DriverTrac/docs/FIX_404_ERROR.md

Fix for 404 Error - OpenCV Model Download

Problem

The OpenCV fallback detector was trying to download face detection models from URLs that returned 404 errors:

urllib.error.HTTPError: HTTP Error 404: Not Found

Root Cause

The original implementation attempted to download OpenCV DNN models from GitHub URLs that are no longer available or have moved.

Solution

✅ Replaced with OpenCV's Built-in Haar Cascade Classifier

• No downloads required - Uses OpenCV's built-in face detection
• Always available - Included with OpenCV installation
• More reliable - No dependency on external URLs
• Faster initialization - No network requests

What Changed

Before:

• Tried to download models from GitHub (404 errors)
• Required external dependencies
• Failed if URLs were unavailable

After:

• Uses cv2.data.haarcascades (built-in)
• No network requests
• Works offline
• More reliable

Technical Details

The fix changes the face detector from:

# OLD: Download DNN models
urllib.request.urlretrieve(FACE_DETECTION_MODEL_URL, face_model)
self.face_net = cv2.dnn.readNetFromTensorflow(...)

To:

# NEW: Use built-in Haar Cascade
cascade_path = cv2.data.haarcascades + 'haarcascade_frontalface_default.xml'
self.face_cascade = cv2.CascadeClassifier(cascade_path)

Verification

The fix ensures:

1. ✅ No HTTP requests for model downloads
2. ✅ Uses OpenCV's built-in resources
3. ✅ Works offline
4. ✅ Compatible with all OpenCV installations
5. ✅ Maintains MediaPipe-compatible interface

Performance

• Haar Cascade: Slightly faster than DNN for face detection
• Accuracy: Good for face detection (suitable for POC)
• Memory: Lower memory usage than DNN models

Testing

To verify the fix works:

# Activate virtual environment
source venv/bin/activate

# Test the import
python3 -c "from src.face_pose_detector import get_face_detector; print('OK')"

# Run the application
streamlit run src/poc_demo.py

Expected Behavior

When MediaPipe is not available:

1. Code detects MediaPipe import failure
2. Automatically uses OpenCV Haar Cascade
3. Logs: "✓ OpenCV Face Detector loaded (Haar Cascade)"
4. Application runs normally

Notes

• Haar Cascade is less accurate than MediaPipe for detailed face landmarks
• However, it's sufficient for:
  • Face presence detection
  • Basic face tracking
  • Driver absent detection
  • Simplified PERCLOS calculation

For production, MediaPipe is still recommended for better accuracy.

Summary

✅ Fixed: 404 error eliminated ✅ Improved: No external dependencies ✅ Reliable: Works with standard OpenCV installation ✅ Compatible: Maintains same interface as MediaPipe

The application should now work without any download errors!