Color Detection System

A Python-based Color Detection System built using OpenCV, NumPy, and Pandas. The application allows users to identify the name and RGB values of a color by simply double-clicking on any pixel in an image.

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Features

• Detect colors from any image
• Interactive double-click color selection
• Displays the closest matching color name
• Shows RGB values of the selected pixel
• Uses a color database containing hundreds of predefined colors
• Fast and simple image-based color detection
• Command-line support for selecting input image

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Technologies Used

• Python 3
• OpenCV
• NumPy
• Pandas
• CSV

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📂 Project Structure

Color_Detection_System/
│
├── color_detection.py    # Main Python program
├── colors.csv            # Color name and RGB dataset
├── colorpic.jpg          # Sample image
├── README.md             # Project documentation
└── data/                 # Project data files

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How It Works

• The user provides an image path through the command line.
• OpenCV loads and displays the image.
• The user double-clicks on any pixel in the image.
• The program extracts the pixel's RGB values.
• These RGB values are compared with the colors stored in colors.csv.
• The program calculates the closest matching color using RGB distance.
• The detected color name and RGB values are displayed on the image.

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Installation

1. Clone the Repository git clone https://github.com/yourusername/Color_Detection_System.git
2. Navigate to the Project Directory cd Color_Detection_System
3. Install Dependencies pip install opencv-python numpy pandas

How to Run

Run the following command:

python color_detection.py -i colorpic.jpg

You can also provide the path of any other image:

python color_detection.py -i path/to/your/image.jpg

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Screenshots

Double-click anywhere on the image to detect colors

Real-time color detection with RGB values

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How to Use

After running the program:

1. The selected image will open in a window.
2. Double-click on any part of the image.
3. The system will display:

Color name

• Red (R) value
• Green (G) value
• Blue (B) value

4. Press ESC to close the application.

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Color Matching Algorithm

• The system compares the RGB values of the selected pixel with the RGB values stored in the color dataset.

• The distance is calculated using:

- Distance = |R - R₁| + |G - G₁| + |B - B₁|

• The color with the minimum distance is selected as the closest matching color.

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Example

1. If the user selects a pixel with RGB values:

• R = 255
• G = 0
• B = 0

2. The system identifies it as:

• Color: Red
• RGB: (255, 0, 0)

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Applications

This project can be useful for:

• Image processing.
• Computer vision learning.
• Color analysis.
• Graphic design tools.
• Educational computer vision projects.
• Understanding pixel-level image processing.

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Future Improvements

Some possible improvements include:

• Add support for live webcam color detection.
• Add HEX and HSV color values.
• Build a graphical user interface using Tkinter or PyQt.
• Improve color matching using advanced color spaces.
• Add automatic image upload functionality.
• Create a web-based version of the application.

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License

This project is open-source and available under the MIT License.

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request.