Python实现人脸识别
人脸识别,乍一听还是高大上的东西.
今天我们就分享下怎么玩?
不需要一大坨代码,只要你会装……包.
当然,我们的重点不是装包,归根结底,还是怎么玩.
Ok,那么,我们开始
一、需要安装什么?
1.OpenCV 一个图像处理的强大的包.官网 http://opencv.org/,最新的版本3.3.0
不需要最新的版本直接brew install opencv3,我这里装好是3.2.0的
如果需要最新的版本3.3.0的话,请按照这里安装 http://www.pyimagesearch.com/2016/12/19/install-opencv-3-on-macos-with-homebrew-the-easy-way/
2.Python2.7或者Python3.x
3.依赖包NumPY. 可以pip install numpy
4.依赖包face recognition.主角就是他了.pip install face recognition
注意事项参照地址 https://github.com/ageitgey/face_recognition
二、怎么玩
我们首先给定一张被照片
2.从摄像头捕捉的图像里获取检测出头像,跟上面的照片的图片进行对比.
先看下结果:
从截下来的图片来看. 我自己因为没有放图片上去进行识别,所以是unknown的. 手机上的图片被识别到了写上chu(名字) 标签.
代码:
import face_recognition import cv2 import time #获取摄像头
video_capture = cv2.VideoCapture(0)# 加载图片
obama_image = face_recognition.load_image_file("IMG_20170723_213850R.jpg") # 图片先识别一遍人脸,后面用来比较
obama_face_encoding = face_recognition.face_encodings(obama_image)[0]# 初始化变量
face_locations = []
face_encodings = []
face_names = []
process_this_frame = Truewhile True: # 从摄像头获取图像
ret, frame = video_capture.read() # 缩放1/4大小,方便快速处理
small_frame = cv2.resize(frame, (0, 0), fx=0.25, fy=0.25) # 保证只处理一遍
if process_this_frame: #找出所有的人脸
face_locations = face_recognition.face_locations(small_frame)
face_encodings = face_recognition.face_encodings(small_frame, face_locations)
face_names = []
for face_encoding in face_encodings: # 判断是否匹配给定的人脸
match = face_recognition.compare_faces([obama_face_encoding], face_encoding)
name = "Unknown"
if match[0]:
name = "CHU" face_names.append(name)
process_this_frame = not process_this_frame # 把识别到和为识别到的人脸进行标记
for (top, right, bottom, left), name in zip(face_locations, face_names): # 原来是1/4的大小,现在放大4倍
top *= 4 right *= 4 bottom *= 4 left *= 4 # 给脸部画框
cv2.rectangle(frame, (left, top), (right, bottom), (0, 0, 255), 2) # 脸部下面显示标签 cv2.rectangle(frame, (left, bottom - 35), (right, bottom), (0, 0, 255), 2)
font = cv2.FONT_HERSHEY_DUPLEX cv2.putText(frame, name, (left + 6, bottom - 6), font, 1.5, (255, 255, 255), 3) #识别到时候进行抓屏
for name in face_names: if name=="CHU": cv2.imwrite('img-%d.png'%int(time.time()), frame) # 显示加了头像框视频
cv2.imshow('Video', frame) # Hit 'q' on the keyboard to quit!
if cv2.waitKey(1) & 0xFF == ord('q'): break# 释放摄像头句柄
video_capture.release()
cv2.destroyAllWindows()