使用OpenCV_python中的DNN调用CaffeModel识别图像只需30行代码

来源：互联网发布：新西兰华人知乎编辑：程序博客网时间：2024/06/07 08:34

OpenCV3.3开始正式支持DNN，有C++，Python的Sample，只要下载CaffeModel，识别图像的代码非常简洁。

#coding:utf-8from __future__ import print_functionimport numpy as npimport cv2from cv2 import dnnimport syscm_path='caffemodel/'def get_class_list():    with open(cm_path+'bvlc_googlenet_synset_words_cn1.txt', 'rt') as f:        return [x[x.find(" ") + 1:] for x in f]def dnn_show_result(prob,classes,n):    y = sorted(prob[0],reverse = True) #从大到小排序    z=range(n)  #前n名    for i in range(0, n):        z[i]=np.where(prob[0] == y[i])[0][0]        print(u"第",i+1,u"匹配：", classes[z[i]],end='')            print(u"类所在行：", z[i]+1,"  ",u"可能性:", y[i])if __name__ == "__main__":    if len(sys.argv) < 2:        print ("USAGE: googlenet_z.py images/tiger.jpg")        sys.exit()        fn=sys.argv[1]    blob = dnn.blobFromImage(cv2.imread(fn), 1, (224, 224), (104, 117, 123))    print("Input:", blob.shape, blob.dtype)    net = dnn.readNetFromCaffe(cm_path+'bvlc_googlenet.prototxt', cm_path+'bvlc_googlenet.caffemodel')    net.setInput(blob)    prob = net.forward()    print("Output:", prob.shape, prob.dtype)    classes = get_class_list()    dnn_show_result(prob,classes,3)

OpenCV-Python 下载：https://pypi.python.org/pypi/opencv-python

代码下载：http://download.csdn.net/download/zw010101/10109152 （含bvlc_googlenet.caffemodel，bvlc_googlenet.prototxt，bvlc_googlenet_synset_words.txt）

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