This project demonstrates real-time detection of red objects using OpenCV and Python. The script captures video from a webcam, processes each frame to identify red regions, and highlights them with bounding boxes and labels.
- HSV Color Space Conversion: The input frames are converted to HSV color space for easier and more precise color segmentation.
- Color Range Masking: A mask is applied to isolate pixels within the specified red color range.
- Contour Detection: Contours of the detected red regions are extracted to identify distinct objects.
- Bounding Box and Labeling: Red regions exceeding a defined size are highlighted with a green bounding box and labeled with the text "Red."
- Real-Time Processing: Continuously processes video frames from the webcam, allowing real-time detection.
- The webcam captures a video feed.
- Each frame is converted to HSV and masked using a defined range for the red color.
- Contours are detected from the masked image.
- Contours meeting the size criteria are highlighted with a bounding box and labeled.
- Press
qto exit the program.
- OpenCV
- NumPy
- Install the required libraries using
pip install opencv-python numpy. - Run the script, and the program will display the webcam feed with detected red objects highlighted.
- Ensure you have a webcam connected and configured for your system.
It may detect darker or very lighter shades of red; feel free to adjust the red color range to refine the detection.