A real-time computer vision application that detects, tracks, and analyzes specific colors from a video feed using OpenCV. This project simplifies color measurement and object tracking for educational and hobbyist purposes.
# Install dependencies
pip install -r requirements.txt
# Run the application
python code/main.py- HSV Conversion: Accurate color segmentation by converting frames to HSV space.
- Hue Thresholding: Calculates dynamic limits to isolate specific colors reliably.
- Contour Filtering: Area-based noise suppression to ignore small, irrelevant objects.
- Bounding Boxes: Real-time visual tracking with green borders around detected targets.
- Color Identification: Automatic naming of detected colors (Red, Blue, Yellow, etc.).
- Smooth Feed: Low-latency video processing for continuous real-time execution.
- RGB Sampling: Left-click any pixel to view its precise RGB value in real-time.
- Dynamic Highlighting: Visual indicators at clicked positions for precise sampling.
- Parametric Input: Terminal-based BGR specification before the main loop starts.
- Launch the script via terminal
- Enter the target color's BGR values when prompted (e.g.,
0 0 255for Red) - Point your camera at objects matching the specified color
- View the live tracking and color name labels
- Left-click anywhere on the frame to sample live RGB data
Note: Performance may vary based on environmental lighting conditions and camera sensor quality.