Examples of using histograms in python

samples/python2/hist.py

+''' This is a sample for histogram plotting for RGB images and grayscale images for better understanding of colour distribution
+
+Benefit : Learn how to draw histogram of images
+          Get familier with cv2.calcHist, cv2.equalizeHist,cv2.normalize and some drawing functions
+
+Level : Beginner or Intermediate
+
+Functions : 1) hist_curve : returns histogram of an image drawn as curves
+            2) hist_lines : return histogram of an image drawn as bins ( only for grayscale images )
+
+Usage : python hist.py <image_file> 
+
+Abid Rahman 3/14/12 debug Gary Bradski
+'''
+
+import cv2,sys
+import numpy as np
+
+bins = np.arange(256).reshape(256,1)
+
+def hist_curve(im):
+    h = np.zeros((300,256,3))
+    if len(im.shape) == 2:
+        color = [(255,255,255)]
+    elif im.shape[2] == 3:
+        color = [ (255,0,0),(0,255,0),(0,0,255) ]
+    for ch, col in enumerate(color):
+        hist_item = cv2.calcHist([im],[ch],None,[256],[0,255])
+        cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
+        hist=np.int32(np.around(hist_item))
+        pts = np.int32(np.column_stack((bins,hist)))
+        cv2.polylines(h,[pts],False,col)
+    y=np.flipud(h)
+    return y
+
+def hist_lines(im):
+    h = np.zeros((300,256,3))
+    if len(im.shape)!=2:
+        print "hist_lines applicable only for grayscale images"
+        #print "so converting image to grayscale for representation"
+        im = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
+    hist_item = cv2.calcHist([im],[0],None,[256],[0,255])
+    cv2.normalize(hist_item,hist_item,0,255,cv2.NORM_MINMAX)
+    hist=np.int32(np.around(hist_item))
+    for x,y in enumerate(hist):
+        cv2.line(h,(x,0),(x,y),(255,255,255))
+    y = np.flipud(h)
+    return y
+
+
+if __name__ == '__main__':
+    
+    import urllib2
+
+    if len(sys.argv)>1:
+        im = cv2.imread(sys.argv[1])
+    else :
+        im = cv2.imread('../cpp/lena.jpg')
+        print "usage : python hist.py <image_file>"
+        
+
+    gray = cv2.cvtColor(im,cv2.COLOR_BGR2GRAY)
+
+   
+    print ''' Histogram plotting \n
+    Keymap :\n
+    a - show histogram for color image in curve mode \n
+    b - show histogram in bin mode \n
+    c - show equalized histogram (always in bin mode) \n
+    d - show histogram for color image in curve mode \n
+    e - show histogram for a normalized image in curve mode \n
+    Esc - exit \n
+    '''
+
+    cv2.imshow('image',im)
+    while True:
+        k = cv2.waitKey(0)&0xFF
+        if k == ord('a'):
+            curve = hist_curve(im)
+            cv2.imshow('histogram',curve)
+            cv2.imshow('image',im)
+            print 'a'
+        elif k == ord('b'):
+            print 'b'
+            lines = hist_lines(im)
+            cv2.imshow('histogram',lines)
+            cv2.imshow('image',gray)
+        elif k == ord('c'):
+            print 'c'
+            equ = cv2.equalizeHist(gray)
+            lines = hist_lines(equ)
+            cv2.imshow('histogram',lines)
+            cv2.imshow('image',equ)
+        elif k == ord('d'):
+            print 'd'
+            curve = hist_curve(gray)
+            cv2.imshow('histogram',curve)
+            cv2.imshow('image',gray)
+        elif k == ord('e'):
+            print 'e'
+            norm = cv2.normalize(gray,alpha = 0,beta = 255,norm_type = cv2.NORM_MINMAX)
+            lines = hist_lines(norm)
+            cv2.imshow('histogram',lines)
+            cv2.imshow('image',norm)
+        elif k == 27:
+            print 'ESC'
+            cv2.destroyAllWindows()
+            break
+