python face_recognition 简单实时识别

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#!/usr/bin/env python
# -*- coding: utf-8 -*-
# @Site    : 
# @File    : 摄像头实时识别.py



import face_recognition
import cv2



#获取网络摄像机#0的参考（默认值）
video_capture = cv2.VideoCapture(0)

# 本地图像
qiqi_image = face_recognition.load_image_file("/Users/xxx/Downloads/test2.png")
qiqi_face_encoding = face_recognition.face_encodings(qiqi_image,num_jitters=3)[0]


zhiyuan_image = face_recognition.load_image_file("/Users/xxx/Downloads/test1.png")
zhiyuan_face_encoding = face_recognition.face_encodings(zhiyuan_image,num_jitters=3)[0]

juwei_image = face_recognition.load_image_file("/Users/xxx/Downloads/test3.jpg")
juwei_face_encoding = face_recognition.face_encodings(juwei_image,num_jitters=3)[0]

known_face_encodings = [
    zhiyuan_face_encoding,
    juwei_face_encoding,
    qiqi_face_encoding
]
known_face_names = [
    "zhiyuan",
    "juwei",
    "yongqi"
]


#初始化一些变量
face_locations = []
face_encodings = []
face_names = []
process_this_frame = True

while True:
    # 抓取一帧视频
    ret, frame = video_capture.read()

    # 将视频帧调整为1/4大小，以加快脸部识别处理
    small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25)

    # 将图像从BGR颜色（OpenCV使用的）转换为RGB颜色（face_recognition使用）
    rgb_small_frame = small_frame[:, :, ::-1]

    # 只处理每隔一帧视频节省时间
    if process_this_frame:
        # 查找当前视频帧中的所有面部和脸部编码
        face_locations = face_recognition.face_locations(rgb_small_frame)
        face_encodings = face_recognition.face_encodings(rgb_small_frame, face_locations,num_jitters=1)

        face_names = []
        for face_encoding in face_encodings:
            # 查看脸部是否与已知脸部相匹配（S）
            matches = face_recognition.compare_faces(known_face_encodings, face_encoding, tolerance=0.35)
            name = "Unknown"

            # 如果在known_face_encodings中找到了匹配项，只需使用第一个。
#             print(len(matches))
            if True in matches:
#                 print(len(matches))
                first_match_index = matches.index(True)
#                 print(first_match_index)
                name = known_face_names[first_match_index]

            face_names.append(name)

    process_this_frame = not process_this_frame


    # 显示结果
    for (top, right, bottom, left), name in zip(face_locations, face_names):
        # 自从我们检测到的框架缩放到1/4尺寸后，缩放后面的位置
        top *= 4
        right *= 4
        bottom *= 4
        left *= 4

        # 在脸上画一个盒子
        cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2)

        # 在脸部下面画一个名字
        cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), cv2.FILLED)
        font = cv2.FONT_HERSHEY_DUPLEX
        cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.0, (255, 255, 255), 1)

    # 显示结果图像
    cv2.imshow('Video', frame)

    # 点击键盘上的'q'退出！
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# 释放网络摄像机的资源
video_capture.release()
cv2.destroyAllWindows()
python face_recognition 简单实时识别

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