GitHub - farhanc4kra/openCv-3.4.3-FaceDetection-: import cv2 face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') # We load the cascade for the face. eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') # We load the cascade for the eyes. def detect(gray, frame): # We create a function that takes as input the image in black and white (gray) and the original image (frame), and that will return the same image with the detector rectangles. faces = face_cascade.detectMultiScale(gray, 1.3, 5) # We apply the detectMultiScale method from the face cascade to locate one or several faces in the image. for (x, y, w, h) in faces: # For each detected face: cv2.rectangle(frame, (x, y), (x+w, y+h), (255, 0, 0), 2) # We paint a rectangle around the face. roi_gray = gray[y:y+h, x:x+w] # We get the region of interest in the black and white image. roi_color = frame[y:y+h, x:x+w] # We get the region of interest in the colored image. eyes = eye_cascade.detectMultiScale(roi_gray, 1.1, 3) # We apply the detectMultiScale method to locate one or several eyes in the image. for (ex, ey, ew, eh) in eyes: # For each detected eye: cv2.rectangle(roi_color,(ex, ey),(ex+ew, ey+eh), (0, 255, 0), 2) # We paint a rectangle around the eyes, but inside the referential of the face. return frame # We return the image with the detector rectangles. video_capture = cv2.VideoCapture(0) # We turn the webcam on. while True: # We repeat infinitely (until break): _, frame = video_capture.read() # We get the last frame. gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY) # We do some colour transformations. canvas = detect(gray, frame) # We get the output of our detect function. cv2.imshow('Video', canvas) # We display the outputs. stop, cap, steps, prev_frame_none, frames_counter = repeat_image_retrieval( cap, file_path, take_all_frames, steps, frame, prev_frame_none, frames_counter) if cv2.waitKey(1) & 0xFF == ord('q'): # If we type on the keyboard: break # We stop the loop. video_capture.release() # We turn the webcam off. cv2.destroyAllWindows() # We destroy all the windows inside which the images were displayed.

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import cv2 face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') # We load the cascade for the face. eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') # We load the cascade for the eyes. def detect(gray, frame): # We create a function that takes as input the image in black and white (gray) and the original image (f…