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Open Source Computer Vision Library
https://opencv.org/
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80 lines
2.7 KiB
80 lines
2.7 KiB
#!/usr/bin/python |
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import cv2.cv as cv |
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import sys |
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import urllib2 |
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hist_size = 64 |
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range_0 = [0, 256] |
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ranges = [ range_0 ] |
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class DemHist: |
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def __init__(self, src_image): |
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self.src_image = src_image |
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self.dst_image = cv.CloneMat(src_image) |
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self.hist_image = cv.CreateImage((320, 200), 8, 1) |
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self.hist = cv.CreateHist([hist_size], cv.CV_HIST_ARRAY, ranges, 1) |
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self.brightness = 0 |
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self.contrast = 0 |
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cv.NamedWindow("image", 0) |
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cv.NamedWindow("histogram", 0) |
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cv.CreateTrackbar("brightness", "image", 100, 200, self.update_brightness) |
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cv.CreateTrackbar("contrast", "image", 100, 200, self.update_contrast) |
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self.update_brightcont() |
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def update_brightness(self, val): |
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self.brightness = val - 100 |
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self.update_brightcont() |
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def update_contrast(self, val): |
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self.contrast = val - 100 |
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self.update_brightcont() |
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def update_brightcont(self): |
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# The algorithm is by Werner D. Streidt |
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# (http://visca.com/ffactory/archives/5-99/msg00021.html) |
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if self.contrast > 0: |
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delta = 127. * self.contrast / 100 |
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a = 255. / (255. - delta * 2) |
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b = a * (self.brightness - delta) |
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else: |
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delta = -128. * self.contrast / 100 |
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a = (256. - delta * 2) / 255. |
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b = a * self.brightness + delta |
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cv.ConvertScale(self.src_image, self.dst_image, a, b) |
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cv.ShowImage("image", self.dst_image) |
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cv.CalcArrHist([self.dst_image], self.hist) |
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(min_value, max_value, _, _) = cv.GetMinMaxHistValue(self.hist) |
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cv.Scale(self.hist.bins, self.hist.bins, float(self.hist_image.height) / max_value, 0) |
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cv.Set(self.hist_image, cv.ScalarAll(255)) |
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bin_w = round(float(self.hist_image.width) / hist_size) |
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for i in range(hist_size): |
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cv.Rectangle(self.hist_image, (int(i * bin_w), self.hist_image.height), |
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(int((i + 1) * bin_w), self.hist_image.height - cv.Round(self.hist.bins[i])), |
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cv.ScalarAll(0), -1, 8, 0) |
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cv.ShowImage("histogram", self.hist_image) |
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if __name__ == "__main__": |
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# Load the source image. |
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if len(sys.argv) > 1: |
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src_image = cv.GetMat(cv.LoadImage(sys.argv[1], 0)) |
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else: |
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url = 'http://code.opencv.org/projects/opencv/repository/revisions/master/raw/samples/c/baboon.jpg' |
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filedata = urllib2.urlopen(url).read() |
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imagefiledata = cv.CreateMatHeader(1, len(filedata), cv.CV_8UC1) |
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cv.SetData(imagefiledata, filedata, len(filedata)) |
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src_image = cv.DecodeImageM(imagefiledata, 0) |
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dh = DemHist(src_image) |
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cv.WaitKey(0) |
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cv.DestroyAllWindows()
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