def _image_entropy(img):
 hist = img.histogram()
 hist_size = sum(hist)
 hist = [(float(h) / hist_size) for h in hist]
 return (- sum(((p * math.log(p, 2)) for p in hist if (p != 0))))

def _image_entropy ( img ) : hist = img . histogram ( ) hist_size = sum ( hist ) hist = [ ( float ( h ) / hist_size ) for h in hist ] return ( - sum ( ( ( p * math . log ( p , 2 ) ) for p in hist if ( p != 0 ) ) ) )
calculate the entropy of an image .