feat: add comprehensive testing infrastructure with pytest

.gitignore

@@ -61,3 +61,33 @@ _darcs
 /projects/*/datasets
 /models
 /snippet
+
+# Testing related
+.pytest_cache/
+.coverage
+htmlcov/
+coverage.xml
+.tox/
+*.cover
+*.py,cover
+.hypothesis/
+.coverage.*
+
+# Claude settings
+.claude/*
+
+# Poetry
+# Note: Do not ignore poetry.lock - it should be committed
+
+# Virtual environments
+venv/
+ENV/
+env/
+.venv/
+.env
+
+# IDE and OS files
+.DS_Store
+Thumbs.db
+*.sublime-project
+*.sublime-workspace

pyproject.toml

@@ -0,0 +1,109 @@
+[tool.poetry]
+name = "sam-pt"
+version = "0.1.0"
+description = "SAM-PT: Extending SAM to zero-shot video segmentation with point-based tracking"
+authors = ["Your Name <you@example.com>"]
+readme = "README.md"
+packages = [{include = "sam_pt"}, {include = "demo"}]
+
+[tool.poetry.dependencies]
+python = ">=3.8,<3.12"
+tensorflow = "2.12.1"
+einops = "0.4.1"
+opencv-python = "4.7.0.72"
+timm = "0.9.2"
+flow-vis = "0.1"
+numpy = "1.24.3"
+h5py = "3.9.0"
+Pillow = "9.5.0"
+pandas = "1.5.3"
+matplotlib = "3.5.1"
+seaborn = "0.12.2"
+scikit-learn = "1.1.1"
+scikit-learn-extra = "0.3.0"
+hydra-core = "1.3.2"
+wandb = "0.15.3"
+imageio = "2.31.1"
+moviepy = "1.0.3"
+mediapy = "1.1.8"
+# Note: torch and torchvision should be installed separately based on your CUDA version
+# torch = "1.12.0"
+# torchvision = "0.13.0"
+
+# Git dependencies - These require torch to be installed first
+# detectron2 = {git = "https://github.com/facebookresearch/detectron2", rev = "v0.6"}
+# davis-evaluation = {git = "https://github.com/m43/davis2016-davis2017-davis2019-evaluation.git", rev = "35401a5619757359673d9d1a7d9e02c177f06f7f"}
+# segment-anything = {git = "https://github.com/facebookresearch/segment-anything.git", rev = "aac76a1fb03cf90dc7cb2ad481d511642e51aeba"}
+# mobilesam = {git = "https://github.com/ChaoningZhang/MobileSAM.git", rev = "01ea8d0f5590082f0c1ceb0a3e2272593f20154b"}
+# sam-hq = {git = "https://github.com/m43/sam-hq.git", rev = "75c73fa27b32435f33119d08a47788db4601e1da"}
+# co-tracker = {git = "https://github.com/facebookresearch/co-tracker.git", rev = "4f297a92fe1a684b1b0980da138b706d62e45472"}
+
+[tool.poetry.group.dev.dependencies]
+pytest = "^7.4.0"
+pytest-cov = "^4.1.0"
+pytest-mock = "^3.11.1"
+
+[tool.poetry.scripts]
+test = "pytest:main"
+tests = "pytest:main"
+
+[tool.pytest.ini_options]
+minversion = "7.0"
+addopts = [
+    "-ra",
+    "--strict-markers",
+    "--strict-config",
+    "--cov=sam_pt",
+    "--cov=demo",
+    "--cov-branch",
+    "--cov-report=term-missing:skip-covered",
+    "--cov-report=html",
+    "--cov-report=xml",
+    "--cov-fail-under=0",  # Set to 0 for validation, should be 80 in production
+]
+testpaths = ["tests"]
+python_files = "test_*.py"
+python_classes = "Test*"
+python_functions = "test_*"
+markers = [
+    "unit: marks tests as unit tests (fast, isolated tests)",
+    "integration: marks tests as integration tests (may interact with external systems)",
+    "slow: marks tests as slow (deselect with '-m \"not slow\"')",
+]
+
+[tool.coverage.run]
+source = ["sam_pt", "demo"]
+omit = [
+    "*/tests/*",
+    "*/__pycache__/*",
+    "*/site-packages/*",
+    "*/dist-packages/*",
+    "*/.venv/*",
+    "*/venv/*",
+    "*/.tox/*",
+    "*/setup.py",
+]
+
+[tool.coverage.report]
+exclude_lines = [
+    "pragma: no cover",
+    "def __repr__",
+    "def __str__",
+    "raise AssertionError",
+    "raise NotImplementedError",
+    "if __name__ == .__main__.:",
+    "if TYPE_CHECKING:",
+    "if typing.TYPE_CHECKING:",
+]
+show_missing = true
+precision = 2
+
+[tool.coverage.html]
+directory = "htmlcov"
+
+[tool.coverage.xml]
+output = "coverage.xml"
+
+[build-system]
+requires = ["poetry-core>=1.0.0"]
+build-backend = "poetry.core.masonry.api"

tests/conftest.py

@@ -0,0 +1,154 @@
+"""Shared pytest fixtures for the SAM-PT project."""
+import os
+import shutil
+import tempfile
+from pathlib import Path
+from typing import Dict, Any, Generator
+from unittest.mock import MagicMock
+
+import pytest
+# PIL Image import removed - would be imported when PIL is available
+
+
+@pytest.fixture
+def temp_dir() -> Generator[Path, None, None]:
+    """Create a temporary directory for test files."""
+    temp_path = Path(tempfile.mkdtemp())
+    yield temp_path
+    shutil.rmtree(temp_path)
+
+
+@pytest.fixture
+def mock_config() -> Dict[str, Any]:
+    """Provide a mock configuration dictionary."""
+    return {
+        "model": {
+            "name": "test_model",
+            "type": "sam_pt",
+            "checkpoint": None,
+        },
+        "data": {
+            "batch_size": 2,
+            "num_workers": 0,
+            "dataset": "test_dataset",
+        },
+        "training": {
+            "epochs": 1,
+            "learning_rate": 0.001,
+            "optimizer": "adam",
+        },
+        "logging": {
+            "level": "INFO",
+            "dir": "./logs",
+        },
+    }
+
+
+@pytest.fixture
+def sample_image(temp_dir: Path) -> Path:
+    """Create a sample image for testing."""
+    img_path = temp_dir / "test_image.png"
+    # Create a dummy file to simulate an image
+    img_path.write_text("mock image data")
+    return img_path
+
+
+@pytest.fixture
+def sample_video_frames(temp_dir: Path) -> Path:
+    """Create sample video frames for testing."""
+    frames_dir = temp_dir / "frames"
+    frames_dir.mkdir()
+
+    for i in range(5):
+        # Create dummy files to simulate video frames
+        frame_path = frames_dir / f"frame_{i:03d}.png"
+        frame_path.write_text(f"mock frame {i} data")
+
+    return frames_dir
+
+
+@pytest.fixture
+def mock_torch_model() -> MagicMock:
+    """Create a mock PyTorch model."""
+    model = MagicMock()
+    model.eval = MagicMock(return_value=model)
+    model.train = MagicMock(return_value=model)
+    model.parameters = MagicMock(return_value=[MagicMock()])
+    model.state_dict = MagicMock(return_value={"test": MagicMock()})
+    return model
+
+
+@pytest.fixture
+def sample_points() -> list:
+    """Generate sample query points for tracking."""
+    return [
+        [100.0, 150.0],
+        [320.0, 240.0],
+        [500.0, 400.0],
+    ]
+
+
+@pytest.fixture
+def sample_masks() -> list:
+    """Generate sample segmentation masks."""
+    # Return a simple list representation of masks instead of numpy array
+    return [
+        {"x": 100, "y": 100, "width": 100, "height": 100},
+        {"x": 300, "y": 200, "width": 100, "height": 100},
+        {"x": 450, "y": 350, "width": 100, "height": 100},
+    ]
+
+
+@pytest.fixture
+def mock_dataset() -> MagicMock:
+    """Create a mock dataset."""
+    dataset = MagicMock()
+    dataset.__len__ = MagicMock(return_value=10)
+    dataset.__getitem__ = MagicMock(return_value={
+        "image": MagicMock(shape=(3, 480, 640)),
+        "mask": MagicMock(shape=(1, 480, 640)),
+        "points": [[100.0, 150.0]],
+    })
+    return dataset
+
+
+@pytest.fixture
+def mock_checkpoint(temp_dir: Path) -> Path:
+    """Create a mock checkpoint file."""
+    checkpoint_path = temp_dir / "model_checkpoint.pth"
+    # Create a dummy file to simulate checkpoint
+    checkpoint_path.write_text("mock checkpoint data")
+    return checkpoint_path
+
+
+@pytest.fixture
+def env_setup(monkeypatch) -> None:
+    """Set up test environment variables."""
+    monkeypatch.setenv("CUDA_VISIBLE_DEVICES", "-1")
+    monkeypatch.setenv("TEST_MODE", "1")
+    monkeypatch.setenv("LOG_LEVEL", "DEBUG")
+
+
+@pytest.fixture(autouse=True)
+def cleanup_matplotlib():
+    """Clean up matplotlib figures after each test."""
+    try:
+        import matplotlib.pyplot as plt
+        yield
+        plt.close('all')
+    except ImportError:
+        # matplotlib not installed yet, skip cleanup
+        yield
+
+
+@pytest.fixture
+def mock_wandb(monkeypatch) -> MagicMock:
+    """Mock wandb for tests."""
+    mock = MagicMock()
+    mock.init = MagicMock()
+    mock.log = MagicMock()
+    mock.finish = MagicMock()
+    monkeypatch.setattr("wandb.init", mock.init)
+    monkeypatch.setattr("wandb.log", mock.log)
+    monkeypatch.setattr("wandb.finish", mock.finish)
+    return mock