Create tests/conftest.py

tests/conftest.py

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+"""
+Pytest configuration and fixtures for BackgroundFX Pro tests.
+"""
+
+import pytest
+import numpy as np
+import torch
+import cv2
+import tempfile
+import shutil
+from pathlib import Path
+from unittest.mock import Mock, MagicMock
+import os
+import sys
+
+# Add parent directory to path for imports
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+
+# ============================================================================
+# Configuration
+# ============================================================================
+
+@pytest.fixture(scope="session")
+def test_config():
+    """Test configuration."""
+    return {
+        'device': 'cpu',  # Use CPU for testing
+        'test_data_dir': Path(__file__).parent / 'data',
+        'temp_dir': tempfile.mkdtemp(prefix='bgfx_test_'),
+        'max_test_duration': 30,  # seconds
+        'use_gpu': torch.cuda.is_available()
+    }
+
+
+@pytest.fixture(scope="session", autouse=True)
+def cleanup(test_config):
+    """Cleanup after all tests."""
+    yield
+    # Clean up temp directory
+    if os.path.exists(test_config['temp_dir']):
+        shutil.rmtree(test_config['temp_dir'])
+
+
+# ============================================================================
+# Image and Video Fixtures
+# ============================================================================
+
+@pytest.fixture
+def sample_image():
+    """Create a sample image for testing."""
+    # Create 512x512 RGB image with a person-like shape
+    image = np.zeros((512, 512, 3), dtype=np.uint8)
+    
+    # Add background
+    image[:, :] = [100, 150, 200]  # Blue background
+    
+    # Add person-like shape (simple rectangle for testing)
+    cv2.rectangle(image, (150, 100), (350, 450), (50, 100, 50), -1)
+    
+    # Add some texture
+    noise = np.random.randint(0, 20, (512, 512, 3), dtype=np.uint8)
+    image = cv2.add(image, noise)
+    
+    return image
+
+
+@pytest.fixture
+def sample_mask():
+    """Create a sample mask for testing."""
+    mask = np.zeros((512, 512), dtype=np.uint8)
+    # Create person mask
+    cv2.rectangle(mask, (150, 100), (350, 450), 255, -1)
+    # Add some edge refinement
+    mask = cv2.GaussianBlur(mask, (5, 5), 2)
+    return mask
+
+
+@pytest.fixture
+def sample_background():
+    """Create a sample background image."""
+    background = np.zeros((512, 512, 3), dtype=np.uint8)
+    # Create gradient background
+    for i in range(512):
+        background[i, :] = [
+            int(255 * (i / 512)),  # Red gradient
+            100,  # Fixed green
+            int(255 * (1 - i / 512))  # Blue inverse gradient
+        ]
+    return background
+
+
+@pytest.fixture
+def sample_video(test_config):
+    """Create a sample video file for testing."""
+    video_path = Path(test_config['temp_dir']) / 'test_video.mp4'
+    
+    # Create video writer
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter(str(video_path), fourcc, 30.0, (512, 512))
+    
+    # Write 30 frames (1 second at 30fps)
+    for i in range(30):
+        frame = np.zeros((512, 512, 3), dtype=np.uint8)
+        # Animate a moving rectangle
+        x = 100 + i * 5
+        cv2.rectangle(frame, (x, 200), (x + 100, 400), (0, 255, 0), -1)
+        out.write(frame)
+    
+    out.release()
+    return str(video_path)
+
+
+# ============================================================================
+# Model Fixtures
+# ============================================================================
+
+@pytest.fixture
+def mock_model():
+    """Create a mock ML model for testing."""
+    model = MagicMock()
+    model.eval = MagicMock(return_value=None)
+    model.to = MagicMock(return_value=model)
+    
+    # Mock forward pass
+    def forward(x):
+        batch_size = x.shape[0] if hasattr(x, 'shape') else 1
+        return torch.randn(batch_size, 1, 512, 512)
+    
+    model.__call__ = MagicMock(side_effect=forward)
+    model.forward = MagicMock(side_effect=forward)
+    
+    return model
+
+
+@pytest.fixture
+def mock_sam2_predictor():
+    """Create a mock SAM2 predictor."""
+    predictor = MagicMock()
+    
+    def predict(image):
+        h, w = image.shape[:2] if len(image.shape) > 2 else (512, 512)
+        return np.random.randint(0, 2, (h, w), dtype=np.uint8) * 255
+    
+    predictor.predict = MagicMock(side_effect=predict)
+    predictor.set_image = MagicMock(return_value=None)
+    
+    return predictor
+
+
+@pytest.fixture
+def mock_matanyone_model():
+    """Create a mock MatAnyone model."""
+    model = MagicMock()
+    
+    def refine(image, mask):
+        return cv2.GaussianBlur(mask, (5, 5), 2)
+    
+    model.refine = MagicMock(side_effect=refine)
+    
+    return model
+
+
+# ============================================================================
+# Pipeline and Processing Fixtures
+# ============================================================================
+
+@pytest.fixture
+def pipeline_config():
+    """Create pipeline configuration for testing."""
+    from api.pipeline import PipelineConfig
+    
+    return PipelineConfig(
+        use_gpu=False,  # CPU for testing
+        quality_preset='medium',
+        enable_cache=False,  # Disable cache for testing
+        batch_size=1,
+        max_workers=2
+    )
+
+
+@pytest.fixture
+def mock_pipeline(pipeline_config):
+    """Create a mock processing pipeline."""
+    from api.pipeline import ProcessingPipeline
+    
+    # Mock the pipeline to avoid loading real models
+    with pytest.MonkeyPatch().context() as m:
+        m.setattr('api.pipeline.ModelFactory.load_model', 
+                  lambda self, *args, **kwargs: Mock())
+        pipeline = ProcessingPipeline(pipeline_config)
+    
+    return pipeline
+
+
+# ============================================================================
+# API and Server Fixtures
+# ============================================================================
+
+@pytest.fixture
+def api_client():
+    """Create a test client for the API."""
+    from fastapi.testclient import TestClient
+    from api.api_server import app
+    
+    return TestClient(app)
+
+
+@pytest.fixture
+def mock_job_manager():
+    """Create a mock job manager."""
+    manager = MagicMock()
+    manager.create_job = MagicMock(return_value='test-job-123')
+    manager.get_job = MagicMock(return_value={'status': 'processing'})
+    manager.update_job = MagicMock(return_value=None)
+    
+    return manager
+
+
+# ============================================================================
+# File System Fixtures
+# ============================================================================
+
+@pytest.fixture
+def temp_dir(test_config):
+    """Create a temporary directory for test files."""
+    temp_path = Path(test_config['temp_dir']) / 'test_run'
+    temp_path.mkdir(parents=True, exist_ok=True)
+    yield temp_path
+    # Cleanup
+    if temp_path.exists():
+        shutil.rmtree(temp_path)
+
+
+@pytest.fixture
+def sample_files(temp_dir, sample_image):
+    """Create sample files in temp directory."""
+    files = {}
+    
+    # Save sample image
+    image_path = temp_dir / 'sample.jpg'
+    cv2.imwrite(str(image_path), sample_image)
+    files['image'] = image_path
+    
+    # Create multiple images for batch testing
+    for i in range(3):
+        path = temp_dir / f'image_{i}.jpg'
+        cv2.imwrite(str(path), sample_image)
+        files[f'image_{i}'] = path
+    
+    return files
+
+
+# ============================================================================
+# Model Registry Fixtures
+# ============================================================================
+
+@pytest.fixture
+def mock_registry():
+    """Create a mock model registry."""
+    from models.registry import ModelRegistry, ModelInfo, ModelTask, ModelFramework
+    
+    registry = ModelRegistry(models_dir=Path(tempfile.mkdtemp()))
+    
+    # Add test model
+    test_model = ModelInfo(
+        model_id='test-model',
+        name='Test Model',
+        version='1.0',
+        task=ModelTask.SEGMENTATION,
+        framework=ModelFramework.PYTORCH,
+        url='http://example.com/model.pth',
+        filename='test_model.pth',
+        file_size=1000000
+    )
+    
+    registry.register_model(test_model)
+    
+    return registry
+
+
+# ============================================================================
+# WebSocket Fixtures
+# ============================================================================
+
+@pytest.fixture
+def mock_websocket():
+    """Create a mock WebSocket connection."""
+    ws = MagicMock()
+    ws.accept = MagicMock(return_value=None)
+    ws.send_json = MagicMock(return_value=None)
+    ws.receive_text = MagicMock(return_value='{"type": "ping", "data": {}}')
+    
+    return ws
+
+
+# ============================================================================
+# Utility Fixtures
+# ============================================================================
+
+@pytest.fixture
+def mock_progress_callback():
+    """Create a mock progress callback."""
+    callback = MagicMock()
+    return callback
+
+
+@pytest.fixture
+def device():
+    """Get device for testing."""
+    return 'cuda' if torch.cuda.is_available() else 'cpu'
+
+
+@pytest.fixture
+def performance_timer():
+    """Timer for performance testing."""
+    import time
+    
+    class Timer:
+        def __init__(self):
+            self.start_time = None
+            self.elapsed = 0
+        
+        def __enter__(self):
+            self.start_time = time.time()
+            return self
+        
+        def __exit__(self, *args):
+            self.elapsed = time.time() - self.start_time
+    
+    return Timer
+
+
+# ============================================================================
+# Markers
+# ============================================================================
+
+def pytest_configure(config):
+    """Register custom markers."""
+    config.addinivalue_line(
+        "markers", "slow: marks tests as slow (deselect with '-m \"not slow\"')"
+    )
+    config.addinivalue_line(
+        "markers", "gpu: marks tests that require GPU"
+    )
+    config.addinivalue_line(
+        "markers", "integration: marks integration tests"
+    )
+    config.addinivalue_line(
+        "markers", "unit: marks unit tests"
+    )