face detection with CNN

get_faces.py

###################################################
# conda create -n opencnn python=3.7 tensorflow   #
# conda activate opencnn                          #
# pip install opencv-python mtcnn                 #
###################################################

import logging
import os

import cv2
from mtcnn.mtcnn import MTCNN

# Disable warnings
logging.disable(logging.WARNING)
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
# os.environ['OMP_NUM_THREADS'] = '4'
# os.environ['KMP_AFFINITY'] = 'none'


def draw_roi(image,results):
    # image to which we draw the roi
    # results is an array with all the bounding boxes detected. 
    for result in results:
        bounding_box = result['box']
        keypoints = result['keypoints']

        cv2.rectangle(image,
                    (bounding_box[0], bounding_box[1]),
                    (bounding_box[0]+bounding_box[2], bounding_box[1] + bounding_box[3]),
                    (0,155,255),
                    2)

        cv2.circle(image,(keypoints['left_eye']), 2, (0,155,255), 2)
        cv2.circle(image,(keypoints['right_eye']), 2, (0,155,255), 2)
        cv2.circle(image,(keypoints['nose']), 2, (0,155,255), 2)
        cv2.circle(image,(keypoints['mouth_left']), 2, (0,155,255), 2)
        cv2.circle(image,(keypoints['mouth_right']), 2, (0,155,255), 2)

class Face:

    def __init__(self, model:MTCNN, 
                camera_index:int=0):
        
        self.capture = cv2.VideoCapture(camera_index)
        self.detector = model()
    

    def __enter__(self):
        return self

    def __exit__(self, exc_type, exc_value, traceback):
         self.capture.release()
         cv2.destroyAllWindows()
    

    def detect(self):
        '''Find Face, Eyes, Nose and Mouth
        '''
        while True:
            has_frame, frame = self.capture.read()
            assert has_frame, 'No frame'

            frame_RGB = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
            results = self.detector.detect_faces(frame_RGB)
            draw_roi(frame, results)
            cv2.imshow('Video', frame)

            # Break while loop
            if cv2.waitKey(20) & 0xFF == ord('q'):
                break

        # Release capture
        self.capture.release()
        cv2.destroyAllWindows()

if __name__ == '__main__':
    # Run face detection capturing Eyes, Nose and Mouth
    detect = Face(model=MTCNN)
    detect.detect()