demo1_2.py

import face_recognition
import cv2

def detect(filename):
    image=face_recognition.load_image_file(filename)
    #加载图片到image
    face_locations_noCNN=face_recognition.face_locations(image)
    #Returns an array of bounding boxes of human faces in a image
    #A list of tuples of found face locations in css (top, right, bottom, left) order
    #因为返回值的顺序是这样子的，因此在后面的for循环里面赋值要注意按这个顺序来

    print("face_location_noCNN:")
    print(face_locations_noCNN)
    face_num2=len(face_locations_noCNN)
    print("I found {} face(s) in this photograph.".format(face_num2))
    # 到这里为止，可以观察两种情况的坐标和人脸数，一般来说，坐标会不一样，但是检测出来的人脸数应该是一样的
    # 也就是说face_num1　＝　face_num２；　face_locations_useCNN　和　face_locations_noCNN　不一样

    org=cv2.imread(filename)
    img=cv2.imread(filename)
    #cv2.imshow(filename,img) #显示原始图片

    for i in range(0,face_num2):
        top=face_locations_noCNN[i][0]
        right=face_locations_noCNN[i][1]
        bottom=face_locations_noCNN[i][2]
        left=face_locations_noCNN[i][3]

        start=(left,top)
        end=(right,bottom)

        color=(0,255,255)
        thickness=2
        cv2.rectangle(org,start,end,color,thickness)
        #cv2.rectangle(img, pt1, pt2, color[, thickness[, lineType[, shift]]]) → None
        #img:图片   pt1&pt2:矩形的左上角和右下角    color:矩形边框的颜色(rgb)   thickness:参数表示矩形边框的厚度

    cv2.imshow("no cnn",org)
    cv2.waitKey(0)
    cv2.destroyAllWindows()

    # # use CNN
# face_locations_useCNN = face_recognition.face_locations(image,model='cnn')
# model – Which face detection model to use. “hog” is less accurate but faster on CPUs.
# “cnn” is a more accurate deep-learning model which is GPU/CUDA accelerated (if available). The default is “hog”.

# print("face_location_useCNN:")
# print(face_locations_useCNN)
# face_num1=len(face_locations_useCNN)
# print(face_num1)       # The number of faces


# for i in range(0,face_num1):
#     top = face_locations_useCNN[i][0]
#     right = face_locations_useCNN[i][1]
#     bottom = face_locations_useCNN[i][2]
#     left = face_locations_useCNN[i][3]
#
#     start = (left, top)
#     end = (right, bottom)
#
#     color = (0,255,255)
#     thickness = 2
#     cv2.rectangle(img, start, end, color, thickness)    # opencv 里面画矩形的函数

# # Show the result
# cv2.imshow("useCNN",img)

if __name__ =='__main__':
    detect('image/101.png')