Video Processing Project with OpenCV and PIL 🎥⚽

This project demonstrates the detection of a yellow ball in a video using OpenCV and PIL. The code applies color-based masking and identifies the bounding box of the detected object, then draws the bounding box around the object in the video frames.

Requirements 📦

To run the project, you need to install the required dependencies using pip:

• opencv-python
• Pillow
• numpy

Installation 🔧

1. Clone the repository:

   git clone https://github.com/lamaabdeldayem/Color-Detection.git
   cd Color-Detection

2. Install the dependencies:

   pip install opencv-python Pillow numpy

Usage 🚀

Make sure the video file Bouncing Red Ball (1).mp4 is in the same directory as the script, or update the path in the script accordingly.

Run the script:

python script_name.py

Description of the Code 📝

• The script loads a video (Bouncing Red Ball (1).mp4) using OpenCV.
• It converts each frame from the video to the HSV color space.
• It defines a color range for yellow in the HSV space and creates a mask for pixels within this range.
• The script finds the bounding box of the yellow object in the mask and draws a rectangle around it on the original frame.
• The video is displayed with the bounding box, and you can press q to quit the video.

Example 🎬

The video will show the bounding box drawn around the yellow object as it moves through the frames.

Customizing the Color 🌈

If you want to track a different color, you can modify the yellow variable with a new color in the BGR color space. The get_limits function will automatically adjust the HSV range for the new color.

yellow = [0, 0, 255]  # Change to a new BGR color if needed

Example of get_limits:

If you have your custom function get_limits to return the lower and upper limits for HSV color detection, ensure it’s implemented in the util.py file as shown in the code.

# Example get_limits function
def get_limits(color):
    # Your implementation of HSV limits based on the input color
    pass

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