This project demonstrates a real-time face blurring application using OpenCV. It captures video from your webcam, detects faces in real-time, and applies a median blur effect to the detected faces.
- Python 3.x
- OpenCV
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Install Requirements:
pip install -r requirements.txt
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Run the script:
python main.py
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The webcam will open, and the application will begin detecting faces. Detected faces will be blurred in real-time.
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Press
qto exit the application.
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Importing Libraries: The script uses OpenCV for video capture and face detection.
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Loading the Cascade Classifier: The
haarcascade_frontalface_default.xmlfile is loaded to detect faces in the video frames. -
Capturing Video: A video stream from the default camera (index 0) is initiated.
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Face Detection Loop:
- Each frame is read from the video stream.
- The frame is converted to grayscale for face detection.
detectMultiScaleis used to detect faces in the grayscale image.- Detected faces are blurred using a median filter applied to the corresponding regions of the original frame.
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Displaying Video: The processed video is displayed in a window titled "gotch !!!".
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Exiting the Application: Pressing the 'q' key will terminate the video stream and close all windows.
- This project uses the OpenCV library, which is a powerful tool for image processing and computer vision tasks.
- Haar Cascades for face detection are provided by OpenCV, which allows for efficient face detection in images and video.
Vivek Prakash