0x01. 滤镜
喜欢自拍的人肯定都知道滤镜了，下面代码尝试使用一些简单的滤镜，包括图片的平滑处理、灰度化、二值化等：
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import cv2.cv as cv image=cv.LoadImage('img/lena.jpg', cv.CV_LOAD_IMAGE_COLOR) #Load the image cv.ShowImage("Original", image) grey = cv.CreateImage((image.width ,image.height),8,1) #8depth, 1 channel so grayscale cv.CvtColor(image, grey, cv.CV_RGBA2GRAY) #Convert to gray so act as a filter cv.ShowImage('Greyed', grey) # 平滑变换 smoothed = cv.CloneImage(image) cv.Smooth(image,smoothed,cv.CV_MEDIAN) #Apply a smooth alogrithm with the specified algorithm cv.MEDIAN cv.ShowImage("Smoothed", smoothed) # 均衡处理 cv.EqualizeHist(grey, grey) #Work only on grayscaled pictures cv.ShowImage('Equalized', grey) # 二值化处理 threshold1 = cv.CloneImage(grey) cv.Threshold(threshold1,threshold1, 100, 255, cv.CV_THRESH_BINARY) cv.ShowImage("Threshold", threshold1) threshold2 = cv.CloneImage(grey) cv.Threshold(threshold2,threshold2, 100, 255, cv.CV_THRESH_OTSU) cv.ShowImage("Threshold 2", threshold2) element_shape = cv.CV_SHAPE_RECT pos=3 element = cv.CreateStructuringElementEx(pos*2+1, pos*2+1, pos, pos, element_shape) cv.Dilate(grey,grey,element,2) #Replace a pixel value with the maximum value of neighboors #There is others like Erode which replace take the lowest value of the neighborhood #Note: The Structuring element is optionnal cv.ShowImage("Dilated", grey) cv.WaitKey(0) |
0x02. HighGUI
OpenCV 内建了一套简单的 GUI 工具，方便我们在处理界面上编写一些控件，动态的改变输出：
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import cv2.cv as cv im = cv.LoadImage("img/lena.jpg", cv.CV_LOAD_IMAGE_GRAYSCALE) thresholded = cv.CreateImage(cv.GetSize(im), 8, 1) def onChange(val): cv.Threshold(im, thresholded, val, 255, cv.CV_THRESH_BINARY) cv.ShowImage("Image", thresholded) # 创建一个滑动条控件 onChange(100) #Call here otherwise at startup. Show nothing until we move the trackbar cv.CreateTrackbar("Thresh", "Image", 100, 255, onChange) #Threshold value arbitrarily set to 100 cv.WaitKey(0) |
0x03. 选区操作
有事希望对图像中某一块区域进行变换等操作，就可以使用如下方式：
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import cv2.cv as cv im = cv.LoadImage("img/lena.jpg",3) # 选择一块区域 cv.SetImageROI(im, (50,50,150,150)) #Give the rectangle coordinate of the selected area # 变换操作 cv.Zero(im) #cv.Set(im, cv.RGB(100, 100, 100)) put the image to a given value # 解除选区 cv.ResetImageROI(im) # Reset the ROI cv.ShowImage("Image",im) cv.WaitKey(0) |
0x04. 运算
对于多张图片，我们可以进行一些运算操作(包括算数运算和逻辑运算)，下面的代码将演示一些基本的运算操作：
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import cv2.cv as cv#or simply import cv im = cv.LoadImage("img/lena.jpg") im2 = cv.LoadImage("img/fruits-larger.jpg") cv.ShowImage("Image1", im) cv.ShowImage("Image2", im2) res = cv.CreateImage(cv.GetSize(im2), 8, 3) # 加 cv.Add(im, im2, res) #Add every pixels together (black is 0 so low change and white overload anyway) cv.ShowImage("Add", res) # 减 cv.AbsDiff(im, im2, res) # Like minus for each pixel im(i) - im2(i) cv.ShowImage("AbsDiff", res) # 乘 cv.Mul(im, im2, res) #Multiplie each pixels (almost white) cv.ShowImage("Mult", res) # 除 cv.Div(im, im2, res) #Values will be low so the image will likely to be almost black cv.ShowImage("Div", res) # 与 cv.And(im, im2, res) #Bit and for every pixels cv.ShowImage("And", res) # 或 cv.Or(im, im2, res) # Bit or for every pixels cv.ShowImage("Or", res) # 非 cv.Not(im, res) # Bit not of an image cv.ShowImage("Not", res) # 异或 cv.Xor(im, im2, res) #Bit Xor cv.ShowImage("Xor", res) # 乘方 cv.Pow(im, res, 2) #Pow the each pixel with the given value cv.ShowImage("Pow", res) # 最大值 cv.Max(im, im2, res) #Maximum between two pixels #Same form Min MinS cv.ShowImage("Max",res) cv.WaitKey(0) |
