Spaces:
Runtime error
Runtime error
copilot-swe-agent[bot]
kr4phy
Refactor code into modular structure with separate lane detection module
e40d5b1 | """ | |
| Basic tests for lane detection functionality | |
| """ | |
| import numpy as np | |
| import cv2 | |
| import sys | |
| import os | |
| # Add parent directory to path | |
| sys.path.insert(0, os.path.dirname(os.path.abspath(__file__))) | |
| from lane_detection import region_of_interest, process_frame, process_video | |
| def test_region_of_interest(): | |
| """Test region of interest masking""" | |
| print("Testing region_of_interest function...") | |
| # Create a test image | |
| img = np.ones((100, 100), dtype=np.uint8) * 255 | |
| # Define vertices | |
| vertices = np.array([[(20, 100), (40, 50), (60, 50), (80, 100)]], dtype=np.int32) | |
| # Apply ROI | |
| result = region_of_interest(img, vertices) | |
| # Check that result has correct shape | |
| assert result.shape == img.shape, f"Expected shape {img.shape}, got {result.shape}" | |
| # Check that areas outside ROI are masked (zero) | |
| assert result[10, 10] == 0, "Pixels outside ROI should be 0" | |
| print("✓ region_of_interest test passed") | |
| def test_process_frame(): | |
| """Test frame processing for lane detection""" | |
| print("Testing process_frame function...") | |
| # Create a test frame with simulated road | |
| height, width = 480, 640 | |
| frame = np.zeros((height, width, 3), dtype=np.uint8) | |
| # Draw white lines to simulate lanes | |
| cv2.line(frame, (200, height), (280, int(height*0.6)), (255, 255, 255), 5) | |
| cv2.line(frame, (440, height), (360, int(height*0.6)), (255, 255, 255), 5) | |
| # Process the frame | |
| result = process_frame(frame) | |
| # Check that result has correct shape | |
| assert result.shape == frame.shape, f"Expected shape {frame.shape}, got {result.shape}" | |
| # Check that result is a valid image (not None and correct dtype) | |
| assert result is not None, "Result should not be None" | |
| assert result.dtype == np.uint8, "Result should be uint8 type" | |
| print("✓ process_frame test passed") | |
| def test_imports(): | |
| """Test that all required modules can be imported""" | |
| print("Testing imports...") | |
| try: | |
| import cv2 | |
| print("✓ opencv-python imported successfully") | |
| except ImportError as e: | |
| print(f"✗ Failed to import cv2: {e}") | |
| return False | |
| try: | |
| import numpy | |
| print("✓ numpy imported successfully") | |
| except ImportError as e: | |
| print(f"✗ Failed to import numpy: {e}") | |
| return False | |
| return True | |
| def test_video_processing(): | |
| """Test complete video processing""" | |
| print("Testing video processing...") | |
| from create_test_video import create_test_video | |
| # Create test video | |
| input_path = "/tmp/test_input.mp4" | |
| output_path = "/tmp/test_output.mp4" | |
| create_test_video(input_path, duration_sec=1, fps=10) | |
| # Process video | |
| success = process_video(input_path, output_path) | |
| assert success, "Video processing should succeed" | |
| assert os.path.exists(output_path), "Output file should exist" | |
| assert os.path.getsize(output_path) > 0, "Output file should not be empty" | |
| print("✓ video processing test passed") | |
| if __name__ == "__main__": | |
| print("Running lane detection tests...\n") | |
| # Test imports | |
| if not test_imports(): | |
| print("\nImport tests failed!") | |
| sys.exit(1) | |
| print() | |
| # Test functions | |
| try: | |
| test_region_of_interest() | |
| test_process_frame() | |
| test_video_processing() | |
| print("\n✅ All tests passed!") | |
| except Exception as e: | |
| print(f"\n❌ Test failed: {e}") | |
| import traceback | |
| traceback.print_exc() | |
| sys.exit(1) | |