Python+OpenCV: cv2.imwrite

This following code should extract face in images and save faces on disk

def detect(image):
    image_faces = []
    bitmap = cv.fromarray(image)
    faces = cv.HaarDetectObjects(bitmap, cascade, cv.CreateMemStorage(0))
    if faces:
        for (x,y,w,h),n in faces:
            image_faces.append(image[y:(y+h), x:(x+w)])
            #cv2.rectangle(image,(x,y),(x+w,y+h),(255,255,255),3)
    return image_faces

if __name__ == "__main__":
    cam = cv2.VideoCapture(0)
    while 1:
        _,frame =cam.read()
        image_faces = []
        image_faces = detect(frame)
        for i, face in enumerate(image_faces):
            cv2.imwrite("face-" + str(i) + ".jpg", face)

        #cv2.imshow("features", frame)
        if cv2.waitKey(1) == 0x1b: # ESC
            print 'ESC pressed. Exiting ...'
            break

Alternatively, with MTCNN and OpenCV(other dependencies including TensorFlow also required), you can:

1 Perform face detection(Input an image, output all boxes of detected faces):

from mtcnn.mtcnn import MTCNN
import cv2

face_detector = MTCNN()

img = cv2.imread("Anthony_Hopkins_0001.jpg")
detect_boxes = face_detector.detect_faces(img)
print(detect_boxes)

[{'box': [73, 69, 98, 123], 'confidence': 0.9996458292007446, 'keypoints': {'left_eye': (102, 116), 'right_eye': (150, 114), 'nose': (129, 142), 'mouth_left': (112, 168), 'mouth_right': (146, 167)}}]

2 save all detected faces to separate files:

for i in range(len(detect_boxes)):
    box = detect_boxes[i]["box"]
    face_img = img[box[1]:(box[1] + box[3]), box[0]:(box[0] + box[2])]
    cv2.imwrite("face-{:03d}.jpg".format(i+1), face_img)

3 or Draw rectangles of all detected faces:

for box in detect_boxes:
    box = box["box"]
    pt1 = (box[0], box[1]) # top left
    pt2 = (box[0] + box[2], box[1] + box[3]) # bottom right
    cv2.rectangle(img, pt1, pt2, (0,255,0), 2)
cv2.imwrite("detected-boxes.jpg", img)