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