File name
Commit message
Commit date
import numpy as np
import cv2
import glob
def shift_img(img, x, y):
M = np.float32([[1, 0, x],
[0, 1, y]])
shifted = cv2.warpAffine(img, M, (img.shape[1], img.shape[0]))
return shifted
def binary_diff_mask(clean, dirty, thresold=0.2):
# this parts corrects gamma, and always remember, sRGB values are not in linear scale with lights intensity,
clean = np.power(clean, 1/2.2)
dirty = np.power(dirty, 1/2.2)
# averaged_per_pixel = np.abs(dirty / shift_img(clean, 5, 0) - 1)
# print(averaged_per_pixel)
diff = np.abs(clean - dirty)
bin_diff = (diff > thresold).astype(np.uint8)
return bin_diff
clean = glob.glob("data/source/clean/*.png")
clean = sorted(clean)
dirty = glob.glob("data/source/dirty/*.png")
dirty = sorted(dirty)
clean_img = cv2.imread(clean[0])
dirty_img = cv2.imread(dirty[0])
binary_diff_mask_img = binary_diff_mask(dirty_img/255, clean_img/255, thresold=0.05)
k = 40
for i in range(k*2):
print(i)
clean_img_copy = shift_img(clean_img, (i-k)/4, 0)
binary_diff_mask_img = binary_diff_mask(dirty_img / 255, clean_img_copy / 255, thresold=0.2)
cv2.imwrite(f"test/test_img{(i-k)/4}.png", binary_diff_mask_img*255)