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Testing Guide for PoseDetector

This guide explains how to test the pose_detector.py file using different approaches.

Prerequisites

Make sure you have all the required dependencies installed:

pip install -r requirements.txt
pip install -r requirements-test.txt

Testing Approaches

1. Quick Test (Recommended for beginners)

Run the simple test script directly:

python test_pose_detector_simple.py

This will run basic functionality tests and error handling tests without requiring pytest.

2. Comprehensive Unit Tests with pytest

Run the full test suite:

# Run all tests
pytest tests/

# Run with verbose output
pytest tests/ -v

# Run with coverage report
pytest tests/ --cov=src --cov-report=html

# Run specific test file
pytest tests/test_pose_detector.py

# Run specific test method
pytest tests/test_pose_detector.py::TestPoseDetector::test_initialization

3. Interactive Testing in Python REPL

# Start Python REPL
python

# Import and test
from src.pose_detector import PoseDetector
import numpy as np

# Create detector
detector = PoseDetector()

# Test with sample frame
frame = np.random.randint(0, 255, (480, 640, 3), dtype=np.uint8)
result = detector.detect_pose(frame)

# Check results
print(f"Pose detected: {detector.is_pose_detected()}")
print(f"Frame shape: {result.shape}")

# Clean up
detector.release()

What the Tests Cover

Basic Functionality Tests

  • ✅ Initialization of MediaPipe pose detection
  • ✅ Frame processing and validation
  • ✅ Pose detection workflow
  • ✅ Landmark coordinate extraction
  • ✅ Running keypoints retrieval
  • ✅ Pose detection status checking

Error Handling Tests

  • ✅ None frame handling
  • ✅ Empty frame handling
  • ✅ Invalid frame dimensions (2D, wrong channels)
  • ✅ Invalid landmark IDs
  • ✅ Graceful degradation when no pose detected

Integration Tests

  • ✅ Complete workflow from detection to keypoint extraction
  • ✅ Resource cleanup and memory management
  • ✅ MediaPipe integration

Test Structure

tests/
├── test_pose_detector.py          # Comprehensive pytest tests
├── requirements-test.txt           # Testing dependencies
└── test_pose_detector_simple.py   # Simple test script

TESTING.md                         # This guide

Understanding Test Results

Green Checkmarks (✓)

  • All assertions passed
  • Functionality working as expected

Red X (❌)

  • Test failed
  • Check error messages for debugging

Common Issues and Solutions

  1. Import Errors

    • Make sure you're in the project root directory
    • Check that src/ is in your Python path

  2. MediaPipe Errors

    • Ensure MediaPipe is properly installed
    • Check version compatibility

  3. OpenCV Errors

    • Verify OpenCV installation
    • Check numpy array compatibility

Performance Testing

For performance testing, you can create larger frames or process multiple frames:

# Performance test with larger frames
large_frame = np.random.randint(0, 255, (1080, 1920, 3), dtype=np.uint8)
detector = PoseDetector()

import time
start_time = time.time()
for _ in range(100):
    result = detector.detect_pose(large_frame)
end_time = time.time()

print(f"Processed 100 frames in {end_time - start_time:.2f} seconds")
detector.release()

Continuous Integration

To integrate testing into your development workflow:

  1. Pre-commit hooks: Run tests before each commit
  2. GitHub Actions: Automate testing on push/PR
  3. Local development: Run tests after each significant change

Debugging Failed Tests

  1. Read error messages carefully - they often point to the exact issue
  2. Check dependencies - ensure all packages are installed
  3. Verify file paths - make sure you're in the correct directory
  4. Use verbose output - pytest -v provides more details
  5. Run individual tests - isolate the failing test case

Contributing

When adding new features to PoseDetector:

  1. Write tests first (TDD approach)
  2. Cover edge cases - test invalid inputs
  3. Test error conditions - ensure graceful failure
  4. Update this guide - document new testing approaches

Happy testing! 🧪✨