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makelovemakelove
committed
10-25
1 parent 73622d9 commit 95e7388

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‎.idea/workspace.xml

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‎ch14/14.resize.py

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res=cv2.resize(img,(2*width,2*height),interpolation=cv2.INTER_CUBIC)
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while(1):
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cv2.imshow('res',res)
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cv2.imshow('img',img)
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cv2.imshow('resize',res)
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cv2.imshow('src img',img)
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if cv2.waitKey(1) & 0xFF == 27:
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break
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cv2.destroyAllWindows()

‎ch19-Canny-bian缘检测/19.Canny.py renamed to ‎ch19-Canny-边缘检测/19.Canny.py

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import numpy as np
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from matplotlib import pyplot as plt
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img = cv2.imread('messi5.jpg',0)
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img = cv2.imread('../data/messi5.jpg',0)
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edges = cv2.Canny(img,100,200)
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plt.subplot(121),plt.imshow(img,cmap = 'gray')

‎ch20-Contours/21-findContour.py

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‎ch21-Contours/21-findContour.py

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# -*- coding: utf-8 -*-
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import numpy as np
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import cv2
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# im = cv2.imread('test.jpg')#
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im = cv2.imread('../data/star.png')#contour.jpg
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imgray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
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ret,thresh = cv2.threshold(imgray,50,255,0)
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image, contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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print "contours size: ", len(contours)
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#img = cv2.drawContour(img, contours, -1, (0,255,0), 3)
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img = cv2.drawContours(image, contours, 3, (0,0,255), 3)
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cv2.namedWindow("contour.jpg",0)
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cv2.imshow("contour.jpg",img)
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cv2.waitKey(0)

‎ch21-Contours/21-moments.py

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#-*-coding:utf8-*-#
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__author__ = 'play4fun'
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"""
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create time:15-10-23 下午12:56
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"""
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import cv2
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import numpy as np
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img = cv2.imread('../data/star.jpg',0)
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ret,thresh = cv2.threshold(img,127,255,0)
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# ret, binary = cv2.threshold(gray,127,255,cv2.THRESH_BINARY)
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contours,hierarchy = cv2.findContours(thresh, 1, 2)
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# contours, hierarchy = cv2.findContours(thresh,cv2.RETR_TREE,cv2.CHAIN_APPROX_SIMPLE)
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cnt = contours[0]
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M = cv2.moments(cnt)
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print M

‎ch22/hist-1.py

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#-*-coding:utf8-*-#
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__author__ = 'play4fun'
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"""
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create time:15-10-24 下午5:17
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"""
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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img = cv2.imread('../data/home.jpg',0)
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plt.hist(img.ravel(),256,[0,256]);
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plt.show()

‎ch22/hist-bgr.py

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#-*-coding:utf8-*-#
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__author__ = 'play4fun'
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"""
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create time:15-10-24 下午5:19
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"""
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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img = cv2.imread('../data/home.jpg')
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color = ('b','g','r')
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# 对一个列表或数组既要遍历索引又要遍历元素时
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# 使用内置 enumerrate 函数会有更加直接 优美的做法
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#enumerate 会将数组或列表组成一个索引序列。
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# 使我们再获取索引和索引内容的时候更加方便
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for i,col in enumerate(color):
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histr = cv2.calcHist([img],[i],None,[256],[0,256])
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plt.plot(histr,color = col)
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plt.xlim([0,256])
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plt.show()

‎ch22/hist-normalized-2.py

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#-*-coding:utf8-*-#
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__author__ = 'play4fun'
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"""
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create time:15-10-24 下午5:26
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"""
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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img = cv2.imread('../data/contrast75.png',0)
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#flatten() 将数组变成一维
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hist,bins = np.histogram(img.flatten(),256,[0,256])
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#计算累积分布图
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cdf = hist.cumsum()
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##
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# 构建 Numpy 掩模数组 cdf 为原数组 当数组元素为 0 时 掩盖(计算时被忽略
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cdf_m = np.ma.masked_equal(cdf,0)
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cdf_m = (cdf_m - cdf_m.min())*255/(cdf_m.max()-cdf_m.min())
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# 对被掩盖的元素赋值，赋值为 0
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cdf = np.ma.filled(cdf_m,0).astype('uint8')
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img2 = cdf[img]
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cv2.imshow("img2",img2)
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cv2.waitKey(0)
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##
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#flatten() 将数组变成一维
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hist,bins = np.histogram(img2.flatten(),256,[0,256])
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#计算累积分布图
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cdf = hist.cumsum()
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cdf_normalized = cdf * hist.max()/ cdf.max()
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plt.plot(cdf_normalized, color = 'b')
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plt.hist(img.flatten(),256,[0,256], color = 'r')
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plt.xlim([0,256])
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plt.legend(('cdf','histogram'), loc = 'upper left')
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plt.show()

‎ch22/hist-normalized.py

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#-*-coding:utf8-*-#
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__author__ = 'play4fun'
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"""
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create time:15-10-24 下午5:26
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"""
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import cv2
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import numpy as np
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from matplotlib import pyplot as plt
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img = cv2.imread('../data/contrast75.png',0)
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#flatten() 将数组变成一维
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hist,bins = np.histogram(img.flatten(),256,[0,256])
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#计算累积分布图
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cdf = hist.cumsum()
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cdf_normalized = cdf * hist.max()/ cdf.max()
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plt.plot(cdf_normalized, color = 'b')
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plt.hist(img.flatten(),256,[0,256], color = 'r')
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plt.xlim([0,256])
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plt.legend(('cdf','histogram'), loc = 'upper left')
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plt.show()

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