最近需要做一个图像识别的GUI应用,权衡了Opencv+ 1)QT,2)Python GUI,3).NET后选择了.NET。。。
本文给出C#+Opencv和Python+Opencv的相应参考,节省大家时间。
(一)C#.NET + Opencv
1)下载并安装Emgu库(for opencv on .NET env)
Download @ http://sourceforge.net/projects/emgucv/
2)How to use opencv on C#?
VS上配置Emgu(库)
3)测试on C#.NET
(二)Python + Opencv
按照官网的Instruction一步步来,可以从source自己编译,也可以直接用二进制文件。
这里注意我遇到的一个错误,undefined cv2.SIFT():
AttributeError: 'module' object has no attribute 'SIFT'
但我自己编译成功后还是没解决问题。。。于是试着吧opencv 2.3.1换成opencv 2.4.6.0,再按官网的Instruction预编译二进制文件方法把cv2.pyd拷到python下,成功了。。。。
PS: 喜欢在mac上折腾的看看这个帖子吧。。。Installing OpenCV 2.4.2 on Mac OSX Mountain Lion with Python support
最后贴个python+opencv+numpy测试代码:
import cv2 import numpy as np #import pdb #pdb.set_trace()#turn on the pdb prompt #test cv2 and numpy package print cv2.__version__ a = np.arange(10) print(a) #read image img = cv2.imread('D:\privacy\picture\little girl.jpg',cv2.IMREAD_COLOR) gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) cv2.imshow('tt',img); #basic accessing b,g,r = img[0,0];#blue,green,red print b,g,r rows,columns,channels = img.shape print rows,columns,channels print img.size #channels split and merge b,g,r = cv2.split(img) img = cv2.merge([b,g,r]) #SIFT detector = cv2.SIFT() keypoints = detector.detect(gray,None) img = cv2.drawKeypoints(gray,keypoints) #img = cv2.drawKeypoints(gray,keypoints,flags = cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS) cv2.imshow('test',img); cv2.waitKey(0) cv2.destroyAllWindows()
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