Color Detection using Pandas and OpenCV (cv2)

This simple Python program allows you to detect the color of an image by extracting data from a dataset using pandas and OpenCV (cv2) libraries.

Installation

1. Clone the repository:

   git clone https://github.com/nomaanahmedd/codeclause_color-detection.git

2. Navigate to the project directory:

   cd color-detection

3. Install the required dependencies using pip:

   pip install pandas opencv-python

Usage

1. Place your image in the project directory.

2. Update the image path in the code:

   img_path = 'your-image.jpg'

3. Make sure you have a dataset file (CSV format) with color information (name, hex code, RGB values). Update the dataset file name and column names in the code:

   data = pd.read_csv('color_dataset.csv', names=['Name', 'Hex', 'R', 'G', 'B'], header=None)

4. Run the program:

   python color_detection.py

5. The program will display the image with an interactive window—Double-click on any pixel to detect its color. The color name, RGB values, and a colored rectangle will be displayed on the image.

6. Press the Esc key to exit the program.

Dataset

Dataset: https://www.kaggle.com/datasets/nomaanahmeddd/color-codes

The dataset file is in CSV format and contains the following columns containing more than 1000 color codes and their names:

• Name: Color name
• Hex: Hex code for the color
• R: Red component value
• G: Green component value
• B: Blue component value

while creating your own dataset make sure the dataset file is formatted correctly and contains valid color information.

Contributing

Contributions are welcome! If you have any ideas, suggestions, or bug reports, please open an issue or submit a pull request.

License

This project is licensed under the MIT License.