/Face_Detection_using_RPi

Face Detection using Open CV with Raspberry Pi

Primary LanguagePython

Face Detection & Recognition using OpenCV with Raspberry Pi

This Repository will explain my 4th task in Robotics and AI department at SMART METHODS summer training.

Task Requirements:

  • Use OpenCV for making a real time face detection and recognition in Raspberry Pi.

Detailed Steps:

  1. Configure the Raspbeery Pi to control the controller remotely (Click Here).

  2. Create your Python virtual environment and install NumPy then Compile OpenCV 4 from source (Click Here for full installation details).

  3. Camera Test:

    • Test the camera using this Code in full details with commenet.

    • Run the virtual environment workon cv

    • Open the path file if you have saved your .py file in a directory using cd command, in my case I will run the folowing command cd Face_Recognition/Face_Detection

    • Run you camera test file by using python folowed by your file name, in my case python Face_Detection.py

    • I will use a usb camera as shown in the figure:

    • Tested result will show an image in a Gray and RGB color:

  4. Face Detection:

    • To recognise a face first we should captutre the face (detecte it).The most common way used to detect a face or any objects, is using the "Haar Cascade classifier" (It is a machine learning based approach where a cascade function is trained from a lot of positive and negative images, It is then used to detect objects in other images).To detect faces the algorithm needs a lot of positive images (images of faces) and negative images (images without faces) to train the classifier. Then we need to extract features from it. OpenCV comes with a trainer as well as a detector. If we want to train our classifier for any object like car, planes etc. we can use OpenCV to create one using "Cascade Classifier Training".
    • The good news is that OpenCV comes with a trainer as well as a detector and we will used it to detect faces. To see my code with comments, Click here.
    • As shown in the figure below my face was detected successfully:

  5. Face and Eye Detection:

    • Now, lets detect the eyes of the face. To do that we should include the classifier for the eyes as we did in the face detection.
    • Note that, on those cases, we will include the classifier function and rectangle draw inside the face loop, because there would be no sense to detect an eye outside of a face.
    • To see my code with full comments, Click here.
    • Tested Result:

  6. Face Recognition