TensorFlow实现人脸识别(5)-------利用训练好的模型实时进行人脸检测

#-*- coding:UTF-8 -*-
import tensorflow as tf
import numpy as np
import sys
import gc
from face_train import Model
import cv2

def IdentifyFace(window_name):
cv2.namedWindow(window_name)

model = Model()
model.load_model(file_path = 'face.model.h5')

cap = cv2.VideoCapture("test.wmv")  #获取视频数据
classifier=cv2.CascadeClassifier('/usr/local/share/OpenCV/haarcascades/haarcascade_frontalface_alt2.xml')
color=(0,255,0)
num = 0
while cap.isOpened():
ok,frame = cap.read()  #ok表示返回的状态  frame存储着图像数据矩阵 mat类型的
if not ok:
break

#图像灰度化
grey=cv2.cvtColor(frame,cv2.COLOR_BGR2GRAY)
#加载分类器 opencv自带
faceRects = classifier.detectMultiScale(grey, scaleFactor=1.2, minNeighbors=3, minSize=(32, 32))

if len(faceRects) > 0 :
for faceRect in faceRects:
x,y,w,h = faceRect

image = frame[y-10:y+h+10,x-10:x+w+10]
faceID = model.face_predict(image)
#如果是“我”
if faceID == 0:
cv2.rectangle(frame, (x - 10, y - 10
4000
), (x + w + 10, y + h + 10), color, thickness = 2)

#文字提示是谁
cv2.putText(frame,'ME',
(x + 30, y + 30),                      #坐标
cv2.FONT_HERSHEY_SIMPLEX,              #字体
1,                                     #字号
(255,0,255),                           #颜色
2)                                     #字的线宽
else:
cv2.rectangle(frame, (x - 10, y - 10), (x + w + 10, y + h + 10), color, thickness = 2)

#文字提示是谁
cv2.putText(frame,'others',
(x + 30, y + 30),                      #坐标
cv2.FONT_HERSHEY_SIMPLEX,              #字体
1,                                     #字号
(255,0,255),                           #颜色
2)

cv2.imshow(window_name,frame) #将捕获的数据显示出来
c = cv2.waitKey(30)
if c & 0xff == ord('q'): #按q退出
break

cap.release()
cv2.destroyWindow(window_name)

#主程序调用方法运行
if __name__ == '__main__':
IdentifyFace('IdentifyFace')