = useLocation(); + const { t } = useTranslation(); + + const location = useLocation(); + + const navItems = [ + { to: '/scanner', icon: ScanLine, label: t('components.bottomNav.scanner') }, + { to: '/map', icon: Map, label: t('components.bottomNav.map') }, + { to: '/mode', icon: Layers, label: t('components.bottomNav.mode') }, + ]; return ( ); -} \ No newline at end of file +} diff --git a/src/components/OnboardingTour.tsx b/src/components/OnboardingTour.tsx index ecb37e0..2f75f27 100644 --- a/src/components/OnboardingTour.tsx +++ b/src/components/OnboardingTour.tsx @@ -1,23 +1,25 @@ -import { Joyride, type Step } from "react-joyride"; +import Joyride, { type Step } from "react-joyride"; +import { useTranslation } from 'react-i18next'; interface Props { run: boolean; } export default function OnboardingTour({ run }: Props) { + const { t } = useTranslation(); const steps: Step[] = [ { target: "body", - content: "Welcome to FreshScanAI! Let's take a quick tour.", + content: t('onboarding.welcome'), placement: "center", }, { target: "a[href='/scanner']", - content: "Use Scanner to analyze fish freshness.", + content: t('onboarding.scannerTip'), }, { target: "a[href='/map']", - content: "View market insights and trust map here.", + content: t('onboarding.mapTip'), }, ]; @@ -26,14 +28,25 @@ export default function OnboardingTour({ run }: Props) { steps={steps} run={run} continuous + showProgress styles={{ + options: { + zIndex: 10000, + primaryColor: "#eab308", + backgroundColor: "#111111", + textColor: "#ffffff", + arrowColor: "#111111", + }, + tooltip: { + borderRadius: 0, + }, tooltipContainer: { border: "3px solid #eab308", borderRadius: 0, boxShadow: "none", textAlign: "left", }, - buttonPrimary: { + buttonNext: { backgroundColor: "#eab308", color: "#000000", borderRadius: 0, @@ -44,18 +57,7 @@ export default function OnboardingTour({ run }: Props) { buttonSkip: { color: "#ffffff", }, - tooltip: { - borderRadius: 0, - }, - }} - options={{ - showProgress: true, - buttons: ["back", "close", "primary", "skip"], - primaryColor: "#eab308", - backgroundColor: "#111111", - textColor: "#ffffff", - zIndex: 10000, }} /> ); -} \ No newline at end of file +} diff --git a/src/components/PostHogPageView.tsx b/src/components/PostHogPageView.tsx index 96a43d3..dac4aa5 100644 --- a/src/components/PostHogPageView.tsx +++ b/src/components/PostHogPageView.tsx @@ -9,7 +9,8 @@ import { api, isAuthenticated } from '../lib/api'; * actually reloads between routes. */ export default function PostHogPageView() { - const location = useLocation(); + + const location = useLocation(); const posthog = usePostHog(); useEffect(() => { @@ -44,3 +45,4 @@ export default function PostHogPageView() { return null; } + diff --git a/src/fusionInference.js b/src/fusionInference.js index f9cc8ca..6d4739a 100644 --- a/src/fusionInference.js +++ b/src/fusionInference.js @@ -1,3 +1,4 @@ +// eslint-disable-next-line @typescript-eslint/ban-ts-comment // @ts-nocheck /** * Fish Freshness Fusion Inference Engine @@ -24,7 +25,6 @@ // --------------------------------------------------------------------------- const STREAM_A_CLASSES = ['C1 (Fresh)', 'C2 (Moderate)', 'C3 (Spoiled)']; -const STREAM_B_CLASSES = ['Fresh_Eyes', 'Fresh_Gills', 'Nonfresh_Eyes', 'Nonfresh_Gills']; const STREAM_A_INPUT_SIZE = { width: 224, height: 224 }; const STREAM_B_INPUT_SIZE = { width: 224, height: 224 }; @@ -88,22 +88,6 @@ function temperatureScale(logits, temperature) { return softmax(scaled); } -/** - * Element-wise weighted sum of probability arrays. - * @param {Array<{probs: number[], weight: number}>} streams - * @returns {number[]} fused probability vector - */ -function weightedFuse(streams) { - const len = streams[0].probs.length; - const out = new Array(len).fill(0); - for (const { probs, weight } of streams) { - for (let i = 0; i < len; i++) { - out[i] += probs[i] * weight; - } - } - return out; -} - /** * Map an argmax index to a human-readable label and confidence. * @param {number[]} probs diff --git a/src/i18n.ts b/src/i18n.ts new file mode 100644 index 0000000..f77f619 --- /dev/null +++ b/src/i18n.ts @@ -0,0 +1,32 @@ +// i18n.ts - Function for initializing and exporting the i18next instance + +import i18n from 'i18next'; +import { initReactI18next } from 'react-i18next'; +import LanguageDetector from 'i18next-browser-languagedetector'; + +// Import your translation files +import en from './i18n/locales/en.json'; +import hi from './i18n/locales/hi.json'; +import bn from './i18n/locales/bn.json'; + +i18n + .use(LanguageDetector) + .use(initReactI18next) + .init({ + resources: { + en: { translation: en }, + hi: { translation: hi }, + bn: { translation: bn }, + }, + fallbackLng: 'en', + debug: import.meta.env.DEV, + interpolation: { + escapeValue: false, // React already does escaping + }, + detection: { + order: ['localStorage', 'navigator'], + caches: ['localStorage'], + }, + }); + +export default i18n; diff --git a/src/i18n/i18n.ts b/src/i18n/i18n.ts new file mode 100644 index 0000000..849135b --- /dev/null +++ b/src/i18n/i18n.ts @@ -0,0 +1,26 @@ +import i18n from "i18next"; +import { initReactI18next } from "react-i18next"; +import LanguageDetector from "i18next-browser-languagedetector"; +import en from "./locales/en.json"; +import hi from "./locales/hi.json"; +import bn from "./locales/bn.json"; + +i18n + .use(LanguageDetector) + .use(initReactI18next) + .init({ + debug: import.meta.env.DEV, + fallbackLng: "en", + interpolation: { + escapeValue: false, // not needed for react as it escapes by default + }, + resources: { + en: { + translation: en, + }, + hi: { translation: hi }, + bn: { translation: bn }, + }, + }); + +export default i18n; \ No newline at end of file diff --git a/src/i18n/index.ts b/src/i18n/index.ts index f6dd995..e69de29 100644 --- a/src/i18n/index.ts +++ b/src/i18n/index.ts @@ -1,21 +0,0 @@ -import i18n from "i18next"; -import { initReactI18next } from "react-i18next"; - -import en from "./locales/en.json"; -import hi from "./locales/hi.json"; -import bn from "./locales/bn.json"; - -i18n.use(initReactI18next).init({ - resources: { - en: { translation: en }, - hi: { translation: hi }, - bn: { translation: bn } - }, - lng: "en", - fallbackLng: "en", - interpolation: { - escapeValue: false - } -}); - -export default i18n; \ No newline at end of file diff --git a/src/i18n/locales/bn.json b/src/i18n/locales/bn.json index 7e65852..b0cc658 100644 --- a/src/i18n/locales/bn.json +++ b/src/i18n/locales/bn.json @@ -1,8 +1,372 @@ { - "home": "হোম", - "scanner": "স্ক্যানার", - "trustMap": "ট্রাস্ট ম্যাপ", - "signin": "সাইন ইন / সাইন আপ", - "results": "ফলাফল", - "logout": "লগ আউট" -} \ No newline at end of file + "navbar": { + "home": "হোম", + "scanner": "স্ক্যানার", + "trustMap": "ট্রাস্ট ম্যাপ", + "signin": "সাইন ইন / সাইন আপ", + "results": "ফলাফল", + "logout": "লগ আউট", + "profile": "প্রোফাইল", + "theme": "থিম", + "devLogin": "ডেভ", + "terminateSession": "সেশন শেষ করুন (লগ আউট)", + "sessionTerminated": "সেশন শেষ করা হয়েছে", + "loginMobile": "লগইন" + }, + "landing": { + "heroLine1": "মাছের তাজা", + "heroLine2": "*উদ্দেশ্যমূলকভাবে মূল্যায়িত*", + "heroSubtitle": "উচ্চ আর্দ্রতা পরিবেশে রিয়েল-টাইম বায়োমার্কার বিশ্লেষণের জন্য প্রকৌশলী একাডেমিক-গ্রেড এআই দৃষ্টি।", + "heroDescription": "FreshScan AI বিশৃঙ্খল কাঁচাবাজারকে একটি সুবিন্যস্ত ও <1>স্বচ্ছ ইকোসিস্টেমে রূপান্তর করে।", + "inferenceSpeed": "অনুমান গতি", + "speedValue": "<50ms", + "biomarkerAccuracy": "বায়োমার্কার নির্ভুলতা", + "accuracyValue": "98.9%", + "beginAssessment": "মূল্যায়ন শুরু করুন", + "initializeSession": "সেশন শুরু করুন", + "coreModulesTitle": "মূল মডিউল", + "intelligenceFor": "বুদ্ধিমত্তা ডিজাইন করা হয়েছে", + "forThe": "জন্য", + "wetMarket": "ভেজা বাজার", + "moduleDescription": "তিনটি বিশেষায়িত এআই পাইপলাইন ভোক্তা হার্ডওয়্যারে ল্যাবরেটরি-গ্রেড তাজা বিশ্লেষণ প্রদান করতে একসাথে কাজ করে।", + "moduleLoaded": "মডিউল 0{{num}}: লোড করা হয়েছে", + "scanProtocolTitle": "স্ক্যান প্রোটোকল", + "stepsTo": "নিশ্চিততার জন্য তিন ধাপ", + "certainty": "নিশ্চিততা", + "faqTitle": "প্রোটোকল FAQ", + "frequentlyAsked": "প্রায়শই জিজ্ঞাসিত", + "questions": "প্রশ্ন", + "assessmentReady": "মূল্যায়ন প্রস্তুত", + "firstClass": "প্রথম শ্রেণী", + "assessment": "মূল্যায়ন", + "readyDescription": "সরাসরি আপনার মোবাইল ডিভাইসে ল্যাবরেটরি-গ্রেড তাজা বিশ্লেষণ স্থাপন করুন। কোন সাবস্ক্রিপশন নেই। কোন ক্লাউড নির্ভরতা নেই।", + "launchScanner": "স্ক্যানার চালু করুন", + "dualStreamTitle": "ডুয়াল-স্ট্রিম প্রসঙ্গ", + "dualStreamDesc": "উচ্চ আর্দ্রতা পরিবেশের জন্য বিশেষণ প্রতিফলন এবং জৈব টেক্সচারের সমসাময়িক প্রসেসিং।", + "explainableAITitle": "ব্যাখ্যাযোগ্য এআই", + "explainableAIDesc": "শুধুমাত্র একটি গ্রেডে বিশ্বাস করবেন না। গিল, চোখ এবং স্কেলে হাইলাইট করা চিহ্নগুলি রিয়েল-টাইমে দেখুন।", + "crowdsourcedTitle": "ক্রাউডসোর্সড ম্যাপ", + "crowdsourcedDesc": "অনাম ব্যবহারকারী মেটাডেটা দ্বারা চালিত স্থানীয় বাজারের জুড়ে লাইভ তাজা হিটম্যাপ।", + "scanBodyTitle": "শরীর স্ক্যান করুন", + "scanBodyDesc": "ক্যামেরাটি নমুনা থেকে 15cm দূরে রাখুন। পরিবেশ আলো বা বিল্ট-ইন স্ট্রোব ব্যবহার করুন।", + "targetBiomarkersTitle": "লক্ষ্য বায়োমার্কার", + "targetBiomarkersDesc": "এআই গিল স্যাচুরেশন, কর্নিয়াল স্বচ্ছতা এবং এপিডার্মাল টেনশন চিহ্নিত করে।", + "getGradeTitle": "গ্রেড পান", + "getGradeDesc": "সঞ্চয় সুপারিশগুলির সাথে তাৎক্ষণিক তাজা সূচক (0-100) উৎপাদিত।", + "faq": { + "q1": "ডুয়াল-স্ট্রিম এআই মডেলটি কিভাবে কাজ করে?", + "a1": "FreshScan সমান্তরালে দুটি বিশেষায়িত নিউরাল নেটওয়ার্ক ব্যবহার করে। স্ট্রিম A (MobileNetV2) পুরো মাছের দেহ বিশ্লেষণ করে এবং স্ট্রিম B (BiomarkerCNN) চোখ ও গিলের মতো ক্ষুদ্র অঞ্চল পরীক্ষা করে; তাদের আউটপুট মিলিয়ে চূড়ান্ত Freshness Index তৈরি করা হয়।", + "q2": "Freshness গ্রেডগুলোর মানে কী?", + "a2": "Freshness Index (0-100) গ্রেডে ম্যাপ করা হয়: A+ (≥92), A (≥80), B (≥65), C (≥50), D (<50)। উচ্চ স্কোর ভালো সংরক্ষণ ও দীর্ঘ নিরাপদ সংরক্ষণ নির্দেশ করে।", + "q3": "অটো-স্ক্যান মোড বনাম ম্যান্যুয়াল স্ক্যান কী?", + "a3": "অটো-স্ক্যান একটি ছবি নিয়ে স্বয়ংক্রিয়ভাবে ভ্যালিডেশন এবং উভয় স্ট্রিম চালায়। ম্যানুয়াল স্ক্যান আলাদা Body, Eye, এবং Gill ছবি আপলোড করে আরও বিস্তারিত মূল্যায়ন দেয়।", + "q4": "Grad-CAM ওভারলে কী?", + "a4": "Grad-CAM একটি হিটম্যাপ তৈরি করে যা চিত্রের সেই অংশগুলোকে হাইলাইট করে যা মডেলের পূর্বানুমানে প্রভাব ফেলেছে, যার ফলে আপনি দেখতে পারবেন কোন ফিচারগুলো গ্রেডে অবদান রেখেছে।", + "q5": "ট্রাস্ট ম্যাপ কী?", + "a5": "ট্রাস্ট ম্যাপ হলো অনানুমানিক স্ক্যান থেকে সংগৃহীত বিক্রেতাদের তাজা ডেটার লাইভ হিটম্যাপ, যা ধারাবাহিকভাবে উচ্চ মানের বিক্রেতাদের চিহ্নিত করতে সহায়তা করে।" + } + }, + "scanner": { + "cameraAccessNeeded": "ক্যামেরা অ্যাক্সেস প্রয়োজন", + "cameraPermissionDenied": "ক্যামেরা অনুমতি অস্বীকার করা হয়েছে", + "cameraNotFound": "এই ডিভাইসে কোনো ক্যামেরা পাওয়া যায়নি। একটি ক্যামেরা সংযোগ করুন এবং আবার চেষ্টা করুন।", + "cameraAccessError": "ক্যামেরা অ্যাক্সেস করতে অক্ষম। আপনার ব্রাউজার অনুমতি পরীক্ষা করুন এবং আবার চেষ্টা করুন।", + "cameraSomethingWrong": "ক্যামেরা অ্যাক্সেস করার সময় কিছু ভুল হয়েছে।", + "cameraInstructions": "আপনার ব্রাউজারের ঠিকানা বারে ক্যামেরা আইকন ক্লিক করুন, ক্যামেরা অ্যাক্সেসের অনুমতি দিন এবং পৃষ্ঠা রিফ্রেশ করুন।", + "failedCaptureFrame": "ফ্রেম ক্যাপচার করতে ব্যর্থ।", + "modeEdgeOnnx": "মোড: EDGE ONNX", + "runningLocalInference": "স্থানীয় অনুমান চলছে...", + "modeCloudApi": "মোড: CLOUD API", + "connectingToHf": "HF-তে সংযোগ করছে...", + "detectingModel": "মডেল সনাক্ত করছে...", + "pleaseWait": "অনুগ্রহ করে অপেক্ষা করুন", + "modelEdgeOnnx": "মডেল: EDGE ONNX", + "deviceOnDevice": "ডিভাইস: ON DEVICE", + "latencyValue": "লেটেন্সি: <50ms", + "modelCloudApi": "মডেল: CLOUD API", + "deviceHfInference": "ডিভাইস: HF INFERENCE", + "scanSeqFailed": "SCAN SEQ: ব্যর্থ", + "checkSpecimen": "নমুনা পরীক্ষা করুন", + "systemReady": "সিস্টেম: প্রস্তুত", + "pointCameraAtFish": "ক্যামেরাটি মাছের দিকে নির্দেশ করুন", + "fresh": "তাজা", + "moderate": "মাঝারি", + "spoiled": "নষ্ট", + "pointAtFish": "মাছের দিকে নির্দেশ করুন", + "analyzingBiomarkers": "বায়োমার্কার বিশ্লেষণ করছে", + "gradePrefix": "গ্রেড ", + "runningEdgeInference": "এজ অনুমান চলছে...", + "runningCloudInference": "ক্লাউড অনুমান চলছে...", + "freshnessIndex": "তাজা সূচক", + "viewAnalysisButton": "বিশ্লেষণ দেখুন", + "copiedToClipboard": "ক্লিপবোর্ডে অনুলিপি করা হয়েছে", + "shareGradeReport": "গ্রেড-এ রিপোর্ট শেয়ার করুন", + "captureButton": "মাছ ক্যাপচার করুন", + "switchCamera": "ক্যামেরা স্যুইচ করুন", + "uploadButton": "ছবি আপলোড করুন", + "notFishDetected": "মাছ নয়: কোনো মাছ সনাক্ত করা হয়নি। একটি মাছের ছবি আপলোড করুন।", + "inferenceFailed": "অনুমান ব্যর্থ।", + "capturedAlt": "ক্যাপচার করা হয়েছে", + "rejectedUploadAlt": "আপলোড প্রত্যাখ্যাত করা হয়েছে" + }, + "dashboard": { + "loadingAnalysis": "বিশ্লেষণ লোড হচ্ছে...", + "fetchingResult": "ফলাফল আনছে", + "loadFailed": "লোড ব্যর্থ", + "noData": "কোনো ডেটা নেই", + "noDataMessage": "কোনো স্ক্যান ডেটা উপলব্ধ নেই। প্রথম একটি স্ক্যান চালান।", + "goToScanner": "স্ক্যানারে যান", + "backToScanner": "স্ক্যানারে ফিরে যান", + "analysisComplete": "বিশ্লেষণ সম্পূর্ণ", + "specimenLabel": "নমুনা: ", + "scanIdLabel": "স্ক্যান ID: ", + "gradeLabel": "গ্রেড ", + "freshnessIndexLabel": "তাজা সূচক", + "scorePercentage": "/100", + "classificationLabel": "শ্রেণীবিভাগ: ", + "confidenceLabel": "আত্মবিশ্বাস: ", + "percentageSymbol": "%", + "lowConfidence": "কম আত্মবিশ্বাস", + "highConfidence": "উচ্চ আত্মবিশ্বাস", + "detectedSpecimen": "সনাক্ত নমুনা", + "weightEst": "ওজন অনুমান", + "kilogramUnit": "কেজি", + "catchAge": "ধরা বয়স", + "hoursUnit": "ঘণ্টা", + "marketLabel": "বাজার", + "biomarkerAnalysis": "বায়োমার্কার বিশ্লেষণ", + "cautionLabel": "সতর্কতা", + "storageRecommendations": "সঞ্চয় সুপারিশ", + "consumeWithin": "মধ্যে খরচ করুন", + "consumeHours": "ঘণ্টা", + "discardAction": "ত্যাগ করুন", + "storageTemp": "সঞ্চয় তাপমাত্রা", + "alertLabel": "সতর্কতা", + "newScanButton": "নতুন স্ক্যান", + "viewHistoryButton": "ইতিহাস দেখুন" + }, + "auth": { + "authInitiated": "প্রমাণীকরণ শুরু করা হয়েছে", + "redirectingToOauth": "OAuth-তে পুনর্নির্দেশ করছে...", + "authError": "প্রমাণীকরণ ত্রুটি", + "retryRequired": "পুনরায় চেষ্টা প্রয়োজন", + "authenticationTitle": "প্রমাণীকরণ", + "protocolOauth": "প্রোটোকল: OAUTH-SECURE", + "authWatermark": "প্রমাণীকরণ", + "freshscanBrand": "FreshScan ", + "aiBrand": "AI", + "authFailed": "প্রমাণীকরণ ব্যর্থ। আবার চেষ্টা করুন।", + "authSubtitle": "আপনার লাইভ ট্রাস্ট ম্যাপ দেখতে এবং ডিভাইস জুড়ে বায়োমার্কার ডেটা সিঙ্ক করতে সাইন ইন করুন।", + "loadingVerification": "যাচাইকরণ চ্যালেঞ্জ লোড করছে...", + "continueWithGoogle": "Google দিয়ে চালিয়ে যান", + "authenticating": "প্রমাণীকরণ করছে...", + "devLoginBypass": "DEV LOGIN — BYPASS OAUTH", + "localOnlyNote": "[শুধুমাত্র স্থানীয়]" + }, + "results": { + "loadingHistory": "ইতিহাস লোড হচ্ছে...", + "queryingDb": "ডেটাবেস অনুসন্ধান করছে", + "historyLoadFailed": "ইতিহাস লোড ব্যর্থ", + "failedToLoadHistory": "ইতিহাস লোড করতে ব্যর্থ।", + "signInRequired": "সাইন ইন প্রয়োজনীয়", + "scanHistoryTerminal": "স্ক্যান ইতিহাস", + "totalPrefix": "মোট: ", + "avgScorePrefix": "গড় স্কোর: ", + "scanTitle": "স্ক্যান ", + "resultsTitle": "ফলাফল", + "totalScans": "মোট স্ক্যান", + "avgFreshness": "গড় তাজা", + "freshRate": "তাজা হার", + "percentageSymbol": "%", + "noScansFound": "কোনো স্ক্যান পাওয়া যায়নি", + "runFirstScan": "প্রথম স্ক্যান চালান", + "initiateFirstScan": "প্রথম স্ক্যান শুরু করুন" + }, + "marketMap": { + "failedLoadMarketData": "লাইভ বাজার ডেটা লোড করতে ব্যর্থ।", + "liveGps": "লাইভ জিপিএস", + "trustMapTerminal": "ট্রাস্ট ম্যাপ", + "regionPrefix": "অঞ্চল: ", + "syncingDb": "ডেটাবেস সিঙ্ক করছে...", + "loadError": "লোড ত্রুটি", + "nodesPrefix": "নোড: ", + "marketTrustTitle": "বাজার বিশ্বাস ", + "mapTitle": "ম্যাপ", + "leaderboardLink": "লিডারবোর্ড", + "selectMarketNode": "বাজার নোড নির্বাচন করুন", + "highTrust": "উচ্চ (85+)", + "mediumTrust": "মাঝারি (70-84)", + "lowTrust": "কম (<70)", + "geolocationDenied": "ভূ-অবস্থান অস্বীকার করা হয়েছে বা ব্যর্থ হয়েছে, মক ডেটায় ফিরে যাচ্ছে।", + "failedLoadMarkets": "বাজার লোড করতে ব্যর্থ।", + "vendorsLabel": "বিক্রেতা", + "avgFreshness": "গড় তাজা", + "scorePrefix": "স্কোর: ", + "vendorsPrefix": "বিক্রেতা: " + }, + "leaderboard": { + "failedFetchLeaderboard": "লিডারবোর্ড আনতে ব্যর্থ।", + "vendorTrustLeaderboard": "বিক্রেতা বিশ্বাস লিডারবোর্ড", + "vendorSubtitle": "বাজার জুড়ে অনাম তাজা স্ক্যানের উপর ভিত্তি করে র‍্যাঙ্কিং", + "noVendorData": "এখনো কোনো বিক্রেতা ডেটা নেই।", + "goldBadge": "[ সোনা ]", + "silverBadge": "[ রূপা ]", + "bronzeBadge": "[ ব্রোঞ্জ ]", + "unrankedBadge": "[ অর‍্যাঙ্কড ]", + "improving": "উন্নতি করছে", + "declining": "হ্রাস পাচ্ছে", + "stable": "স্থির", + "scorePercentage": "/100", + "scansLabel": "স্ক্যান", + "scans": "স্ক্যান", + "subtitle": "উপশিরোনাম", + "title": "শিরোনাম" + }, + "modeSelect": { + "individual": { + "title": "ব্যক্তিগত স্ক্যান", + "code": "মোড একক", + "desc": "একটি একক নমুনার পয়েন্ট-বিশ্লেষণ। খুচরা ভোক্তাদের জন্য ব্যক্তিগত ক্রয় গুণমান যাচাই করার জন্য অনুকূল।", + "stat": "গড় সময়: 2.3s" + }, + "batch": { + "title": "ব্যাচ মূল্যায়ন", + "code": "মোড ব্যাচ", + "desc": "ডিসপ্লে জুড়ে মাল্টি-নমুনা সুইপ। পাইকারি ক্রেতাদের জন্য প্রতি সেশনে 20+ ইউনিট প্রক্রিয়াকরণের জন্য ডিজাইন করা হয়েছে।", + "stat": "থ্রু পুট: 12/মিনিট" + }, + "survey": { + "title": "বাজার সার্ভে", + "code": "মোড সার্ভে", + "desc": "ক্রাউডসোর্সড ট্রাস্ট ম্যাপে অবদান রাখুন। একটি সম্পূর্ণ বাজার স্টল জরিপ করুন এবং অনাম তাজা ডেটা জমা দিন।", + "stat": "ডেটা পয়েন্ট: 47.2K" + }, + "gradcamTitle": "গ্র্যাড-ক্যাম ভিউয়ার", + "xaiModule": "XAI মডিউল", + "classificationFresh": "তাজা", + "classificationModerate": "মাঝারি", + "classificationSpoiled": "নষ্ট", + "demoMode": "ডেমো মোড", + "operationMode": "অপারেশন মোড", + "selectProtocol": "প্রোটোকল নির্বাচন করুন", + "awaitingInput": "ইনপুট অপেক্ষা করছে...", + "selectOperation": "অপারেশন মোড নির্বাচন করুন", + "mode": "মোড", + "description": "একটি স্ক্যানিং প্রোটোকল বাছুন অথবা মডেলের আচরণ বুঝতে এক্সপ্লেইনেবিলিটি টুলকিট ব্যবহার করুন।", + "explainability": "ব্যাখ্যাযোগ্যতা", + "toolkit": "টুলকিট", + "gradcamSectionDescription": "মডেল কী দেখে তা বুঝুন। গ্রেডিয়েন্ট-ওয়েটেড ক্লাস অ্যাক্টিভেশন ম্যাপ (গ্র্যাড-ক্যাম) হিটম্যাপ তৈরি করতে যেকোনো মাছের ছবি আপলোড করুন।", + "allModulesLoaded": "সমস্ত মডিউল লোড হয়েছে", + "gpuAccelOn": "GPU ত্বরণ: চালু", + "gradcamViewerTitle": "গ্র্যাড-ক্যাম ভিউয়ার", + "gradcamDescription": "স্ট্রিম এ নিউরাল নেটওয়ার্কটি সতেজতা শ্রেণীবিভাগের জন্য কোন অঞ্চলে ফোকাস করে তা দেখতে একটি মাছের ছবি আপলোড করুন।", + "clickToUpload": "আপলোড করতে ক্লিক করুন", + "orDragDrop": "বা টেনে আনুন", + "acceptedFormats": "JPEG · PNG · WebP — যেকোনো রেজোলিউশন" + }, + "gradcam": { + "invalidFileError": "অনুগ্রহ করে একটি বৈধ চিত্র ফাইল আপলোড করুন (JPEG / PNG / WebP)।", + "generationFailedError": "গ্র্যাড-ক্যাম তৈরি ব্যর্থ হয়েছে।", + "runningForwardPass": "ফরওয়ার্ড পাস চলছে", + "computingGradients": "গ্রেডিয়েন্ট গণনা করছে", + "renderingHeatmap": "হীটম্যাপ রেন্ডারিং করছে", + "rejectedUploadAlt": "প্রত্যাখ্যাত আপলোড", + "notAFishDetected": "মাছ সনাক্ত নয়", + "notAFishText": "আপলোড করা চিত্রে কোনো মাছ দেখা যাচ্ছে না। একটি মাছের শরীর, চোখ বা গিলের স্পষ্ট ছবি আপলোড করুন।", + "tryAgain": "পুনরায় চেষ্টা করুন", + "uploadDifferentImage": "বিভিন্ন চিত্র আপলোড করুন", + "originalInput": "মূল ইনপুট", + "originalImageAlt": "মূল আপলোড করা চিত্র", + "activationMap": "অ্যাক্টিভেশন ম্যাপ", + "heatmapAlt": "গ্র্যাড-ক্যাম হিটম্যাপ ওভারলে", + "streamA": "স্ট্রিম এ", + "synthetic": "সিন্থেটিক", + "lowToHigh": "কম → উচ্চ", + "uploadNewImage": "নতুন ছবি আপলোড করুন" + }, + "publicReport": { + "errorCode": "ত্রুটি: 404", + "reportNotFound": "রিপোর্ট পাওয়া যায়নি", + "verifyScanId": "স্ক্যান ID যাচাই করুন", + "fetchingData": "ডেটা আনছে", + "standby": "প্রস্তুত...", + "freshscanBrand": "FreshScan ", + "publicReport": "জনসাধারণ রিপোর্ট", + "generatedPrefix": "উৎপাদিত: ", + "idPrefix": "ID: ", + "freshnessScore": "তাজা স্কোর", + "gradeBadge": "গ্রেড ", + "separator": "—", + "rawMarkers": "কাঁচা চিহ্ন", + "copiedClipboard": "ক্লিপবোর্ডে অনুলিপি করা হয়েছে", + "copyShareLink": "শেয়ার লিংক কপি করুন", + "printSavePdf": "প্রিন্ট বা PDF সংরক্ষণ করুন", + "notFound": "পাওয়া যায়নি" + }, + "notFound": { + "errorCode": "404", + "pageNotFound": "পৃষ্ঠা পাওয়া যায়নি", + "errorMessage": "আপস! আপনি যে পৃষ্ঠাটি খুঁজছেন তা বিদ্যমান নেই বা সরানো হয়েছে।", + "returnHome": "হোমে ফিরে যান" + }, + "components": { + "bottomNav": { + "scanner": "স্ক্যানার", + "map": "ম্যাপ", + "mode": "মোড" + }, + "footer": { + "freshscanAi": "FreshScan AI", + "copyright": "© 2026 FreshScan AI. সর্বাধিকার সংরক্ষিত। নির্ভুল বুদ্ধিমত্তা।" + }, + "layout": { + "watermark": "FS AI" + }, + "installPrompt": { + "iosMessage": "এক-ট্যাপ মাছ তাজা বিশ্লেষণের জন্য আপনার হোম স্ক্রীনে FreshScan AI যোগ করুন। শেয়ার করুন এবং হোম স্ক্রীনে যোগ করুন নির্বাচন করুন।", + "androidMessage": "তাৎক্ষণিক মাছ তাজা বিশ্লেষণের জন্য আপনার হোম স্ক্রীনে FreshScan AI যোগ করুন।", + "appName": "FreshScan AI", + "promptTitle": "অ্যাপ ইনস্টল করুন", + "installButton": "ইনস্টল করুন", + "notNowButton": "এখন নয়", + "appImageAlt": "FreshScan AI", + "installedConsole": "ব্যবহারকারী PWA ইনস্টল করেছে!", + "dismissedConsole": "ব্যবহারকারী ইনস্টল সংলাপ খারিজ করেছে।", + "errorConsole": "ইনস্টল প্রম্পট ট্রিগার করতে ত্রুটি:" + }, + "onboardingTour": { + "welcomeMessage": "FreshScanAI-তে স্বাগতম! দ্রুত ট্যুর চলতে দিন।", + "scannerStep": "মাছের তাজা বিশ্লেষণ করতে স্ক্যানার ব্যবহার করুন।", + "mapStep": "এখানে বাজার অন্তর্দৃষ্টি এবং ট্রাস্ট ম্যাপ দেখুন।" + }, + "posthog": { + "identifyError": "ব্যাকএন্ডের সাথে ব্যবহারকারী সনাক্ত করতে ব্যর্থ" + } + }, + "common": { + "error": "ত্রুটি", + "loading": "লোড হচ্ছে", + "success": "সাফল্য", + "warning": "সতর্কতা", + "alert": "সতর্কতা", + "tryAgain": "পুনরায় চেষ্টা করুন", + "reset": "রিসেট", + "cancel": "বাতিল করুন", + "confirm": "নিশ্চিত করুন", + "save": "সংরক্ষণ করুন", + "delete": "মুছে ফেলুন", + "close": "বন্ধ করুন", + "ok": "ঠিক আছে" + }, + "error": { + "network": { + "connection": "সংযোগ ব্যর্থ হয়েছে। অনুগ্রহ করে আপনার ইন্টারনেট পরীক্ষা করুন এবং আবার চেষ্টা করুন।", + "server": "সার্ভারের সাথে সংযোগ করতে অক্ষম। অনুগ্রহ করে আপনার ইন্টারনেট সংযোগ পরীক্ষা করুন।" + }, + "auth": { + "supabaseConfig": "প্রমাণীকরণ ব্যর্থ: সার্ভারটি ভুলভাবে কনফিগার করা হয়েছে। অনুগ্রহ করে সহায়তার সাথে যোগাযোগ করুন।" + }, + "unknown": "একটি অপ্রত্যাশিত ত্রুটি ঘটেছে। অনুগ্রহ করে আবার চেষ্টা করুন।", + "serverError": "সার্ভার ত্রুটি। অনুগ্রহ করে পরে আবার চেষ্টা করুন।" + } +} diff --git a/src/i18n/locales/en.json b/src/i18n/locales/en.json index 2a088df..4368f0f 100644 --- a/src/i18n/locales/en.json +++ b/src/i18n/locales/en.json @@ -1,8 +1,372 @@ { - "home": "HOME", - "scanner": "SCANNER", - "trustMap": "TRUST MAP", - "signin": "SIGN IN / SIGN UP", - "results": "RESULTS", - "logout": "LOGOUT" -} \ No newline at end of file + "navbar": { + "home": "HOME", + "scanner": "SCANNER", + "trustMap": "TRUST MAP", + "signin": "SIGN IN / SIGN UP", + "results": "RESULTS", + "logout": "LOGOUT", + "profile": "Profile", + "theme": "THEME", + "devLogin": "DEV", + "terminateSession": "TERMINATE SESSION (LOGOUT)", + "sessionTerminated": "SESSION TERMINATED", + "loginMobile": "LOGIN" + }, + "landing": { + "heroLine1": "Fish Freshness", + "heroLine2": "*Objectively Graded*", + "heroSubtitle": "Academic-grade AI vision engineered for real-time biomarker analysis in high-humidity environments.", + "heroDescription": "FreshScan AI transforms the chaotic wet market into a structured, <1>transparent ecosystem.", + "inferenceSpeed": "Inference Speed", + "speedValue": "<50ms", + "biomarkerAccuracy": "Biomarker Accuracy", + "accuracyValue": "98.9%", + "beginAssessment": "BEGIN ASSESSMENT", + "initializeSession": "INITIALIZE SESSION", + "coreModulesTitle": "CORE MODULES", + "intelligenceFor": "Intelligence designed", + "forThe": "for the", + "wetMarket": "wet market", + "moduleDescription": "Three specialized AI pipelines working in concert to deliver laboratory-grade freshness analysis on consumer hardware.", + "moduleLoaded": "MODULE 0{{num}}: LOADED", + "scanProtocolTitle": "SCAN PROTOCOL", + "stepsTo": "Three steps to", + "certainty": "certainty", + "faqTitle": "PROTOCOL FAQ", + "frequentlyAsked": "Frequently Asked", + "questions": "Questions", + "assessmentReady": "ASSESSMENT READY", + "firstClass": "First Class", + "assessment": "Assessment", + "readyDescription": "Deploy laboratory-grade freshness analysis directly to your mobile device. No subscription. No cloud dependency.", + "launchScanner": "LAUNCH SCANNER", + "dualStreamTitle": "Dual-Stream Context", + "dualStreamDesc": "Simultaneous processing of specular reflection and biological texture for high-humidity environments.", + "explainableAITitle": "Explainable AI", + "explainableAIDesc": "Don't just trust a grade. See highlighted markers on the gills, eyes, and scales in real-time.", + "crowdsourcedTitle": "Crowdsourced Map", + "crowdsourcedDesc": "Live freshness heatmaps across local markets powered by anonymized user metadata.", + "scanBodyTitle": "Scan Body", + "scanBodyDesc": "Position camera 15cm from specimen. Use ambient light or built-in strobe.", + "targetBiomarkersTitle": "Target Biomarkers", + "targetBiomarkersDesc": "AI identifies gill saturation, corneal clarity, and epidermal tension.", + "getGradeTitle": "Get Grade", + "getGradeDesc": "Instant Freshness Index (0-100) generated with storage recommendations.", + "faq": { + "q1": "How does the dual-stream AI model work?", + "a1": "FreshScan uses two specialized neural networks in parallel. Stream A (MobileNetV2) analyzes the full fish body for overall freshness classification while Stream B (BiomarkerCNN) inspects micro-regions like eyes and gills. Their outputs are fused to produce the final Freshness Index.", + "q2": "What do the freshness grades mean?", + "a2": "The Freshness Index (0-100) maps to letter grades: A+ (≥92), A (≥80), B (≥65), C (≥50), D (<50). Higher scores indicate better preservation and longer safe storage windows.", + "q3": "What is Auto-Scan mode vs. manual scan?", + "a3": "Auto-Scan accepts a single photo and runs validation and both model streams automatically. Manual scan allows uploading separate Body, Eye, and Gill images for a more granular assessment.", + "q4": "What is the Grad-CAM overlay?", + "a4": "Grad-CAM produces a heatmap that highlights image regions that influenced the model's prediction, helping you see which features (gills, eyes, scales) contributed most to the grade.", + "q5": "What is the Trust Map?", + "a5": "The Trust Map is a live, crowdsourced heatmap of vendor freshness aggregated from anonymized scans, helping you find consistently high-quality sellers." + } + }, + "scanner": { + "cameraAccessNeeded": "Camera Access Needed", + "cameraPermissionDenied": "Camera permission was denied", + "cameraNotFound": "No camera was found on this device. Please connect a camera and try again.", + "cameraAccessError": "Unable to access the camera. Please check your browser permissions and try again.", + "cameraSomethingWrong": "Something went wrong while accessing the camera.", + "cameraInstructions": "Click the camera icon in your browser's address bar, allow camera access, and refresh the page.", + "failedCaptureFrame": "Failed to capture frame.", + "modeEdgeOnnx": "MODE: EDGE ONNX", + "runningLocalInference": "RUNNING LOCAL INFERENCE...", + "modeCloudApi": "MODE: CLOUD API", + "connectingToHf": "CONNECTING TO HF...", + "detectingModel": "DETECTING MODEL...", + "pleaseWait": "PLEASE WAIT", + "modelEdgeOnnx": "MODEL: EDGE ONNX", + "deviceOnDevice": "DEVICE: ON DEVICE", + "latencyValue": "LATENCY: <50ms", + "modelCloudApi": "MODEL: CLOUD_API", + "deviceHfInference": "DEVICE: HF INFERENCE", + "scanSeqFailed": "SCAN SEQ: FAILED", + "checkSpecimen": "CHECK SPECIMEN", + "systemReady": "SYSTEM: READY", + "pointCameraAtFish": "POINT CAMERA AT FISH", + "fresh": "Fresh", + "moderate": "Moderate", + "spoiled": "Spoiled", + "pointAtFish": "POINT AT FISH", + "analyzingBiomarkers": "ANALYZING BIOMARKERS", + "gradePrefix": "GRADE ", + "runningEdgeInference": "RUNNING EDGE INFERENCE...", + "runningCloudInference": "RUNNING CLOUD INFERENCE...", + "freshnessIndex": "FRESHNESS INDEX", + "viewAnalysisButton": "VIEW ANALYSIS", + "copiedToClipboard": "COPIED TO CLIPBOARD", + "shareGradeReport": "SHARE GRADE-A REPORT", + "captureButton": "CAPTURE FISH", + "switchCamera": "Switch camera", + "uploadButton": "UPLOAD PHOTO", + "notFishDetected": "NOT A FISH: No fish detected. Please photograph a fish.", + "inferenceFailed": "Inference failed.", + "capturedAlt": "Captured", + "rejectedUploadAlt": "Rejected upload" + }, + "dashboard": { + "loadingAnalysis": "LOADING ANALYSIS...", + "fetchingResult": "FETCHING RESULT", + "loadFailed": "LOAD FAILED", + "noData": "NO DATA", + "noDataMessage": "No scan data available. Run a scan first.", + "goToScanner": "GO TO SCANNER", + "backToScanner": "BACK TO SCANNER", + "analysisComplete": "ANALYSIS COMPLETE", + "specimenLabel": "SPECIMEN: ", + "scanIdLabel": "SCAN ID: ", + "gradeLabel": "GRADE ", + "freshnessIndexLabel": "Freshness Index", + "scorePercentage": "/100", + "classificationLabel": "CLASSIFICATION: ", + "confidenceLabel": "CONFIDENCE: ", + "percentageSymbol": "%", + "lowConfidence": "LOW CONFIDENCE", + "highConfidence": "HIGH CONFIDENCE", + "detectedSpecimen": "Detected Specimen", + "weightEst": "WEIGHT EST", + "kilogramUnit": "kg", + "catchAge": "CATCH AGE", + "hoursUnit": "hrs", + "marketLabel": "MARKET", + "biomarkerAnalysis": "BIOMARKER ANALYSIS", + "cautionLabel": "CAUTION", + "storageRecommendations": "STORAGE RECOMMENDATIONS", + "consumeWithin": "CONSUME WITHIN", + "consumeHours": "HRS", + "discardAction": "DISCARD", + "storageTemp": "STORAGE TEMP", + "alertLabel": "ALERT", + "newScanButton": "NEW SCAN", + "viewHistoryButton": "VIEW HISTORY" + }, + "auth": { + "authInitiated": "AUTH INITIATED", + "redirectingToOauth": "REDIRECTING TO OAUTH...", + "authError": "AUTH ERROR", + "retryRequired": "RETRY REQUIRED", + "authenticationTitle": "AUTHENTICATION", + "protocolOauth": "PROTOCOL: OAUTH-SECURE", + "authWatermark": "AUTH", + "freshscanBrand": "FRESHSCAN ", + "aiBrand": "AI", + "authFailed": "Authentication failed. Please try again.", + "authSubtitle": "Sign in to view your live Trust Map and sync biomarker data across devices.", + "loadingVerification": "Loading verification challenge...", + "continueWithGoogle": "CONTINUE WITH GOOGLE", + "authenticating": "AUTHENTICATING...", + "devLoginBypass": "DEV LOGIN — BYPASS OAUTH", + "localOnlyNote": "[local only]" + }, + "results": { + "loadingHistory": "LOADING HISTORY...", + "queryingDb": "QUERYING DB", + "historyLoadFailed": "HISTORY LOAD FAILED", + "failedToLoadHistory": "Failed to load history.", + "signInRequired": "SIGN IN REQUIRED", + "scanHistoryTerminal": "SCAN HISTORY", + "totalPrefix": "TOTAL: ", + "avgScorePrefix": "AVG SCORE: ", + "scanTitle": "Scan ", + "resultsTitle": "Results", + "totalScans": "TOTAL SCANS", + "avgFreshness": "AVG FRESHNESS", + "freshRate": "FRESH RATE", + "percentageSymbol": "%", + "noScansFound": "NO SCANS FOUND", + "runFirstScan": "RUN FIRST SCAN", + "initiateFirstScan": "INITIATE FIRST SCAN" + }, + "marketMap": { + "failedLoadMarketData": "Failed to load live market data.", + "liveGps": "LIVE GPS", + "trustMapTerminal": "TRUST MAP", + "regionPrefix": "REGION: ", + "syncingDb": "SYNCING DB...", + "loadError": "LOAD ERROR", + "nodesPrefix": "NODES: ", + "marketTrustTitle": "Market Trust ", + "mapTitle": "Map", + "leaderboardLink": "LEADERBOARD", + "selectMarketNode": "Select Market Mode", + "highTrust": "HIGH (85+)", + "mediumTrust": "MED (70-84)", + "lowTrust": "LOW (<70)", + "geolocationDenied": "Geolocation denied or failed, falling back to mock data.", + "failedLoadMarkets": "Failed to load markets.", + "vendorsLabel": "VENDORS", + "avgFreshness": "AVG FRESHNESS", + "scorePrefix": "SCORE: ", + "vendorsPrefix": "VENDORS: " + }, + "leaderboard": { + "failedFetchLeaderboard": "Failed to fetch leaderboard.", + "vendorTrustLeaderboard": "VENDOR TRUST LEADERBOARD", + "vendorSubtitle": "RANKINGS BASED ON ANONYMOUS FRESHNESS SCANS ACROSS MARKETS", + "noVendorData": "NO VENDOR DATA YET.", + "goldBadge": "[ GOLD ]", + "silverBadge": "[ SILVER ]", + "bronzeBadge": "[ BRONZE ]", + "unrankedBadge": "[ UNRANKED ]", + "improving": "Improving", + "declining": "Declining", + "stable": "Stable", + "scorePercentage": "/100", + "scansLabel": "SCANS", + "scans": "Scans", + "subtitle": "Subtitle", + "title": "Title" + }, + "modeSelect": { + "individual": { + "title": "Individual Scan", + "code": "MODE SINGLE", + "desc": "Point-and-analyze a single specimen. Optimal for retail consumers verifying individual purchase quality.", + "stat": "AVG TIME: 2.3s" + }, + "batch": { + "title": "Batch Assessment", + "code": "MODE BATCH", + "desc": "Multi-specimen sweep across a display. Designed for wholesale buyers processing 20+ units per session.", + "stat": "THROUGHPUT: 12/min" + }, + "survey": { + "title": "Market Survey", + "code": "MODE SURVEY", + "desc": "Contribute to the crowdsourced Trust Map. Survey an entire market stall and submit anonymized freshness data.", + "stat": "DATA POINTS: 47.2K" + }, + "gradcamTitle": "Grad-CAM Viewer", + "xaiModule": "XAI MODULE", + "classificationFresh": "FRESH", + "classificationModerate": "MODERATE", + "classificationSpoiled": "SPOILED", + "demoMode": "DEMO MODE", + "operationMode": "OPERATION MODE", + "selectProtocol": "SELECT PROTOCOL", + "awaitingInput": "AWAITING INPUT...", + "selectOperation": "Select Operation Mode", + "mode": "Mode", + "description": "Choose a scanning protocol or use the Explainability Toolkit to understand model behavior.", + "explainability": "Explainability", + "toolkit": "Toolkit", + "gradcamSectionDescription": "Understand what the model sees. Upload any fish photo to generate a Gradient-weighted Class Activation Map (Grad-CAM) heatmap.", + "allModulesLoaded": "ALL MODULES LOADED", + "gpuAccelOn": "GPU ACCEL: ON", + "gradcamViewerTitle": "Grad-CAM Viewer", + "gradcamDescription": "Upload a fish image to visualise which regions the Stream A neural network focuses on for freshness classification.", + "clickToUpload": "Click to upload", + "orDragDrop": "or drag & drop", + "acceptedFormats": "JPEG · PNG · WebP — any resolution" + }, + "gradcam": { + "invalidFileError": "Please upload a valid image file (JPEG / PNG / WebP).", + "generationFailedError": "Grad-CAM generation failed.", + "runningForwardPass": "RUNNING FORWARD PASS", + "computingGradients": "COMPUTING GRADIENTS", + "renderingHeatmap": "RENDERING HEATMAP", + "rejectedUploadAlt": "Rejected upload", + "notAFishDetected": "NOT A FISH DETECTED", + "notAFishText": "The uploaded image does not appear to contain a fish. Please upload a clear photo of a fish body, eye, or gill.", + "tryAgain": "Try again", + "uploadDifferentImage": "UPLOAD DIFFERENT IMAGE", + "originalInput": "ORIGINAL INPUT", + "originalImageAlt": "Original uploaded image", + "activationMap": "ACTIVATION MAP", + "heatmapAlt": "Grad-CAM heatmap overlay", + "streamA": "STREAM A", + "synthetic": "SYNTHETIC", + "lowToHigh": "Low → High", + "uploadNewImage": "UPLOAD NEW IMAGE" + }, + "publicReport": { + "errorCode": "ERROR: 404", + "reportNotFound": "REPORT NOT FOUND", + "verifyScanId": "VERIFY SCAN ID", + "fetchingData": "FETCHING DATA", + "standby": "STANDBY...", + "freshscanBrand": "FreshScan ", + "publicReport": "Public Report", + "generatedPrefix": "GENERATED: ", + "idPrefix": "ID: ", + "freshnessScore": "FRESHNESS SCORE", + "gradeBadge": "GRADE ", + "separator": "—", + "rawMarkers": "RAW MARKERS", + "copiedClipboard": "COPIED TO CLIPBOARD", + "copyShareLink": "COPY SHARE LINK", + "printSavePdf": "PRINT / SAVE PDF", + "notFound": "Not found" + }, + "notFound": { + "errorCode": "404", + "pageNotFound": "Page Not Found", + "errorMessage": "Oops! The page you are looking for doesn't exist or has been moved.", + "returnHome": "Return Home" + }, + "components": { + "bottomNav": { + "scanner": "SCANNER", + "map": "MAP", + "mode": "MODE" + }, + "footer": { + "freshscanAi": "FreshScan AI", + "copyright": "© 2026 FreshScan AI. All rights reserved. Precision Intelligence." + }, + "layout": { + "watermark": "FS AI" + }, + "installPrompt": { + "iosMessage": "Add FreshScan AI to your Home Screen for one-tap fish freshness analysis. Tap Share and select Add to Home Screen.", + "androidMessage": "Add FreshScan AI to your home screen for instant fish freshness analysis in one tap.", + "appName": "FreshScan AI", + "promptTitle": "Install App", + "installButton": "Install", + "notNowButton": "Not Now", + "appImageAlt": "FreshScan AI", + "installedConsole": "User installed the PWA!", + "dismissedConsole": "User dismissed the install dialog.", + "errorConsole": "Error triggering the install prompt:" + }, + "onboardingTour": { + "welcomeMessage": "Welcome to FreshScanAI! Let's take a quick tour.", + "scannerStep": "Use Scanner to analyze fish freshness.", + "mapStep": "View market insights and trust map here." + }, + "posthog": { + "identifyError": "Failed to identify user with backend" + } + }, + "common": { + "error": "Error", + "loading": "Loading", + "success": "Success", + "warning": "Warning", + "alert": "Alert", + "tryAgain": "Try Again", + "reset": "Reset", + "cancel": "Cancel", + "confirm": "Confirm", + "save": "Save", + "delete": "Delete", + "close": "Close", + "ok": "OK" + }, + "error": { + "network": { + "connection": "Connection failed. Please check your internet and try again.", + "server": "Unable to connect to the server. Please check your internet connection." + }, + "auth": { + "supabaseConfig": "Authentication failed: Server is misconfigured. Please contact support." + }, + "unknown": "An unexpected error occurred. Please try again.", + "serverError": "Server error. Please try again later." + } +} diff --git a/src/i18n/locales/hi.json b/src/i18n/locales/hi.json index e60eea8..f34a7ea 100644 --- a/src/i18n/locales/hi.json +++ b/src/i18n/locales/hi.json @@ -1,8 +1,372 @@ { - "home": "होम", - "scanner": "स्कैनर", - "trustMap": "ट्रस्ट मैप", - "signin": "साइन इन / साइन अप", - "results": "परिणाम", - "logout": "लॉग आउट" -} \ No newline at end of file + "navbar": { + "home": "होम", + "scanner": "स्कैनर", + "trustMap": "ट्रस्ट मैप", + "signin": "साइन इन / साइन अप", + "results": "परिणाम", + "logout": "लॉग आउट", + "profile": "प्रोफ़ाइल", + "theme": "थीम", + "devLogin": "डेव", + "terminateSession": "सत्र समाप्त करें (लॉग आउट)", + "sessionTerminated": "सत्र समाप्त कर दिया गया", + "loginMobile": "लॉगिन" + }, + "landing": { + "heroLine1": "मछली की ताजगी", + "heroLine2": "*वस्तुनिष्ठ रूप से मूल्यांकन की गई*", + "heroSubtitle": "उच्च आर्द्रता वातावरण में रीयल-टाइम बायोमार्कर विश्लेषण के लिए इंजीनियर किया गया अकादमिक-ग्रेड एआई दृष्टि।", + "heroDescription": "FreshScan AI अराजक गीले बाजार को एक संरचित, <1>पारदर्शी पारिस्थितिकी तंत्र में बदल देता है।", + "inferenceSpeed": "अनुमान गति", + "speedValue": "<50ms", + "biomarkerAccuracy": "बायोमार्कर सटीकता", + "accuracyValue": "98.9%", + "beginAssessment": "मूल्यांकन शुरू करें", + "initializeSession": "सत्र शुरू करें", + "coreModulesTitle": "मुख्य मॉड्यूल", + "intelligenceFor": "बुद्धिमत्ता डिज़ाइन की गई", + "forThe": "के लिए", + "wetMarket": "गीली मंडी", + "moduleDescription": "तीन विशेष एआई पाइपलाइनें उपभोक्ता हार्डवेयर पर प्रयोगशाला-ग्रेड ताजगी विश्लेषण प्रदान करने के लिए एक साथ काम करती हैं।", + "moduleLoaded": "मॉड्यूल 0{{num}}: लोड किया गया", + "scanProtocolTitle": "स्कैन प्रोटोकॉल", + "stepsTo": "निश्चितता के लिए तीन कदम", + "certainty": "निश्चितता", + "faqTitle": "प्रोटोकॉल सामान्य प्रश्न", + "frequentlyAsked": "अक्सर पूछे जाने वाले", + "questions": "प्रश्न", + "assessmentReady": "मूल्यांकन तैयार", + "firstClass": "प्रथम श्रेणी", + "assessment": "मूल्यांकन", + "readyDescription": "अपने मोबाइल डिवाइस पर सीधे प्रयोगशाला-ग्रेड ताजगी विश्लेषण तैनात करें। कोई सदस्यता नहीं। कोई क्लाउड निर्भरता नहीं।", + "launchScanner": "स्कैनर लॉन्च करें", + "dualStreamTitle": "दोहरी-स्ट्रीम संदर्भ", + "dualStreamDesc": "उच्च आर्द्रता वातावरण के लिए सर्कुलर प्रतिबिंब और जैविक बनावट की समवर्ती प्रसंस्करण।", + "explainableAITitle": "व्याख्या योग्य एआई", + "explainableAIDesc": "सिर्फ ग्रेड पर विश्वास न करें। गिल्स, आंखों और तराजू पर हाइलाइट किए गए मार्कर को रीयल-टाइम में देखें।", + "crowdsourcedTitle": "क्राउडसोर्स्ड मैप", + "crowdsourcedDesc": "अनाम उपयोगकर्ता मेटाडेटा द्वारा संचालित स्थानीय बाजारों में जीवंत ताजगी हीटमैप।", + "scanBodyTitle": "शरीर स्कैन करें", + "scanBodyDesc": "कैमरा को नमूने से 15cm दूर रखें। परिवेश प्रकाश या बिल्ट-इन स्ट्रोब का उपयोग करें।", + "targetBiomarkersTitle": "लक्ष्य बायोमार्कर", + "targetBiomarkersDesc": "एआई गिल संतृप्ति, कॉर्नियल स्पष्टता और अधिचर्मीय तनाव की पहचान करता है।", + "getGradeTitle": "ग्रेड प्राप्त करें", + "getGradeDesc": "तत्काल ताजगी सूचकांक (0-100) भंडारण सुझावों के साथ उत्पन्न।", + "faq": { + "q1": "दोहरी-स्ट्रीम एआई मॉडल कैसे काम करता है?", + "a1": "FreshScan समानांतर में दो विशिष्ट न्यूरल नेटवर्क का उपयोग करता है। स्ट्रीम A (MobileNetV2) पूरे मछली शरीर का विश्लेषण करता है जबकि स्ट्रीम B (BiomarkerCNN) आंखों और गिल्स जैसे छोटे क्षेत्रों की जाँच करता है; उनके आउटपुट को मिलाकर अंतिम ताजगी सूचकांक बनाया जाता है।", + "q2": "ताजगी ग्रेड का क्या अर्थ है?", + "a2": "ताजगी सूचकांक (0–100) को पत्र ग्रेड में मैप किया जाता है: A+ (≥92), A (≥80), B (≥65), C (≥50), D (<50)। उच्च स्कोर बेहतर संरक्षण और अधिक सुरक्षित भंडारण विंडो का संकेत देते हैं।", + "q3": "ऑटो-स्कैन मोड बनाम मैन्युअल स्कैन क्या है?", + "a3": "ऑटो-स्कैन एक तस्वीर स्वीकार करता है और स्वचालित रूप से मान्यकरण और दोनों मॉडल स्ट्रीम चलाता है। मैन्युअल स्कैन अलग-अलग बॉडी, आई, और गिल छवियाँ अपलोड करने की अनुमति देता है।", + "q4": "Grad-CAM ओवरले क्या है?", + "a4": "Grad-CAM एक हीटमैप बनाता है जो उन छवि क्षेत्रों को हाइलाइट करता है जिन्होंने मॉडल के अनुमान को प्रभावित किया, ताकि आप देख सकें कि किन विशेषताओं ने ग्रेड में योगदान दिया।", + "q5": "ट्रस्ट मैप क्या है?", + "a5": "ट्रस्ट मैप विक्रेता ताजगी के अनाम स्कैन से संकलित एक लाइव हीटमैप है, जो लगातार उच्च-गुणवत्ता विक्रेताओं की पहचान करने में मदद करता है।" + } + }, + "scanner": { + "cameraAccessNeeded": "कैमरा पहुंच आवश्यक है", + "cameraPermissionDenied": "कैमरा अनुमति अस्वीकार कर दी गई", + "cameraNotFound": "इस डिवाइस पर कोई कैमरा नहीं मिला। कृपया एक कैमरा कनेक्ट करें और फिर से प्रयास करें।", + "cameraAccessError": "कैमरा तक पहुंचने में असमर्थ। कृपया अपनी ब्राउज़र अनुमतियों की जांच करें और फिर से प्रयास करें।", + "cameraSomethingWrong": "कैमरा तक पहुंचते समय कुछ गलत हो गया।", + "cameraInstructions": "अपने ब्राउज़र के पता बार में कैमरा आइकन पर क्लिक करें, कैमरा पहुंच की अनुमति दें, और पृष्ठ को रीफ्रेश करें।", + "failedCaptureFrame": "फ्रेम कैप्चर करने में विफल।", + "modeEdgeOnnx": "मोड: EDGE_ONNX", + "runningLocalInference": "स्थानीय अनुमान चल रहा है...", + "modeCloudApi": "मोड: CLOUD_API", + "connectingToHf": "HF से जुड़ रहे हैं...", + "detectingModel": "मॉडल का पता लगाया जा रहा है...", + "pleaseWait": "कृपया प्रतीक्षा करें", + "modelEdgeOnnx": "मॉडल: EDGE_ONNX", + "deviceOnDevice": "डिवाइस: ऑन_डिवाइस", + "latencyValue": "विलंबता: <50ms", + "modelCloudApi": "मॉडल: CLOUD_API", + "deviceHfInference": "डिवाइस: HF_अनुमान", + "scanSeqFailed": "स्कैन अनुक्रम: विफल", + "checkSpecimen": "नमूने की जांच करें", + "systemReady": "सिस्टम: तैयार", + "pointCameraAtFish": "कैमरा को मछली की ओर इशारा करें", + "fresh": "ताजा", + "moderate": "मध्यम", + "spoiled": "खराब", + "pointAtFish": "मछली की ओर इशारा करें", + "analyzingBiomarkers": "बायोमार्कर का विश्लेषण किया जा रहा है", + "gradePrefix": "ग्रेड ", + "runningEdgeInference": "एज अनुमान चल रहा है...", + "runningCloudInference": "क्लाउड अनुमान चल रहा है...", + "freshnessIndex": "ताजगी सूचकांक", + "viewAnalysisButton": "विश्लेषण देखें", + "copiedToClipboard": "क्लिपबोर्ड पर कॉपी किया गया", + "shareGradeReport": "ग्रेड-ए रिपोर्ट साझा करें", + "captureButton": "मछली कैप्चर करें", + "switchCamera": "कैमरा स्विच करें", + "uploadButton": "फोटो अपलोड करें", + "notFishDetected": "मछली नहीं: कोई मछली नहीं मिली। कृपया एक मछली की तस्वीर अपलोड करें।", + "inferenceFailed": "अनुमान विफल।", + "capturedAlt": "कैप्चर किया गया", + "rejectedUploadAlt": "अपलोड अस्वीकार किया गया" + }, + "dashboard": { + "loadingAnalysis": "विश्लेषण लोड हो रहा है...", + "fetchingResult": "परिणाम प्राप्त किया जा रहा है", + "loadFailed": "लोड विफल", + "noData": "कोई डेटा नहीं", + "noDataMessage": "कोई स्कैन डेटा उपलब्ध नहीं है। पहले एक स्कैन चलाएं।", + "goToScanner": "स्कैनर पर जाएं", + "backToScanner": "स्कैनर पर वापस जाएं", + "analysisComplete": "विश्लेषण पूर्ण", + "specimenLabel": "नमूना: ", + "scanIdLabel": "स्कैन ID: ", + "gradeLabel": "ग्रेड ", + "freshnessIndexLabel": "ताजगी सूचकांक", + "scorePercentage": "/100", + "classificationLabel": "वर्गीकरण: ", + "confidenceLabel": "आत्मविश्वास: ", + "percentageSymbol": "%", + "lowConfidence": "निम्न आत्मविश्वास", + "highConfidence": "उच्च आत्मविश्वास", + "detectedSpecimen": "पता लगाया गया नमूना", + "weightEst": "वजन अनुमान", + "kilogramUnit": "किग्रा", + "catchAge": "पकड़ आयु", + "hoursUnit": "घंटे", + "marketLabel": "बाजार", + "biomarkerAnalysis": "बायोमार्कर विश्लेषण", + "cautionLabel": "सावधानी", + "storageRecommendations": "भंडारण सिफारिशें", + "consumeWithin": "के भीतर उपभोग करें", + "consumeHours": "घंटे", + "discardAction": "त्याग दें", + "storageTemp": "भंडारण तापमान", + "alertLabel": "सतर्कता", + "newScanButton": "नया स्कैन", + "viewHistoryButton": "इतिहास देखें" + }, + "auth": { + "authInitiated": "प्रमाणीकरण शुरू किया गया", + "redirectingToOauth": "ओओथ पर पुनर्निर्देशित किया जा रहा है...", + "authError": "प्रमाणीकरण त्रुटि", + "retryRequired": "पुनः प्रयास आवश्यक", + "authenticationTitle": "प्रमाणीकरण", + "protocolOauth": "प्रोटोकॉल: ओथ-सुरक्षित", + "authWatermark": "प्रमाणीकरण", + "freshscanBrand": "FreshScan ", + "aiBrand": "AI", + "authFailed": "प्रमाणीकरण विफल। कृपया फिर से प्रयास करें।", + "authSubtitle": "अपने लाइव ट्रस्ट मैप को देखने और डिवाइस में बायोमार्कर डेटा को सिंक करने के लिए साइन इन करें।", + "loadingVerification": "सत्यापन चुनौती लोड की जा रही है...", + "continueWithGoogle": "Google के साथ जारी रखें", + "authenticating": "प्रमाणीकरण किया जा रहा है...", + "devLoginBypass": "डेव लॉगिन — ओथ बाईपास", + "localOnlyNote": "[केवल स्थानीय]" + }, + "results": { + "loadingHistory": "इतिहास लोड हो रहा है...", + "queryingDb": "डेटाबेस को क्वेरी किया जा रहा है", + "historyLoadFailed": "इतिहास लोड विफल", + "failedToLoadHistory": "इतिहास लोड करने में विफल।", + "signInRequired": "साइन इन आवश्यक", + "scanHistoryTerminal": "स्कैन इतिहास", + "totalPrefix": "कुल: ", + "avgScorePrefix": "औसत स्कोर: ", + "scanTitle": "स्कैन ", + "resultsTitle": "परिणाम", + "totalScans": "कुल स्कैन", + "avgFreshness": "औसत ताजगी", + "freshRate": "ताजा दर", + "percentageSymbol": "%", + "noScansFound": "कोई स्कैन नहीं मिला", + "runFirstScan": "पहला स्कैन चलाएं", + "initiateFirstScan": "पहला स्कैन शुरू करें" + }, + "marketMap": { + "failedLoadMarketData": "लाइव बाजार डेटा लोड करने में विफल।", + "liveGps": "लाइव जीपीएस", + "trustMapTerminal": "ट्रस्ट मैप", + "regionPrefix": "क्षेत्र: ", + "syncingDb": "डेटाबेस को सिंक किया जा रहा है...", + "loadError": "त्रुटि लोड", + "nodesPrefix": "नोड: ", + "marketTrustTitle": "बाजार विश्वास ", + "mapTitle": "मैप", + "leaderboardLink": "लीडरबोर्ड", + "selectMarketNode": "बाजार नोड चुनें", + "highTrust": "उच्च (85+)", + "mediumTrust": "माध्यम (70-84)", + "lowTrust": "निम्न (<70)", + "geolocationDenied": "भू-स्थान अस्वीकार किया गया या विफल, मॉक डेटा पर वापस जा रहे हैं।", + "failedLoadMarkets": "बाजार लोड करने में विफल।", + "vendorsLabel": "विक्रेता", + "avgFreshness": "औसत ताजगी", + "scorePrefix": "स्कोर: ", + "vendorsPrefix": "विक्रेता: " + }, + "leaderboard": { + "failedFetchLeaderboard": "लीडरबोर्ड प्राप्त करने में विफल।", + "vendorTrustLeaderboard": "विक्रेता ट्रस्ट लीडरबोर्ड", + "vendorSubtitle": "बाजारों में अनाम ताजगी स्कैन पर आधारित रैंकिंग", + "noVendorData": "अभी कोई विक्रेता डेटा नहीं।", + "goldBadge": "[ सोना ]", + "silverBadge": "[ चांदी ]", + "bronzeBadge": "[ कांस्य ]", + "unrankedBadge": "[ अरैंक किया गया ]", + "improving": "सुधार रहा है", + "declining": "गिरावट", + "stable": "स्थिर", + "scorePercentage": "/100", + "scansLabel": "स्कैन", + "scans": "स्कैन", + "subtitle": "उपशीर्षक", + "title": "शीर्षक" + }, + "modeSelect": { + "individual": { + "title": "व्यक्तिगत स्कैन", + "code": "मोड एकल", + "desc": "एक एकल नमूने की बिंदु-विश्लेषण। खुदरा उपभोक्ताओं के लिए व्यक्तिगत खरीद गुणवत्ता की पुष्टि के लिए।", + "stat": "औसत समय: 2.3s" + }, + "batch": { + "title": "बैच मूल्यांकन", + "code": "मोड बैच", + "desc": "डिस्प्ले में बहु-नमूना स्वीप। थोक खरीदारों के लिए प्रति सत्र 20+ इकाइयों को संसाधित करने के लिए डिज़ाइन किया गया।", + "stat": "प्रवाह: 12/मिनट" + }, + "survey": { + "title": "बाजार सर्वेक्षण", + "code": "मोड सर्वेक्षण", + "desc": "क्राउडसोर्स्ड ट्रस्ट मैप में योगदान दें। एक पूरी बाजार दुकान का सर्वेक्षण करें और अनाम ताजगी डेटा जमा करें।", + "stat": "डेटा बिंदु: 47.2K" + }, + "gradcamTitle": "ग्रैड-कैम दर्शक", + "xaiModule": "XAI मॉड्यूल", + "classificationFresh": "ताजा", + "classificationModerate": "मध्यम", + "classificationSpoiled": "खराब", + "demoMode": "डेमो मोड", + "operationMode": "ऑपरेशन मोड", + "selectProtocol": "प्रोटोकॉल चुनें", + "awaitingInput": "इनपुट की प्रतीक्षा है...", + "selectOperation": "ऑपरेशन मोड चुनें", + "mode": "मोड", + "description": "एक स्कैनिंग प्रोटोकॉल चुनें या मॉडल व्यवहार को समझने के लिए व्याख्यात्मकता टूलकिट का उपयोग करें।", + "explainability": "व्याख्यात्मकता", + "toolkit": "टूलकिट", + "gradcamSectionDescription": "समझें कि मॉडल क्या देखता है। ग्रेडिएंट-वेटेड क्लास एक्टिवेशन मैप (ग्रैड-कैम) हीटमैप बनाने के लिए किसी भी मछली की तस्वीर अपलोड करें।", + "allModulesLoaded": "सभी मॉड्यूल लोड हो गए", + "gpuAccelOn": "GPU त्वरण: चालू", + "gradcamViewerTitle": "ग्रैड-कैम दर्शक", + "gradcamDescription": "मछली की छवि अपलोड करें यह देखने के लिए कि स्ट्रीम ए न्यूरल नेटवर्क ताजगी वर्गीकरण के लिए किन क्षेत्रों पर ध्यान केंद्रित करता है।", + "clickToUpload": "अपलोड करने के लिए क्लिक करें", + "orDragDrop": "या खींचें और छोड़ें", + "acceptedFormats": "JPEG · PNG · WebP — कोई भी रिज़ॉल्यूशन" + }, + "gradcam": { + "invalidFileError": "कृपया एक मान्य छवि फ़ाइल (JPEG / PNG / WebP) अपलोड करें।", + "generationFailedError": "ग्रैड-कैम निर्माण विफल।", + "runningForwardPass": "आगे पास चल रहा है", + "computingGradients": "ग्रेडिएंट्स की गणना की जा रही है", + "renderingHeatmap": "हीटमैप प्रदान किया जा रहा है", + "rejectedUploadAlt": "अस्वीकृत अपलोड", + "notAFishDetected": "मछली नहीं पहचानी गई", + "notAFishText": "अपलोड की गई छवि में मछली नहीं दिखाई देती है। कृपया एक मछली के शरीर, आंख या गिल की स्पष्ट तस्वीर अपलोड करें।", + "tryAgain": "फिर से प्रयास करें", + "uploadDifferentImage": "अलग छवि अपलोड करें", + "originalInput": "मूल इनपुट", + "originalImageAlt": "मूल अपलोड की गई छवि", + "activationMap": "सक्रियण मैप", + "heatmapAlt": "ग्रैड-कैम हीटमैप ओवरले", + "streamA": "स्ट्रीम ए", + "synthetic": "सिंथेटिक", + "lowToHigh": "कम → उच्च", + "uploadNewImage": "नई छवि अपलोड करें" + }, + "publicReport": { + "errorCode": "त्रुटि: 404", + "reportNotFound": "रिपोर्ट नहीं मिली", + "verifyScanId": "स्कैन ID सत्यापित करें", + "fetchingData": "डेटा प्राप्त किया जा रहा है", + "standby": "प्रतीक्षा में...", + "freshscanBrand": "FreshScan ", + "publicReport": "सार्वजनिक रिपोर्ट", + "generatedPrefix": "जनरेट किया गया: ", + "idPrefix": "ID: ", + "freshnessScore": "ताजगी स्कोर", + "gradeBadge": "ग्रेड ", + "separator": "—", + "rawMarkers": "कच्चे मार्कर", + "copiedClipboard": "क्लिपबोर्ड पर कॉपी किया गया", + "copyShareLink": "साझा लिंक कॉपी करें", + "printSavePdf": "प्रिंट या PDF सहेजें", + "notFound": "नहीं मिला" + }, + "notFound": { + "errorCode": "404", + "pageNotFound": "पृष्ठ नहीं मिला", + "errorMessage": "आउच! जिस पृष्ठ की आप तलाश कर रहे हैं वह मौजूद नहीं है या स्थानांतरित हो गया है।", + "returnHome": "होम पर वापस जाएं" + }, + "components": { + "bottomNav": { + "scanner": "स्कैनर", + "map": "मैप", + "mode": "मोड" + }, + "footer": { + "freshscanAi": "FreshScan AI", + "copyright": "© 2026 FreshScan AI. सर्वाधिकार सुरक्षित। सटीक बुद्धिमत्ता।" + }, + "layout": { + "watermark": "FS AI" + }, + "installPrompt": { + "iosMessage": "एक-टैप मछली ताजगी विश्लेषण के लिए अपनी होम स्क्रीन पर FreshScan AI जोड़ें। साझा करें पर टैप करें और होम स्क्रीन में जोड़ें चुनें।", + "androidMessage": "तत्काल मछली ताजगी विश्लेषण के लिए अपनी होम स्क्रीन पर FreshScan AI जोड़ें।", + "appName": "FreshScan AI", + "promptTitle": "ऐप्लिकेशन इंस्टॉल करें", + "installButton": "इंस्टॉल", + "notNowButton": "अभी नहीं", + "appImageAlt": "FreshScan AI", + "installedConsole": "उपयोगकर्ता ने PWA स्थापित किया!", + "dismissedConsole": "उपयोगकर्ता ने इंस्टॉल संवाद को खारिज कर दिया।", + "errorConsole": "इंस्टॉल प्रॉम्प्ट ट्रिगर करने में त्रुटि:" + }, + "onboardingTour": { + "welcomeMessage": "FreshScanAI में स्वागत है! आइए एक त्वरित दौरा करते हैं।", + "scannerStep": "मछली की ताजगी का विश्लेषण करने के लिए स्कैनर का उपयोग करें।", + "mapStep": "यहां बाजार अंतर्दृष्टि और ट्रस्ट मैप देखें।" + }, + "posthog": { + "identifyError": "बैकएंड के साथ उपयोगकर्ता की पहचान करने में विफल" + } + }, + "common": { + "error": "त्रुटि", + "loading": "लोड हो रहा है", + "success": "सफलता", + "warning": "चेतावनी", + "alert": "सतर्कता", + "tryAgain": "फिर से प्रयास करें", + "reset": "रीसेट", + "cancel": "रद्द करें", + "confirm": "पुष्टि करें", + "save": "सहेजें", + "delete": "हटाएं", + "close": "बंद करें", + "ok": "ठीक है" + }, + "error": { + "network": { + "connection": "कनेक्शन विफल। कृपया अपना इंटरनेट जांचें और पुनः प्रयास करें।", + "server": "सर्वर से कनेक्ट करने में असमर्थ। कृपया अपना इंटरनेट कनेक्शन जांचें।" + }, + "auth": { + "supabaseConfig": "प्रमाणीकरण विफल: सर्वर गलत तरीके से कॉन्फ़िगर किया गया है। कृपया सहायता से संपर्क करें।" + }, + "unknown": "एक अप्रत्याशित त्रुटि हुई। कृपया पुनः प्रयास करें।", + "serverError": "सर्वर त्रुटि। कृपया बाद में पुनः प्रयास करें।" + } +} diff --git a/src/lib/api.ts b/src/lib/api.ts index f321083..f925c4f 100644 --- a/src/lib/api.ts +++ b/src/lib/api.ts @@ -1,4 +1,3 @@ -import toast from "react-hot-toast"; import type { ScanResult, HistoryScan, @@ -43,39 +42,38 @@ function authHeaders(): Record { async function handleResponse( res: Response, - options?: ApiRequestOptions, ): Promise { if (res.ok) return res; if (res.status >= 500) { - const msg = "Server error. Please try again later."; + // Throw a translation key instead of a translated message. + // The UI component will handle the translation. + throw new Error('error.serverError'); + } - if (!options?.silent) { - toast.error(msg); - } + // Try to parse the error detail from the backend + const errJson = await res.json().catch(() => ({ detail: res.statusText })); + const detail = (errJson as { detail?: string }).detail || `HTTP ${res.status}`; - throw new Error(msg); + // Check for specific, known error strings from the backend and translate them. + if (detail.includes('supabase_url is required')) { + // Throw a translation key for the UI to handle. + throw new Error('error.auth.supabaseConfig'); } - const err = await res.json().catch(() => ({ detail: res.statusText })); - throw new Error((err as { detail?: string }).detail || `HTTP ${res.status}`); + throw new Error(detail); } -type ApiRequestOptions = { - silent?: boolean; -}; async function safeFetch( input: RequestInfo | URL, init?: RequestInit, - options?: ApiRequestOptions, ): Promise { try { const res = await fetch(input, init); - return await handleResponse(res, options); + return await handleResponse(res); } catch (error) { - if (!options?.silent && (error instanceof TypeError || error?.toString().includes("fetch"))) { - toast.error( - "Unable to connect to the server. Please check your internet connection.", - ); + if (error instanceof TypeError) { + // For network errors, throw a specific translation key. + throw new Error('error.network.connection'); } console.error("API Error:", error); @@ -120,6 +118,20 @@ export interface GradcamResponse { mode: "real" | "demo"; } +export interface LeaderboardEntry { + id: string; + name: string; + trust_score: number; + total_scans: number; + avg_freshness_score: number; + lat: number; + lng: number; +} +export interface LeaderboardResponse { + success: boolean; + leaderboard: LeaderboardEntry[]; +} + // Metadata sent alongside edge-inference results so the backend can store them // without re-running the ML pipeline on the server. export interface EdgeInferenceMeta { @@ -154,7 +166,6 @@ export const api = { submitScan: async ( blob: Blob, meta?: EdgeInferenceMeta, - options?: ApiRequestOptions, ): Promise => { const form = new FormData(); form.append("image", blob, "scan.jpg"); @@ -173,7 +184,6 @@ export const api = { headers: authHeaders(), body: form, }, - options, ); return validRes.json() as Promise; @@ -194,19 +204,16 @@ export const api = { headers: authHeaders(), body: form, }); - if (!res.ok) { - const err = await res.json().catch(() => ({ detail: res.statusText })); - throw new Error( - (err as { detail?: string }).detail || `HTTP ${res.status}`, - ); - } - return res.json() as Promise; + // Use the centralized response handler which throws i18n keys for errors + const handledRes = await handleResponse(res); + return handledRes.json() as Promise; } catch (err) { if (err instanceof TypeError) { // Network offline — silent fallback to ONNX return null; } - throw err; // Server error (e.g. NOT_A_FISH) — propagate + // Propagate other errors (which may be i18n keys from handleResponse) + throw err; } }, @@ -246,4 +253,7 @@ export const api = { apiFetch( `/api/v1/maps/markets/live?lat=${lat}&lng=${lng}&radius=${radius}`, ), + + getLeaderboard: (): Promise => + apiFetch("/api/v1/vendors/leaderboard"), }; diff --git a/src/main.tsx b/src/main.tsx index c495c46..92adb0f 100644 --- a/src/main.tsx +++ b/src/main.tsx @@ -5,7 +5,7 @@ import { PostHogProvider } from 'posthog-js/react' import './index.css' import App from './App.tsx' import { initTheme } from './lib/theme' -import "./i18n"; +import './i18n/i18n'; // Initialize theme before rendering the app to prevent flicker initTheme(); @@ -26,7 +26,6 @@ const POSTHOG_HOST = if (POSTHOG_KEY) { posthog.init(POSTHOG_KEY, { api_host: POSTHOG_HOST, - defaults: '2026-01-30', // Loads async — won't block rendering loaded: (ph) => { // Disable in dev so local sessions don't pollute the dashboard @@ -41,4 +40,4 @@ createRoot(document.getElementById('root')!).render( , -) \ No newline at end of file +) diff --git a/src/pages/AnalysisDashboard.tsx b/src/pages/AnalysisDashboard.tsx index aa33f4a..24890e3 100644 --- a/src/pages/AnalysisDashboard.tsx +++ b/src/pages/AnalysisDashboard.tsx @@ -1,15 +1,16 @@ import { useEffect, useState } from 'react'; import { Link, useSearchParams } from 'react-router-dom'; -import { ArrowLeft, AlertTriangle, Droplets, Eye as EyeIcon, Fish, Loader2 } from 'lucide-react'; +import { useTranslation } from 'react-i18next'; +import { ArrowLeft, AlertTriangle, Droplets, Eye as EyeIcon, Fish } from 'lucide-react'; import GlassCard from '../components/GlassCard'; import StatusTerminal from '../components/StatusTerminal'; import { api } from '../lib/api'; import type { ScanResult } from '../lib/types'; -import ScanSkeleton from "../components/shared/ScanSkeleton"; + const BIOMARKER_META = { - gill_saturation: { label: 'Gill Saturation', icon: Droplets }, - corneal_clarity: { label: 'Corneal Clarity', icon: EyeIcon }, - epidermal_tension: { label: 'Epidermal Tension', icon: Fish }, + gill_saturation: { labelKey: 'dashboard.gill_saturation', icon: Droplets }, + corneal_clarity: { labelKey: 'dashboard.corneal_clarity', icon: EyeIcon }, + epidermal_tension: { labelKey: 'dashboard.epidermal_tension', icon: Fish }, } as const; type BiomarkerKey = keyof typeof BIOMARKER_META; @@ -21,28 +22,20 @@ function gradeColor(grade: string) { } export default function AnalysisDashboard() { - const [params] = useSearchParams(); + const { t } = useTranslation(); + + const [params] = useSearchParams(); const [scan, setScan] = useState(null); const [loading, setLoading] = useState(true); - const [error, setError] = useState(''); - - const [gradcamImage, setGradcamImage] = useState(null); - const [gradcamLoading, setGradcamLoading] = useState(false); - const [gradcamError, setGradcamError] = useState(null); - const [blendOpacity, setBlendOpacity] = useState(0.5); - const [retryTrigger, setRetryTrigger] = useState(0); - - const photo_url = scan?.photo_url; + const [errorKey, setErrorKey] = useState(''); useEffect(() => { - async function load() { setLoading(true); - setError(""); - + setErrorKey(''); try { - const idParam = params.get("id"); - const lastId = sessionStorage.getItem("lastScanId"); + const idParam = params.get('id'); + const lastId = sessionStorage.getItem('lastScanId'); const targetId = idParam || lastId; const res = targetId @@ -51,114 +44,36 @@ export default function AnalysisDashboard() { setScan(res.scan); } catch (err) { - const offlineData = sessionStorage.getItem("offlineScanResult"); - - if (offlineData) { - try { - const parsed = JSON.parse(offlineData); - - if (parsed?.freshness_index != null) { - setScan(parsed); - setLoading(false); - return; - } - } catch (e) { - console.warn("Failed to parse offline scan result", e); - } - } - - setError( - err instanceof Error ? err.message : "Failed to load scan data." - ); + setErrorKey(err instanceof Error ? err.message : 'dashboard.noDataMessage'); } finally { setLoading(false); } } - load(); }, [params]); - useEffect(() => { - if (!photo_url) return; - const url = photo_url; - - let isMounted = true; - const controller = new AbortController(); - - async function loadGradcam() { - setGradcamImage(null); - setGradcamLoading(true); - setGradcamError(null); - - try { - const res = await fetch(url, { - signal: controller.signal, - }); - - if (!res.ok) { - throw new Error(`Failed to download scan image (${res.status})`); - } - - const blob = await res.blob(); - const gradcamRes = await api.getGradcam(blob); - - if (isMounted) { - setGradcamImage(gradcamRes.gradcam_image); - } - } catch (err) { - if ( - err instanceof DOMException && - err.name === "AbortError" - ) { - return; - } - - console.error("Grad-CAM generation error:", err); - - if (isMounted) { - setGradcamError( - err instanceof Error - ? err.message - : "Heatmap generation failed." - ); - } - } finally { - if (isMounted) { - setGradcamLoading(false); - } - } - } - - loadGradcam(); - - return () => { - isMounted = false; - controller.abort(); - }; - }, [photo_url, retryTrigger]); - - const handleRetry = () => { - setRetryTrigger((prev) => prev + 1); - }; - // ── Loading state ──────────────────────────────────────────────────────── if (loading) { - return ; + return ( +
+ +
+ ); } // ── Error state ────────────────────────────────────────────────────────── - if (error || !scan) { + if (errorKey || !scan) { return (
- +

- {error || 'No scan data available. Run a scan first.'} + {errorKey ? t(errorKey) : t('dashboard.noDataMessage')}

- GO_TO_SCANNER + {t('dashboard.goToScanner')}
); @@ -177,341 +92,110 @@ export default function AnalysisDashboard() { className="inline-flex items-center gap-2 text-on-surface-variant hover:text-neon no-underline transition-colors mb-6 font-[family-name:var(--font-mono)] text-[0.6875rem] tracking-widest" > - BACK_TO_SCANNER + {t('dashboard.backToScanner')} {/* Terminal header */} - {/* Score + Species row / Visualization */} + {/* Score + Species row */}
- {photo_url ? ( - <> - {/* Left Column: Image Overlay Card */} - -
- - SCAN_VISUALIZATION - - - {/* Stacked Images container */} -
- {/* Viewfinder corner brackets */} -
-
-
-
- - {/* Base Original Image */} - Original Fish Scan - - {/* Heatmap Overlay Image */} - {gradcamImage && ( - GradCAM Heatmap Overlay - )} - - {/* Legend overlay */} - {blendOpacity > 0 && gradcamImage && ( -
- {['#3b82f6', '#22c55e', '#eab308', '#ef4444'].map((c, i) => ( -
- ))} - - LOW → HIGH - -
- )} - - {/* Loading overlay */} - {gradcamLoading && ( -
- - - GENERATING_HEATMAP... - -
- )} - - {/* Error overlay */} - {gradcamError && ( -
- - - ACTIVATION_MAP_ERROR - -

- {gradcamError} -

- -
- )} -
-
- -
- {/* Toggle Buttons */} -
- - - -
- - {/* Opacity slider */} -
-
- BLEND LEVEL - {Math.round(blendOpacity * 100)}% -
- setBlendOpacity(parseFloat(e.target.value))} - className="w-full accent-neon bg-surface-lowest border border-outline-variant/30 cursor-pointer h-1.5 outline-none" - /> -
-
- - - {/* Right Column: Score & Species stacked */} -
- {/* Main score card */} - -
- - GRADE_{grade} - -
- - - Freshness_Index - - -
- - {freshness_index} - - - /100 - -
- -
-
-
- -
- - CLASSIFICATION: {classification} - - - - CONFIDENCE: {confidence}% - + {/* Main score card */} + +
+ + {t('dashboard.gradeLabel')}{grade} + +
- - {confidence < 70 ? "LOW_CONFIDENCE" : "HIGH_CONFIDENCE"} - -
- + + {t('dashboard.freshnessIndexLabel')} + - {/* Species panel */} - - - Detected_Specimen - +
+ + {freshness_index} + + {t('ashboard.scorePercentage')} +
+ +
+
+
+ +
+ + {t('dashboard.classificationLabel')}{classification} + -
- {species.tags.map(tag => ( - - {tag} - - ))} -
+ + {t('dashboard.confidenceLabel')}{confidence}% + -
-
- WEIGHT_EST - - ~{species.weight_estimate_kg} kg - -
-
- CATCH_AGE - - ~{species.catch_age_hours} hrs - -
- {scan.market_name && ( -
- MARKET - - {scan.market_name} - -
- )} -
- + + {confidence < 70 ? t('dashboard.lowConfidence') : t('dashboard.highConfidence')} + +
+ + + {/* Species panel */} + + {t('ashboard.detectedSpecimen')} + +
+ {species.tags.map(tag => ( + + {tag} + + ))} +
+ +
+
+ {t('ashboard.weightEst')} + + ~{species.weight_estimate_kg} kg +
- - ) : ( - <> - {/* Main score card */} - -
- - GRADE_{grade} - -
- - - Freshness_Index +
+ {t('ashboard.catchAge')} + + ~{species.catch_age_hours} hrs - -
- - {freshness_index} - - - /100 - -
- -
-
-
- -
- - CLASSIFICATION: {classification} - - - - CONFIDENCE: {confidence}% - - - - {confidence < 70 ? "LOW_CONFIDENCE" : "HIGH_CONFIDENCE"} +
+ {scan.market_name && ( +
+ {t('ashboard.marketLabel')} + + {scan.market_name}
- - - {/* Species panel */} - - - Detected_Specimen - - -
- {species.tags.map(tag => ( - - {tag} - - ))} -
- -
-
- WEIGHT_EST - - ~{species.weight_estimate_kg} kg - -
-
- CATCH_AGE - - ~{species.catch_age_hours} hrs - -
- {scan.market_name && ( -
- MARKET - - {scan.market_name} - -
- )} -
- - - )} + )} +
+
{/* Biomarkers — 3 model-native streams */}
- BIOMARKER_ANALYSIS + {t('dashboard.biomarkerAnalysis')}
{(Object.keys(BIOMARKER_META) as BiomarkerKey[]).map(key => { @@ -534,7 +218,7 @@ export default function AnalysisDashboard() {

- {meta.label} + {t(meta.labelKey)}

@@ -565,22 +249,22 @@ export default function AnalysisDashboard() { {/* Recommendations */}
- STORAGE_RECOMMENDATIONS + {t('dashboard.storageRecommendations')}
0 ? 'grid-cols-3' : 'grid-cols-2'}`}> - CONSUME_WITHIN + {t('dashboard.consumeWithin')} {recommendations.consume_within_hours > 0 - ? `${recommendations.consume_within_hours} HRS` - : 'DISCARD'} + ? `${recommendations.consume_within_hours} ${t('dashboard.consumeHours')}` + : t('dashboard.discardAction')} - STORAGE_TEMP + {t('dashboard.storageTemp')} {recommendations.storage_temp} @@ -590,7 +274,7 @@ export default function AnalysisDashboard() { {alerts.length > 0 && ( - ALERT + {t('dashboard.alertLabel')} {alerts[0]} @@ -606,13 +290,13 @@ export default function AnalysisDashboard() { to="/scanner" className="flex-1 bg-neon text-on-primary py-4 font-[family-name:var(--font-display)] font-bold text-sm tracking-wider no-underline text-center transition-all duration-200 hover:bg-neon-dim" > - NEW_SCAN + {t('dashboard.newScanButton')} - VIEW_HISTORY + {t('dashboard.viewHistoryButton')}
diff --git a/src/pages/AuthPage.tsx b/src/pages/AuthPage.tsx index efb4577..3cd37c3 100644 --- a/src/pages/AuthPage.tsx +++ b/src/pages/AuthPage.tsx @@ -1,6 +1,7 @@ import { useEffect, useState } from 'react'; import { useNavigate } from 'react-router-dom'; import { usePostHog } from 'posthog-js/react'; +import { useTranslation } from 'react-i18next'; import StatusTerminal from '../components/StatusTerminal'; import { api, setToken, isAuthenticated } from '../lib/api'; import useTurnstile from '../lib/useTurnstile'; @@ -11,9 +12,11 @@ const IS_DEV_MODE = import.meta.env.VITE_DEV_MODE === 'true'; const TURNSTILE_SITE_KEY = import.meta.env.VITE_TURNSTILE_SITE_KEY as string | undefined; export default function AuthPage() { - const navigate = useNavigate(); + const { t } = useTranslation(); + + const navigate = useNavigate(); const posthog = usePostHog(); - const { containerRef, ready: turnstileReady, execute: executeTurnstile, error: turnstileError } = useTurnstile(TURNSTILE_SITE_KEY); + const { containerRef, ready: turnstileReady, execute: executeTurnstile, error: turnstileError } = useTurnstile(TURNSTILE_SITE_KEY); const [status, setStatus] = useState<'idle' | 'processing' | 'error'>(() => { const params = new URLSearchParams(window.location.search); if (params.get('error')) return 'error'; @@ -21,9 +24,9 @@ export default function AuthPage() { return 'idle'; }); - const [errorMsg, setErrorMsg] = useState(() => { + const [errorKey, setErrorKey] = useState(() => { const params = new URLSearchParams(window.location.search); - return params.get('error') ? 'Authentication failed. Please try again.' : ''; + return params.get('error') ? 'auth.authFailed' : ''; }); // Handle redirect from backend OAuth callback @@ -73,10 +76,10 @@ export default function AuthPage() { window.location.href = loginUrl; } catch (err) { setStatus('error'); - setErrorMsg( + setErrorKey( err instanceof Error ? err.message - : 'Could not initiate Google Login. Please check your network connection.' + : 'error.network.connection' // A more generic, translatable key ); console.error('Auth initiation failed:', err); } @@ -89,15 +92,15 @@ export default function AuthPage() { }; const terminalMessages = (() => { - if (status === 'processing') return ['AUTH_INITIATED', 'REDIRECTING_TO_OAUTH...']; - if (status === 'error') return ['AUTH_ERROR', 'RETRY_REQUIRED']; - return ['AUTHENTICATION', 'PROTOCOL: OAUTH-SECURE']; + if (status === 'processing') return [t('auth.authInitiated'), t('auth.redirectingToOauth')]; + if (status === 'error') return [t('auth.authError'), t('auth.retryRequired')]; + return [t('auth.authenticationTitle'), t('auth.protocolOauth')]; })(); return (
- AUTH + {t('auth.authWatermark')}
@@ -108,7 +111,7 @@ export default function AuthPage() {

- FRESHSCAN AI + {t('auth.freshscanBrand')}{t('auth.aiBrand')}

@@ -117,19 +120,19 @@ export default function AuthPage() { {status === 'error' && (

- {errorMsg} + {errorKey && t(errorKey)}

)} {status === 'idle' && (

- Sign in to view your live Trust Map and sync biomarker data across devices. + {t('auth.authSubtitle')}

)} {TURNSTILE_SITE_KEY && !turnstileReady && (

- Loading verification challenge... + {t('auth.loadingVerification')}

)} @@ -156,7 +159,7 @@ export default function AuthPage() { - {status === 'processing' ? 'AUTHENTICATING...' : 'CONTINUE_WITH_GOOGLE'} + {status === 'processing' ? t('auth.authenticating') : t('auth.continueWithGoogle')} {IS_DEV_MODE && ( @@ -166,8 +169,8 @@ export default function AuthPage() { className="w-full border border-dashed border-yellow-500/50 bg-yellow-500/5 text-yellow-400 py-4 font-[family-name:var(--font-mono)] text-xs tracking-widest cursor-pointer transition-all duration-200 hover:bg-yellow-500/10 hover:border-yellow-400 flex items-center justify-center gap-3" > ⚡ - DEV_LOGIN — BYPASS_OAUTH - [local only] + {t('auth.devLoginBypass')} + {t('auth.localOnlyNote')} )}
@@ -176,4 +179,4 @@ export default function AuthPage() {
); -} \ No newline at end of file +} diff --git a/src/pages/LandingPage.tsx b/src/pages/LandingPage.tsx index f4bdf2b..cc0d4a4 100644 --- a/src/pages/LandingPage.tsx +++ b/src/pages/LandingPage.tsx @@ -2,74 +2,61 @@ import { Link } from 'react-router-dom'; import { isAuthenticated } from '../lib/api'; import { Zap, Eye, MapPin, ScanLine, Target, Award, ChevronDown } from 'lucide-react'; import GlassCard from '../components/GlassCard'; -import { useState, useEffect } from 'react'; -import BackToTopButton from '../components/BackToTopButton'; +import { useState, useEffect } from "react"; +import { Trans, useTranslation } from "react-i18next"; -const features = [ - { - icon: Zap, - title: 'Dual-Stream Context', - desc: 'Simultaneous processing of specular reflection and biological texture for high-humidity environments.', - }, - { - icon: Eye, - title: 'Explainable AI', - desc: "Don't just trust a grade. See highlighted markers on the gills, eyes, and scales in real-time.", - }, - { - icon: MapPin, - title: 'Crowdsourced Map', - desc: 'Live freshness heatmaps across local markets powered by anonymized user metadata.', - }, -]; +export default function LandingPage() { + const { t } = useTranslation(); -const steps = [ - { - icon: ScanLine, - step: '01', - title: 'Scan Body', - desc: 'Position camera 15cm from specimen. Use ambient light or built-in strobe.', - }, - { - icon: Target, - step: '02', - title: 'Target Biomarkers', - desc: 'AI identifies gill saturation, corneal clarity, and epidermal tension.', - }, - { - icon: Award, - step: '03', - title: 'Get Grade', - desc: 'Instant Freshness Index (0-100) generated with storage recommendations.', - }, -]; + const [openFaq, setOpenFaq] = useState(null); + const [loggedIn, setLoggedIn] = useState(isAuthenticated()); -const faqs = [ - { - q: 'How does the dual-stream AI model work?', - a: 'FreshScan uses two specialized neural networks in parallel. Stream A is a fine-tuned MobileNetV2 that analyzes the full fish body for overall freshness classification (C1 Fresh / C2 Moderate / C3 Spoiled). Stream B is a custom BiomarkerCNN that inspects micro-regions — eyes and gills — for localized freshness signals. Their outputs are fused with temperature-scaled confidence scoring to produce the final Freshness Index.', - }, - { - q: 'What do the freshness grades mean?', - a: 'The Freshness Index (0–100) maps to letter grades: A+ (≥92) and A (≥80) are prime quality, B (≥65) is acceptable, C (≥50) is borderline, and D (below 50) is classified as SPOILED. A score of 65+ is the FRESH threshold. The system also estimates how many hours the fish can safely be stored at 0–4°C.', - }, - { - q: 'What is Auto-Scan mode vs. manual scan?', - a: 'Auto-Scan accepts a single photo and automatically routes it through a fish-validation gate (CLIP-based) before running both streams. Manual scan mode lets you upload separate Body, Eye, and Gill images for a more granular three-part assessment — useful for advanced users who want to isolate specific biomarkers.', - }, - { - q: 'What is the Grad-CAM overlay?', - a: 'Grad-CAM (Gradient-weighted Class Activation Mapping) generates a heatmap highlighting exactly which regions of your image drove the freshness prediction. High-activation zones on gills, eyes, or scales are overlaid in a jet colormap so you can see what the model is responding to, not just the score it outputs.', - }, - { - q: 'What is the Trust Map?', - a: 'The Trust Map is a live, crowdsourced heatmap of local fish vendors and markets. Every anonymized scan tied to a vendor location updates that vendor\'s average freshness score and trust rating in the Supabase database. You can use the map to identify consistently high-quality vendors in your area before you buy.', - }, -]; + const features = [ + { + icon: Zap, + title: t('landing.dualStreamTitle'), + desc: t('landing.dualStreamDesc'), + }, + { + icon: Eye, + title: t('landing.explainableAITitle'), + desc: t('landing.explainableAIDesc'), + }, + { + icon: MapPin, + title: t('landing.crowdsourcedTitle'), + desc: t('landing.crowdsourcedDesc'), + }, + ]; -export default function LandingPage() { - const [openFaq, setOpenFaq] = useState(null); - const [loggedIn, setLoggedIn] = useState(isAuthenticated()); + const steps = [ + { + icon: ScanLine, + step: '01', + title: t('landing.scanBodyTitle'), + desc: t('landing.scanBodyDesc'), + }, + { + icon: Target, + step: '02', + title: t('landing.targetBiomarkersTitle'), + desc: t('landing.targetBiomarkersDesc'), + }, + { + icon: Award, + step: '03', + title: t('landing.getGradeTitle'), + desc: t('landing.getGradeDesc'), + }, + ]; + + const faqs = [ + { q: t('landing.faq.q1'), a: t('landing.faq.a1') }, + { q: t('landing.faq.q2'), a: t('landing.faq.a2') }, + { q: t('landing.faq.q3'), a: t('landing.faq.a3') }, + { q: t('landing.faq.q4'), a: t('landing.faq.a4') }, + { q: t('landing.faq.q5'), a: t('landing.faq.a5') }, + ]; useEffect(() => { const handleAuthChange = () => setLoggedIn(isAuthenticated()); @@ -83,32 +70,31 @@ export default function LandingPage() {

- Fish Freshness + {t('landing.heroLine1')}
- *Objectively Graded* + {t('landing.heroLine2')}

- Academic-grade AI vision engineered for real-time biomarker analysis - in high-humidity environments. + {t('landing.heroSubtitle')}

{/* Stat Pills */}
- Inference Speed + {t('landing.inferenceSpeed')} - <50ms + {t('landing.speedValue')} - Biomarker Accuracy + {t('landing.biomarkerAccuracy')} - 98.9% + {t('landing.accuracyValue')}
@@ -120,14 +106,14 @@ export default function LandingPage() { className="bg-neon text-on-primary px-8 py-4 font-[family-name:var(--font-display)] font-bold text-sm tracking-wider no-underline transition-all duration-200 hover:bg-neon-dim pulse-glow inline-flex items-center gap-3" > - BEGIN_ASSESSMENT + {t('landing.beginAssessment')} {!loggedIn && ( - INITIALIZE_SESSION + {t('landing.initializeSession')} )}
@@ -137,15 +123,14 @@ export default function LandingPage() { {/* ── FEATURES ── */}
- CORE_MODULES + {t('landing.coreModulesTitle')}

- Intelligence designed + {t('landing.intelligenceFor')}
- for the wet market + {t('landing.forThe')} {t('landing.wetMarket')}

- Three specialized AI pipelines working in concert to deliver - laboratory-grade freshness analysis on consumer hardware. + {t('landing.moduleDescription')}

@@ -161,7 +146,7 @@ export default function LandingPage() { {f.desc}

- MODULE_{String(i + 1).padStart(2, '0')}: LOADED + {t('landing.moduleLoaded', { num: String(i + 1).padStart(2, '0') })} ))} @@ -172,11 +157,11 @@ export default function LandingPage() { {/* ── HOW IT WORKS ── */}
- SCAN_PROTOCOL + {t('landing.scanProtocolTitle')}

- Three steps to + {t('landing.stepsTo')}
- certainty + {t('landing.certainty')}

@@ -208,11 +193,12 @@ export default function LandingPage() {

- "FreshScan AI transforms the chaotic wet market into a structured,{' '} - - transparent ecosystem - - ." + “ + }} + /> + ”

@@ -221,11 +207,11 @@ export default function LandingPage() { {/* ── FAQ ── */}
- PROTOCOL_FAQ + {t('landing.faqTitle')}

- Frequently Asked + {t('landing.frequentlyAsked')}
- Questions + {t('landing.questions')}

@@ -261,26 +247,25 @@ export default function LandingPage() { {/* ── BOTTOM CTA ── */}
- ASSESSMENT_READY + {t('landing.assessmentReady')}

- First Class + {t('landing.firstClass')}
- Assessment + {t('landing.assessment')}

- Deploy laboratory-grade freshness analysis directly to your mobile device. - No subscription. No cloud dependency. + {t('landing.readyDescription')}

- LAUNCH_SCANNER + {t('landing.launchScanner')}
- + {/* */}
); } diff --git a/src/pages/Leaderboard.tsx b/src/pages/Leaderboard.tsx index 9566ab1..540703f 100644 --- a/src/pages/Leaderboard.tsx +++ b/src/pages/Leaderboard.tsx @@ -1,7 +1,7 @@ import { useEffect, useState } from "react"; import Skeleton from "../components/Skeleton"; - -const API_BASE = import.meta.env.VITE_API_URL ?? ""; +import { useTranslation } from 'react-i18next'; +import { api } from "../lib/api"; type Badge = "gold" | "silver" | "bronze" | "unranked"; type Trend = "up" | "down" | "stable"; @@ -9,50 +9,53 @@ type Trend = "up" | "down" | "stable"; interface Vendor { id: string; name: string; - address: string; avg_freshness_score: number; total_scans: number; - trust_badge: Badge; - trend: Trend; + trust_score: number; } -const BADGE: Record = { - gold: { label: "[ GOLD ]", color: "var(--color-neon-yellow, #f59e0b)" }, - silver: { label: "[ SILVER ]", color: "var(--color-on-surface, #9ca3af)" }, - bronze: { label: "[ BRONZE ]", color: "var(--color-neon-orange, #f97316)" }, +const BADGE: Record = { + gold: { labelKey: 'leaderboard.badge.gold', color: "var(--color-neon-yellow, #f59e0b)" }, + silver: { labelKey: 'leaderboard.badge.silver', color: "var(--color-on-surface, #9ca3af)" }, + bronze: { labelKey: 'leaderboard.badge.bronze', color: "var(--color-neon-orange, #f97316)" }, unranked: { - label: "[ UNRANKED ]", + labelKey: 'leaderboard.badge.unranked', color: "var(--color-outline-variant, #6b7280)", }, }; -const TREND: Record = { - up: { - icon: "^", - color: "var(--color-neon-green, #22c55e)", - label: "Improving", - }, - down: { icon: "v", color: "var(--color-error, #ef4444)", label: "Declining" }, - stable: { - icon: "-", - color: "var(--color-on-surface, #9ca3af)", - label: "Stable", - }, +const TREND: Record = { + up: { icon: "^", color: "var(--color-neon-green, #22c55e)", labelKey: 'leaderboard.trend.improving' }, + down: { icon: "v", color: "var(--color-error, #ef4444)", labelKey: 'leaderboard.trend.declining' }, + stable: { icon: "-", color: "var(--color-on-surface, #9ca3af)", labelKey: 'leaderboard.trend.stable' }, }; export default function Leaderboard() { - const [vendors, setVendors] = useState([]); + const { t } = useTranslation(); + + const [vendors, setVendors] = useState([]); const [loading, setLoading] = useState(true); - const [error, setError] = useState(null); + const [errorKey, setErrorKey] = useState(null); + + const getBadgeFromScore = (score: number): Badge => { + if (score >= 90) return 'gold'; + if (score >= 80) return 'silver'; + if (score >= 70) return 'bronze'; + return 'unranked'; + }; useEffect(() => { - fetch(`${API_BASE}/api/v1/vendors/leaderboard`) - .then((r) => { - if (!r.ok) throw new Error("Failed to fetch leaderboard."); - return r.json(); - }) + setLoading(true); + api.getLeaderboard() .then((data) => setVendors(data.leaderboard || [])) - .catch((e) => setError(e.message)) + .catch((err) => { + if (err instanceof Error && err.message.startsWith('error.')) { + setErrorKey(err.message); + } else { + setErrorKey('leaderboard.failedFetchLeaderboard'); + } + console.error("Leaderboard fetch error:", err); + }) .finally(() => setLoading(false)); }, []); @@ -96,31 +99,32 @@ export default function Leaderboard() {
); - if (error) + if (errorKey) return (
- {error} + {t(errorKey)}
); return (

- VENDOR TRUST LEADERBOARD + {t('leaderboard.title')}

- RANKINGS BASED ON ANONYMOUS FRESHNESS SCANS ACROSS MARKETS + {t('leaderboard.subtitle')}

{vendors.length === 0 ? (

- NO VENDOR DATA YET. + {t('leaderboard.noVendorData')}

) : (
{vendors.map((vendor, index) => { - const badge = BADGE[vendor.trust_badge ?? "unranked"]; - const trend = TREND[vendor.trend ?? "stable"]; + const badgeType = getBadgeFromScore(vendor.trust_score ?? 0); + const badge = BADGE[badgeType]; + const trend = TREND['stable']; // Trend data is not available from the API return (
- {badge.label} + {t(badge.labelKey)}

{vendor.name}

-

- {vendor.address} -

{(vendor.avg_freshness_score ?? 0).toFixed(1)} - - /100 - + {t('ashboard.scorePercentage')}

- {vendor.total_scans ?? 0} SCANS + {vendor.total_scans ?? 0} {t('leaderboard.scans')}

{trend.icon} diff --git a/src/pages/MarketMapPage.tsx b/src/pages/MarketMapPage.tsx index aa62eab..2619cac 100644 --- a/src/pages/MarketMapPage.tsx +++ b/src/pages/MarketMapPage.tsx @@ -6,6 +6,7 @@ import "leaflet/dist/leaflet.css"; import GlassCard from "../components/GlassCard"; import StatusTerminal from "../components/StatusTerminal"; import Skeleton from "../components/Skeleton"; +import { useTranslation } from 'react-i18next'; import { api } from "../lib/api"; import type { Market } from "../lib/types"; @@ -58,10 +59,12 @@ function RecenterMap({ center }: { center: [number, number] }) { } export default function MarketMapPage() { - const [markers, setMarkers] = useState([]); + const { t } = useTranslation(); + + const [markers, setMarkers] = useState([]); const [selected, setSelected] = useState(null); const [loading, setLoading] = useState(true); - const [error, setError] = useState(""); + const [errorKey, setErrorKey] = useState(""); const [tileUrl, setTileUrl] = useState(getActiveTile); const [mapCenter, setMapCenter] = useState<[number, number]>([22.5726, 88.3639]); const [regionName, setRegionName] = useState("KOLKATA"); @@ -83,7 +86,12 @@ export default function MarketMapPage() { const res = await api.getLiveMarkets(lat, lng); setMarkers(res.markets || []); } catch (err) { - setError(err instanceof Error ? err.message : "Failed to load live market data."); + // Handle translatable error keys from the API, with a specific fallback for this page. + if (err instanceof Error && err.message.startsWith('error.')) { + setErrorKey(err.message); + } else { + setErrorKey('marketMap.failedLoadMarketData'); + } console.error("Live market fetch error:", err); } finally { setLoading(false); @@ -102,16 +110,16 @@ export default function MarketMapPage() { (err) => { console.warn("Geolocation denied or failed, falling back to mock data.", err); api.getMarkets() - .then(res => setMarkers(res.markets)) - .catch(() => setError("Failed to load markets.")) + .then(res => setMarkers(res.markets || [])) + .catch(() => setErrorKey('marketMap.failedLoadMarkets')) .finally(() => setLoading(false)); }, { timeout: 10000, enableHighAccuracy: false } ); } else { api.getMarkets() - .then(res => setMarkers(res.markets)) - .catch(() => setError("Failed to load markets.")) + .then(res => setMarkers(res.markets || [])) + .catch(() => setErrorKey('marketMap.failedLoadMarkets')) .finally(() => setLoading(false)); } }, []); @@ -122,25 +130,21 @@ export default function MarketMapPage() {

- Market Trust Map + {t('marketMap.marketTrustTitle')} {t('marketMap.mapTitle')}

- LEADERBOARD + {t('marketMap.leaderboardLink')}
@@ -170,15 +174,10 @@ export default function MarketMapPage() {
= 85 - ? "#b5d25e" - : m.score >= 70 - ? "#c3f400" - : "#ffb4ab", + color: m.score >= 85 ? "#b5d25e" : m.score >= 70 ? "#c3f400" : "#ffb4ab", }} > - SCORE: {m.score} | VENDORS: {m.vendors} + {t('marketMap.scorePrefix')}{m.score} | {t('marketMap.vendorsPrefix')}{m.vendors}
@@ -189,9 +188,9 @@ export default function MarketMapPage() { {/* Bottom panel */}
- {error && ( + {errorKey && (

- {error} + {t(errorKey)}

)} @@ -221,7 +220,7 @@ export default function MarketMapPage() { {selected.name} - {selected.vendors} VENDORS + {selected.vendors} {t('arketMap.vendorsLabel')}
@@ -230,9 +229,7 @@ export default function MarketMapPage() { > {selected.score} - - AVG_FRESHNESS - + {t('esults.avgFreshness')}
@@ -246,22 +243,20 @@ export default function MarketMapPage() { /* IDLE/EMPTY STATE */
- SELECT_MARKET_NODE + {t('marketMap.selectMarketNode')}
)}
{[ - { l: "HIGH (85+)", c: "bg-secondary" }, - { l: "MED (70-84)", c: "bg-neon" }, - { l: "LOW (<70)", c: "bg-error" }, + { l: t('marketMap.highTrust'), c: "bg-secondary" }, + { l: t('marketMap.mediumTrust'), c: "bg-neon" }, + { l: t('marketMap.lowTrust'), c: "bg-error" }, ].map((x) => (
-
- - {x.l} - +
+
{x.l}
))}
diff --git a/src/pages/ModeSelectPage.tsx b/src/pages/ModeSelectPage.tsx index 82c2c28..b7df66b 100644 --- a/src/pages/ModeSelectPage.tsx +++ b/src/pages/ModeSelectPage.tsx @@ -5,51 +5,53 @@ import StatusTerminal from '../components/StatusTerminal'; import GlassCard from '../components/GlassCard'; import { api } from '../lib/api'; import type { GradcamResponse } from '../lib/api'; +import { useTranslation } from 'react-i18next'; // ── Mode Cards data ──────────────────────────────────────────────────────────── const modes = [ { icon: ScanLine, - title: 'Individual Scan', - code: 'MODE_SINGLE', - desc: 'Point-and-analyze a single specimen. Optimal for retail consumers verifying individual purchase quality.', - stat: 'AVG_TIME: 2.3s', + titleKey: 'modeSelect.individual.title', + codeKey: 'modeSelect.individual.code', + descKey: 'modeSelect.individual.desc', + statKey: 'modeSelect.individual.stat', to: '/scanner', }, { icon: Layers, - title: 'Batch Assessment', - code: 'MODE_BATCH', - desc: 'Multi-specimen sweep across a display. Designed for wholesale buyers processing 20+ units per session.', - stat: 'THROUGHPUT: 12/min', + titleKey: 'modeSelect.batch.title', + codeKey: 'modeSelect.batch.code', + descKey: 'modeSelect.batch.desc', + statKey: 'modeSelect.batch.stat', to: '/scanner', }, { icon: MapPin, - title: 'Market Survey', - code: 'MODE_SURVEY', - desc: 'Contribute to the crowdsourced Trust Map. Survey an entire market stall and submit anonymized freshness data.', - stat: 'DATA_POINTS: 47.2K', + titleKey: 'modeSelect.survey.title', + codeKey: 'modeSelect.survey.code', + descKey: 'modeSelect.survey.desc', + statKey: 'modeSelect.survey.stat', to: '/map', }, ]; // ── Grad-CAM class colours ──────────────────────────────────────────────────── -const CLASS_META: Record = { - 0: { label: 'FRESH', colour: '#39ff14', bg: 'rgba(57,255,20,0.12)' }, - 1: { label: 'MODERATE', colour: '#f5a623', bg: 'rgba(245,166,35,0.12)' }, - 2: { label: 'SPOILED', colour: '#ff4040', bg: 'rgba(255,64,64,0.12)' }, +const CLASS_META: Record = { + 0: { labelKey: 'modeSelect.classificationFresh', colour: '#39ff14', bg: 'rgba(57,255,20,0.12)' }, + 1: { labelKey: 'modeSelect.classificationModerate', colour: '#f5a623', bg: 'rgba(245,166,35,0.12)' }, + 2: { labelKey: 'modeSelect.classificationSpoiled', colour: '#ff4040', bg: 'rgba(255,64,64,0.12)' }, }; // ── Grad-CAM Viewer component ───────────────────────────────────────────────── function GradCamViewer() { + const { t } = useTranslation(); const [originalSrc, setOriginalSrc] = useState(null); const [result, setResult] = useState(null); const [loading, setLoading] = useState(false); - const [error, setError] = useState(null); + const [errorKey, setErrorKey] = useState(null); const [notAFish, setNotAFish] = useState(false); const [dragging, setDragging] = useState(false); const fileInputRef = useRef(null); @@ -57,7 +59,7 @@ function GradCamViewer() { // Process a File object — show preview & call API const processFile = useCallback(async (file: File) => { if (!file.type.startsWith('image/')) { - setError('Please upload a valid image file (JPEG / PNG / WebP).'); + setErrorKey('gradcam.invalidFileError'); return; } @@ -67,7 +69,7 @@ function GradCamViewer() { reader.readAsDataURL(file); setLoading(true); - setError(null); + setErrorKey(null); setResult(null); setNotAFish(false); @@ -76,12 +78,32 @@ function GradCamViewer() { const res = await api.getGradcam(blob); setResult(res); } catch (err: unknown) { - const msg = err instanceof Error ? err.message : 'Grad-CAM generation failed.'; - if (msg.startsWith('NOT_A_FISH')) { - setNotAFish(true); - // keep originalSrc so user can see what they uploaded + // Centralized and robust error handling. + // We determine the correct translation key first, then translate and set the error. + let errorKey = 'error.unknown'; + let shouldSetError = true; + + if (err instanceof Error) { + const msg = err.message; + + if (msg.startsWith('error.')) { + // Ideal path: The API layer provided a specific translation key. + errorKey = msg; + } else if (msg.toLowerCase().includes('failed to fetch')) { + // Fallback for raw network errors that weren't caught by the API layer. + errorKey = 'error.network.connection'; + } else if (msg.startsWith('NOT_A_FISH')) { + setNotAFish(true); + shouldSetError = false; // Don't show a generic error for this specific case. + } } else { - setError(msg); + // This handles non-Error exceptions. + errorKey = 'gradcam.generationFailedError'; + console.error('Grad-CAM processing non-error thrown:', err); + } + + if (shouldSetError) { + setErrorKey(errorKey); } } finally { setLoading(false); @@ -105,7 +127,7 @@ function GradCamViewer() { const reset = () => { setOriginalSrc(null); setResult(null); - setError(null); + setErrorKey(null); setNotAFish(false); if (fileInputRef.current) fileInputRef.current.value = ''; }; @@ -122,16 +144,14 @@ function GradCamViewer() {

- Grad-CAM Viewer + {t('modeSelect.gradcamViewerTitle')}

- XAI_MODULE + {t('modeSelect.xaiModule')}

- Upload a fish image to visualise which regions the Stream A neural network - focuses on for freshness classification. Colours range from blue (low attention) - to red (high attention). + {t('modeSelect.gradcamDescription')}

@@ -154,10 +174,10 @@ function GradCamViewer() { >

- Click to upload or drag & drop + {t('modeSelect.clickToUpload')} {t('modeSelect.orDragDrop')}

- JPEG · PNG · WebP — any resolution + {t('modeSelect.acceptedFormats')}

- +
)} @@ -185,8 +205,8 @@ function GradCamViewer() { {originalSrc && (
Rejected upload @@ -197,17 +217,16 @@ function GradCamViewer() {

- NOT_A_FISH_DETECTED + {t('gradcam.notAFishDetected')}

- The uploaded image does not appear to contain a fish. - Please upload a clear photo of a fish body, eye, or gill. + {t('gradcam.notAFishText')}

@@ -217,7 +236,7 @@ function GradCamViewer() { onClick={() => fileInputRef.current?.click()} className="text-xs text-neon/70 hover:text-neon transition-colors font-[family-name:var(--font-mono)] tracking-wide flex items-center gap-1.5" > - UPLOAD_DIFFERENT_IMAGE + {t('gradcam.uploadDifferentImage')}
-

{error}

+

{t(errorKey)}

-
@@ -255,7 +278,7 @@ function GradCamViewer() { className="font-[family-name:var(--font-mono)] text-xs font-bold px-2 py-0.5" style={{ color: classMeta!.colour, background: classMeta!.colour + '20' }} > - {classMeta!.label} + {t(classMeta!.labelKey)} {result.predicted_class} @@ -264,13 +287,13 @@ function GradCamViewer() {
{result.mode === 'demo' && ( - DEMO_MODE + {t('modeSelect.demoMode')} )} @@ -281,13 +304,13 @@ function GradCamViewer() {
{/* Original */}
-

- ORIGINAL_INPUT -

+

+ {t('gradcam.originalInput')} +

Original uploaded image
@@ -296,12 +319,12 @@ function GradCamViewer() { {/* Grad-CAM overlay */}

- ACTIVATION_MAP {result.mode === 'real' ? '· STREAM_A' : '· SYNTHETIC'} + {t('gradcam.activationMap')} {result.mode === 'real' ? `· ${t('gradcam.streamA')}` : `· ${t('gradcam.synthetic')}`}

Grad-CAM heatmap overlay {/* Legend overlay */} @@ -310,7 +333,7 @@ function GradCamViewer() {
))} - LOW → HIGH + {t('gradcam.lowToHigh')}
@@ -322,7 +345,7 @@ function GradCamViewer() { onClick={() => fileInputRef.current?.click()} className="text-xs text-neon/70 hover:text-neon transition-colors font-[family-name:var(--font-mono)] tracking-wide flex items-center gap-1.5" > - UPLOAD_NEW_IMAGE + {t('gradcam.uploadNewImage')}
{/* Header */}

- Select Operation + {t('modeSelect.selectOperation')}
- Mode + {t('modeSelect.mode')}

- Choose your scanning protocol. Each mode is optimized for different - operational contexts and specimen volumes. + {t('modeSelect.description')}

{/* Mode Cards */} @@ -376,16 +400,16 @@ export default function ModeSelectPage() {

- {mode.title} + {t(mode.titleKey)}

- {mode.code} + {t(mode.codeKey)}

- {mode.desc} + {t(mode.descKey)}

- +
{/* Arrow */} @@ -403,15 +427,15 @@ export default function ModeSelectPage() { {/* ── Grad-CAM Viewer ───────────────────────────────────────────────── */}

- Explainability Toolkit + {t('modeSelect.explainability', 'Explainability')} {t('modeSelect.toolkit', 'Toolkit')}

- Understand what the model sees. Upload any fish photo to generate a - Gradient-weighted Class Activation Map (Grad-CAM) heatmap. + {t('modeSelect.gradcamSectionDescription', + 'Understand what the model sees. Upload any fish photo to generate a Gradient-weighted Class Activation Map (Grad-CAM) heatmap.')}

@@ -419,7 +443,7 @@ export default function ModeSelectPage() { {/* Footer Info */}
diff --git a/src/pages/NotFound.tsx b/src/pages/NotFound.tsx index e171101..aa5a5f0 100644 --- a/src/pages/NotFound.tsx +++ b/src/pages/NotFound.tsx @@ -1,20 +1,24 @@ // src/pages/NotFound.tsx import { Link } from 'react-router-dom'; +import { useTranslation } from 'react-i18next'; export default function NotFound() { + const { t } = useTranslation(); + + return (
-

404

-

Page Not Found

+

{t('notFound.errorCode')}

+

{t('notFound.pageNotFound')}

- Oops! The page you are looking for doesn't exist or has been moved. + {t('notFound.errorMessage')}

- Return Home + {t('notFound.returnHome')}
); -} \ No newline at end of file +} diff --git a/src/pages/PublicReport.tsx b/src/pages/PublicReport.tsx index eb88a86..ac84978 100644 --- a/src/pages/PublicReport.tsx +++ b/src/pages/PublicReport.tsx @@ -1,5 +1,6 @@ import { useEffect, useState } from 'react'; import { useParams } from 'react-router-dom'; +import { useTranslation } from 'react-i18next'; import StatusTerminal from '../components/StatusTerminal'; interface ScanData { @@ -12,8 +13,10 @@ interface ScanData { } export default function PublicReport() { - const { id } = useParams(); - const [scan, setScan] = useState(null); + const { t } = useTranslation(); + + const { id } = useParams(); + const [scan, setScan] = useState(null); const [copied, setCopied] = useState(false); const [error, setError] = useState(false); @@ -38,7 +41,7 @@ export default function PublicReport() { if (error) { return (
- +
); } @@ -46,7 +49,7 @@ export default function PublicReport() { if (!scan) { return (
- +
); } @@ -58,29 +61,29 @@ export default function PublicReport() { {/* Header */}

- FreshScan Public Report + {t('publicReport.freshscanBrand')}{t('publicReport.publicReport')}

- GENERATED: {new Date(scan.created_at).toLocaleString()} | ID: {scan.id} + {t('publicReport.generatedPrefix')}{new Date(scan.created_at).toLocaleString()} {t('publicReport.separator')} {t('publicReport.idPrefix')}{scan.id}

{/* Score Card */}
-

FRESHNESS_SCORE

+

{t('publicReport.freshnessScore')}

= 85 ? 'text-secondary' : 'text-neon'} print:text-black mb-4`}> {scan.freshness_score}

- GRADE {scan.grade} — {scan.label} + {t('publicReport.gradeBadge')}{scan.grade} {t('publicReport.separator')} {scan.label}

{/* Data Markers */}
-

RAW_MARKERS

+

{t('publicReport.rawMarkers')}

             {JSON.stringify(scan.markers, null, 2)}
@@ -92,16 +95,16 @@ export default function PublicReport() { onClick={handleShare} className="flex-1 py-3 bg-secondary text-on-primary font-display font-bold text-sm tracking-wider uppercase transition-colors hover:brightness-110 border-none cursor-pointer" > - {copied ? 'COPIED TO CLIPBOARD' : 'COPY SHARE LINK'} + {copied ? t('publicReport.copiedClipboard') : t('publicReport.copyShareLink')}
); -} \ No newline at end of file +} diff --git a/src/pages/ResultsPage.tsx b/src/pages/ResultsPage.tsx index 7e84312..2b35281 100644 --- a/src/pages/ResultsPage.tsx +++ b/src/pages/ResultsPage.tsx @@ -1,5 +1,6 @@ import { useEffect, useState } from 'react'; import { Link } from 'react-router-dom'; +import { useTranslation } from 'react-i18next'; import { ArrowRight } from 'lucide-react'; import GlassCard from '../components/GlassCard'; import StatusTerminal from '../components/StatusTerminal'; @@ -7,10 +8,12 @@ import { api } from '../lib/api'; import type { HistoryScan, HistoryStats } from '../lib/types'; export default function ResultsPage() { - const [scans, setScans] = useState([]); + const { t } = useTranslation(); + + const [scans, setScans] = useState([]); const [stats, setStats] = useState(null); const [loading, setLoading] = useState(true); - const [error, setError] = useState(''); + const [errorKey, setErrorKey] = useState(''); useEffect(() => { async function load() { @@ -20,7 +23,14 @@ export default function ResultsPage() { setScans(res.scans); setStats(res.stats); } catch (err) { - setError(err instanceof Error ? err.message : 'Failed to load history.'); + // Use the same robust error handling as other pages - Ensures that both API keys (like 'error.network.connection') and generic errors are translated correctly. + if (err instanceof Error && err.message.startsWith('error.')) { + setErrorKey(err.message); + } else { + // Fallback for other errors, including raw "Failed to fetch" + setErrorKey('results.failedToLoadHistory'); + } + console.error("History fetch error:", err); } finally { setLoading(false); } @@ -31,23 +41,23 @@ export default function ResultsPage() { if (loading) { return (
- +
); } - if (error) { + if (errorKey) { return (
- +

- {error} + {t(errorKey)}

- SIGN_IN_REQUIRED + {t('results.signInRequired')}
); @@ -62,21 +72,21 @@ export default function ResultsPage() {

- Scan Results + {t('results.scanTitle')}{t('results.resultsTitle')}

{/* Summary stats */}
- TOTAL_SCANS + {t('results.totalScans')} {totalScans} @@ -84,7 +94,7 @@ export default function ResultsPage() { - AVG_FRESHNESS + {t('results.avgFreshness')} {avgScore} @@ -92,7 +102,7 @@ export default function ResultsPage() { - FRESH_RATE + {t('results.freshRate')} {freshRate}% @@ -103,12 +113,12 @@ export default function ResultsPage() { {/* History list */} {scans.length === 0 ? (
- + - INITIATE_FIRST_SCAN + {t('results.initiateFirstScan')}
) : ( @@ -178,3 +188,4 @@ export default function ResultsPage() {
); } + diff --git a/src/pages/ScannerPage.tsx b/src/pages/ScannerPage.tsx index af78763..005f897 100644 --- a/src/pages/ScannerPage.tsx +++ b/src/pages/ScannerPage.tsx @@ -1,5 +1,6 @@ import { useState, useEffect, useCallback, useRef } from "react"; import { useNavigate } from "react-router-dom"; +import { useTranslation } from 'react-i18next'; import { Camera, Zap, @@ -15,6 +16,13 @@ import { api, isAuthenticated } from "../lib/api"; import { FishFreshnessInference } from "../fusionInference.js"; import type { ScanResult } from "../lib/types"; + +function translateResultLabel(label: DisplayResult['label'], t: (key: string) => string) { + if (label === 'Fresh') return t('scanner.fresh'); + if (label === 'Moderate') return t('scanner.moderate'); + return t('scanner.spoiled'); +} + // ───────────────────────────────────────────────────────────────────────────── // Types // ───────────────────────────────────────────────────────────────────────────── @@ -103,13 +111,15 @@ async function blobToImageElement(blob: Blob): Promise { // ───────────────────────────────────────────────────────────────────────────── export default function ScannerPage() { - const navigate = useNavigate(); + const { t } = useTranslation(); + const navigate = useNavigate(); + // ── State ────────────────────────────────────────────────────────────────── const [scanPhase, setScanPhase] = useState("idle"); const [inferenceMode, setInferenceMode] = useState(null); const [result, setResult] = useState(null); - const [error, setError] = useState(""); + const [errorKey, setErrorKey] = useState(""); const [flashOn, setFlashOn] = useState(false); const [facingMode, setFacingMode] = useState<"environment" | "user">( "environment", @@ -117,7 +127,7 @@ export default function ScannerPage() { const [progress, setProgress] = useState(0); const [copied, setCopied] = useState(false); const [previewUrl, setPreviewUrl] = useState(null); - const [cameraError, setCameraError] = useState(null); + const [cameraErrorKey, setCameraErrorKey] = useState(null); const videoRef = useRef(null); const fileInputRef = useRef(null); @@ -143,7 +153,7 @@ export default function ScannerPage() { return; } - setCameraError(null); + setCameraErrorKey(null); streamRef.current = stream; if (currentVideo) { @@ -157,18 +167,14 @@ export default function ScannerPage() { if (err instanceof DOMException) { if (err.name === "NotAllowedError") { - setCameraError("Camera permission was denied"); + setCameraErrorKey('scanner.cameraPermissionDenied'); } else if (err.name === "NotFoundError") { - setCameraError( - "No camera was found on this device. Please connect a camera and try again.", - ); + setCameraErrorKey('scanner.cameraNotFound'); } else { - setCameraError( - "Unable to access the camera. Please check your browser permissions and try again.", - ); + setCameraErrorKey('scanner.cameraAccessError'); } } else { - setCameraError("Something went wrong while accessing the camera."); + setCameraErrorKey('scanner.cameraSomethingWrong'); } }); @@ -181,7 +187,7 @@ export default function ScannerPage() { currentVideo.srcObject = null; } }; - }, [facingMode, scanPhase]); + }, [facingMode, scanPhase, t]); // ── Progress bar animation ───────────────────────────────────────────────── const startProgress = useCallback(() => { @@ -208,7 +214,7 @@ export default function ScannerPage() { async (blob: Blob) => { setScanPhase("processing"); startProgress(); - setError(""); + setErrorKey(""); setInferenceMode(null); sessionStorage.removeItem("lastScanId"); @@ -254,57 +260,6 @@ export default function ScannerPage() { stopProgress(100); const freshness = Math.round(fusion.fusedScore * 100); - const offlineScanResult = { - scan_id: "offline-scan", - scan_display_id: "OFFLINE_SCAN", - freshness_index: freshness, - grade: deriveGrade(freshness), - confidence: parseFloat(fusion.confidence), - classification: - fusion.label === "Fresh" - ? "FRESH" - : fusion.label === "Moderate" - ? "FRESH" - : "SPOILED", - is_fresh: fusion.label !== "Spoiled", - uncertain_flag: false, - species: { - common_name: "Unknown Fish", - scientific_name: "N/A", - habitat: "N/A", - tags: [], - weight_estimate_kg: 0, - catch_age_hours: 0, - }, - biomarkers: { - gill_saturation: { - score: freshness, - status: "NOMINAL", - detail: "Offline edge inference", - }, - corneal_clarity: { - score: freshness, - status: "NOMINAL", - detail: "Offline edge inference", - }, - epidermal_tension: { - score: freshness, - status: "NOMINAL", - detail: "Offline edge inference", - }, - }, - recommendations: { - consume_within_hours: 0, - storage_temp: "Unknown", - alert_flags: ["Generated from offline scan"], - }, - }; - - sessionStorage.setItem( - "offlineScanResult", - JSON.stringify(offlineScanResult), - ); - setResult({ label: fusion.label, freshness, @@ -329,7 +284,6 @@ export default function ScannerPage() { fused_score: fusion.fusedScore, source: "edge_onnx", }, - { silent: true }, ); if (saved?.scan?.scan_id) { sessionStorage.setItem("lastScanId", saved.scan.scan_id); @@ -345,19 +299,18 @@ export default function ScannerPage() { setTimeout(() => navigate("/analysis"), 1800); } catch (err) { stopProgress(0); - const msg = err instanceof Error ? err.message : "Inference failed."; + const msg = err instanceof Error ? err.message : 'scanner.inferenceFailed'; const isNotFish = msg.includes("NOT_A_FISH") || msg.includes("not appear to contain a fish"); - setError( + setErrorKey( isNotFish - ? "NOT_A_FISH: No fish detected. Please photograph a fish." - : msg, + ? 'scanner.notFishDetected' + : msg || 'scanner.inferenceFailed', ); setScanPhase("error"); } - }, - [startProgress, stopProgress, stopCamera, navigate], + }, [startProgress, stopProgress, stopCamera, navigate] ); // ── Camera capture ───────────────────────────────────────────────────────── @@ -370,7 +323,7 @@ export default function ScannerPage() { if (!video) return; const blob = await captureVideoBlob(video); if (!blob) { - setError("Failed to capture frame."); + setErrorKey('scanner.failedCaptureFrame'); return; } await runScan(blob); @@ -399,7 +352,7 @@ export default function ScannerPage() { const resetScan = useCallback(() => { setScanPhase("idle"); setResult(null); - setError(""); + setErrorKey(""); setInferenceMode(null); setProgress(0); if (previewUrl) { @@ -419,16 +372,16 @@ export default function ScannerPage() { const terminalMessages = (() => { if (isScanning && inferenceMode === "edge") - return ["MODE: EDGE_ONNX", "RUNNING_LOCAL_INFERENCE..."]; + return [t('scanner.modeEdgeOnnx'), t('scanner.runningLocalInference')]; if (isScanning && inferenceMode === "cloud") - return ["MODE: CLOUD_API", "CONNECTING_TO_HF..."]; - if (isScanning) return ["DETECTING_MODEL...", "PLEASE_WAIT"]; + return [t('scanner.modeCloudApi'), t('scanner.connectingToHf')]; + if (isScanning) return [t('scanner.detectingModel'), t('scanner.pleaseWait')]; if (scanComplete && inferenceMode === "edge") - return ["MODEL: EDGE_ONNX", "DEVICE: ON_DEVICE", "LATENCY: <50ms"]; + return [t('scanner.modelEdgeOnnx'), t('scanner.deviceOnDevice'), t('scanner.latencyValue')]; if (scanComplete && inferenceMode === "cloud") - return ["MODEL: CLOUD_API", "DEVICE: HF_INFERENCE"]; - if (scanPhase === "error") return ["SCAN_SEQ: FAILED", "CHECK_SPECIMEN"]; - return ["SYSTEM: READY", "POINT_CAMERA_AT_FISH"]; + return [t('scanner.modelCloudApi'), t('scanner.deviceHfInference')]; + if (scanPhase === "error") return [t('scanner.scanSeqFailed'), errorKey ? t(errorKey) : t('scanner.checkSpecimen')]; + return [t('scanner.systemReady'), t('scanner.pointCameraAtFish')]; })(); // ── Render ───────────────────────────────────────────────────────────────── @@ -441,21 +394,20 @@ export default function ScannerPage() { {previewUrl && !isScanning ? ( Captured - ) : cameraError ? ( + ) : cameraErrorKey ? (

- Camera Access Needed + {t('scanner.cameraAccessNeeded')}

-

{cameraError}

+

{t(cameraErrorKey)}

- Click the camera icon in your browser's address bar, allow - camera access, and refresh the page. + {t('scanner.cameraInstructions')}

@@ -502,16 +454,16 @@ export default function ScannerPage() {
{scanPhase === "idle" && ( <> - {!cameraError && ( + {!cameraErrorKey && ( - POINT_AT_FISH + {t('scanner.pointAtFish')} )} )} {isScanning && ( - ANALYZING_BIOMARKERS + {t('scanner.analyzingBiomarkers')} )} {scanComplete && result && ( @@ -519,16 +471,16 @@ export default function ScannerPage() { - {result.label.toUpperCase()} + {translateResultLabel(result.label, t).toUpperCase()} - {result.confidence} · GRADE {result.grade} + {result.confidence} · {t('scanner.gradePrefix')}{result.grade}
)} {scanPhase === "error" && ( - {error} + {t(errorKey)} )}
@@ -592,12 +544,12 @@ export default function ScannerPage() { className="flex-1 py-4 bg-neon text-on-primary font-[family-name:var(--font-display)] font-bold text-sm tracking-wider cursor-pointer border-none flex items-center justify-center gap-3 hover:bg-neon-dim pulse-glow transition-all duration-200" > - CAPTURE_FISH + {t('scanner.captureButton')} @@ -609,7 +561,7 @@ export default function ScannerPage() { className="w-full py-3 bg-surface-mid text-on-surface font-[family-name:var(--font-display)] font-bold text-sm tracking-wider cursor-pointer border border-on-surface-variant/30 hover:border-neon hover:text-neon flex items-center justify-center gap-3 transition-all duration-200" > - UPLOAD_PHOTO + {t('scanner.uploadButton')} {inferenceMode === "edge" - ? "RUNNING_EDGE_INFERENCE..." - : "RUNNING_CLOUD_INFERENCE..."} + ? t('scanner.runningEdgeInference') + : t('scanner.runningCloudInference')}
)} @@ -640,9 +592,7 @@ export default function ScannerPage() { {/* Freshness score bar */}
- - FRESHNESS_INDEX - + {t('canner.freshnessIndex')} @@ -662,7 +612,7 @@ export default function ScannerPage() { onClick={() => navigate("/analysis")} className="flex-1 py-3 bg-neon text-on-primary font-[family-name:var(--font-display)] font-bold text-xs tracking-wider border-none cursor-pointer flex items-center justify-center hover:bg-neon-dim transition-all duration-200" > - VIEW_ANALYSIS + {t('scanner.viewAnalysisButton')} )}
@@ -697,7 +647,7 @@ export default function ScannerPage() { {scanPhase === "error" && (
- {error} + {t(errorKey)}