Face Detection Project Overview This project demonstrates face detection using OpenCV and Haar cascades. It utilizes a pre-trained Haar cascade classifier to detect faces in an image and visualizes the detected faces by drawing rectangles around them. The processed image is then displayed using Matplotlib.
Requirements Python 3.x OpenCV NumPy Matplotlib You can install the required packages using pip: pip install opencv-python numpy matplotlib Usage Prepare Your Image: Place the image you want to process in the same directory as your script and name it face.jpg. You can modify the filename in the script if your image has a different name. Run the Script: Execute the script using Python: python face_detection.py View Results: The script will read the image, detect faces, draw rectangles around them, and display the resulting image. Notes Ensure that the haarcascade_frontalface_default.xml file is available in your OpenCV installation's haarcascades directory. Adjust the scaleFactor and minNeighbors parameters in the detectMultiScale function to improve detection results depending on the image. License This project is licensed under the MIT License - see the LICENSE file for details.