Face Detection is a easy task for computer now a days.In fact some ML model achieved state of art in computer vision.

We are using pretrained CNN model for face detection and extraction.

The project has two essential elements:

1. Box around faces: Show red boxes around all the faces recognised in the image. The Python file is faceDetectionCNN.py

2. Extracted faces: Extract faces from all images in a folder and save each face into a destination folder to create a handy dataset. The Python file is faceExtraction.py

def highlight_faces(image_path, faces):
  # display image
    image = plt.imread(image_path)
    plt.imshow(image)

    ax = plt.gca()

    # for each face, draw a rectangle based on coordinates
    for face in faces:
        x, y, width, height = face['box']
        face_border = Rectangle((x, y), width, height,
                          fill=False, color='red')
        ax.add_patch(face_border)
        plt.savefig('./media/face_detected.jpg')
    plt.show()

pip install keras
pip install mtcnn
pip install keras_vggface

def highlight_faces(image_path, faces):
  # display image
    image = plt.imread(image_path)
    plt.imshow(image)

    ax = plt.gca()

    # for each face, draw a rectangle based on coordinates
    for face in faces:
        x, y, width, height = face['box']
        face_border = Rectangle((x, y), width, height,
                          fill=False, color='red')
        ax.add_patch(face_border)
    plt.show()