Color Detection with OpenCV

Overview

This project is a simple real-time color detection system built using Python, OpenCV, NumPy, and Pillow. It captures video from a webcam, detects a specific color (green by default), and draws a bounding box around the detected object.

This project is useful for:

• Learning basic computer vision concepts
• Understanding HSV color space
• Practicing real-time webcam processing
• Building simple object tracking systems

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Features

• Real-time webcam video capture
• HSV-based color detection
• Automatic mask creation
• Bounding box around detected object
• Easy to customize for other colors

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Technologies Used

• Python
• OpenCV (cv2)
• NumPy
• Pillow (PIL)

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Project Structure

color-detection/
│
├── main.py          # Main program for webcam color detection
├── util.py          # HSV color range helper function
├── README.md        # Project documentation

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Installation

1. Clone the repository

git clone https://github.com/your-username/your-repo-name.git
cd your-repo-name

2. Install dependencies

pip install opencv-python numpy pillow

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How to Run

Run the following command:

python main.py

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How It Works

1. The webcam captures live video frames.
2. Each frame is converted from BGR to HSV color space.
3. The program detects the selected color range.
4. A mask is created to isolate the detected color.
5. A bounding box is drawn around the object.

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Customization

To detect another color, simply change this line in main.py:

green = [0, 255, 0]

Example:

• Red → [0, 0, 255]
• Blue → [255, 0, 0]

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Controls

• Press Q to quit the application.

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Future Improvements

• Support multiple colors
• Add object centroid tracking
• Improve detection accuracy with contour filtering
• Add GUI for color selection

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Author

Created as a beginner computer vision project using OpenCV.