Caffe模型MobileNet与opencv的结合

所需原料:opencv-python + yourmobilenet.caffemodel + yourdeploy.prototxt

利用opencv3.3.1之后推出的dnn模块,支持很多模型的导入.这次我选择Caffe的Mobilenet模型.

import numpy as np
import time
import cv2, os
print('******model*********')
net = cv2.dnn.readNetFromCaffe(r'./mobilenet_deploy.prototxt',r'./model/mbilenet_iter_4055.caffemodel')
labels = [````]
cap = cv2.VideoCapture(0)
while 1:_, frame1 = cap.read()print('**********one frame***********')frame = cv2.resize(frame1, (224,224)) # 你的网络输入的尺寸# grab the frame dimensions and convert it to a blobblob = cv2.dnn.blobFromImage(frame, 0.00390625, (224, 224), (112.24, 115.46, 117.84),swapRB=False)net.setInput(blob)detections = net.forward()label = labels[np.argmax(detections)]# label = str(np.argmax(detections))cv2.putText(frame1, label,(111,111),cv2.FONT_HERSHEY_DUPLEX, 2, [0, 0, 111], 2)# show the output framecv2.imshow("Frame", frame1)cv2.waitKey(1)

    blob = cv2.dnn.blobFromImage(frame, 0.00390625, (224, 224), (112.24, 115.46, 117.84),swapRB=False)

第二个参数是scale,第三个是送入网络的尺寸,然后是每个通道的均值.