import os
import face_recognition as face
from PIL import Image
import datetime
import time

def encodingImg(img):
    image_to_be_matched = face.load_image_file(img)
    # 将加载的图像编码为特征向量
    return face.face_encodings(image_to_be_matched)[0]

def face_distancesrc(img,img2):
    return face.face_distance([encodingImg(img)], encodingImg(img2))[0]

def face_distance(codeImg, codimg3):
    return face.face_distance([codeImg], codimg3)[0]

def gain_face(imgSrc):
    encode = face.load_image_file(imgSrc)
    location = face.face_locations(encode)
    for face_location in location:
        # 打印每张脸的位置信息
        top, right, bottom, left = face_location
        face_image = encode[top:bottom, left:right]
        pil_image = Image.fromarray(face_image)
        file = 'F:\\faceai\\face\\' + str(time_format()) + '.jpg'
        pil_image.save(file)
        print(pil_image)
        # pil_image.show()
    print(location)

def time_format():
    dt_ms = datetime.datetime.now().strftime('%Y%m%d%H%M%S%f')  # 含微秒的日期时间,来源 比特量化
    print(dt_ms)
    return dt_ms

if __name__ == '__main__':
    # time_format()
    gain_face("F:\\faceai\\orgin\\4.jpg")
    # print(face_distancesrc("E:\home\data\picdata\history\\2020-11-05\\1.jpg","E:\home\data\picdata\history\\2020-11-05\\2.jpg"))

最后修改于 2020-11-10 14:03:57
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