def to_channels(filename, normalize):
img = cv2.imread(filename, 1)
b, g, r = cv2.split(img)
total = np.sum(img, axis=2).astype(np.float64)
r_ = (r.astype(np.float64)/total*255).astype(np.uint8)
g_ = (g.astype(np.float64)/total*255).astype(np.uint8)
b_ = (b.astype(np.float64)/total*255).astype(np.uint8)
if (normalize):
return r_, g_, b_
else:
return r, g, b
def to_cv_image(channels):
assert len(channels) == 3
return cv2.merge(channels)
if __name__ == "__main__":
if len(sys.argv) < 2:
print 'A filename is required as an argument to run this script'
else:
filename = sys.argv[1]
rgb = to_channels(sys.argv[1], normalize=True)
img = to_cv_image(rgb)
cv2.imshow('The normalized image', img)
cv2.waitKey(0)
cv2.destroyWindow('The normalized image')
write_if_yes(img, filename, 'normalized')
def to_cv_image(filename):
img = cv2.imread(filename, 1)
return img
if __name__ == "__main__":
if len(sys.argv) < 3:
print 'Two filenames are required as an argument to run this script'
else:
if len(sys.argv) > 3:
THRESHOLD = int(sys.argv[3])
file1, file2 = sys.argv[1], sys.argv[2]
img_1 = to_cv_image(file1)
img_2 = to_cv_image(file2)
height = min(img_1.shape[0], img_2.shape[0])
width = min(img_1.shape[1], img_2.shape[1])
img_1 = crop(img_1, 0, height, 0, width)
img_2 = crop(img_2, 0, height, 0, width)
img = img_1 - img_2
# pdb.set_trace()
cv2.imshow('First', img_1)
cv2.imshow('Second', img_2)
cv2.imshow('The diff', img)
cv2.waitKey(0)
cv2.destroyAllWindows()
write_if_yes(img, file1, 'diff')
