Created
November 16, 2023 23:30
-
-
Save humpydonkey/ad40f07211449fee281420038b815b62 to your computer and use it in GitHub Desktop.
Check consistency of four corners of an image
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
import itertools | |
import PIL.Image | |
import numpy as np | |
def four_corners_similar(image: PIL.Image.Image): | |
pixel_value_diff_tolerance = 40 # tolerance for pixel value difference, 0-255 | |
discrepancy_threshold = 0.01 # max percentage of pixels that can be different between corners to be considered similar | |
corner_image_ratio = 0.06 | |
crop_size = int(corner_image_ratio * min(image.size)) | |
# print(crop_size) | |
w, h = image.size | |
img_np = np.asarray(image.convert("RGB"), dtype=np.int16) | |
top_left = img_np[0:crop_size, 0:crop_size] | |
top_right = img_np[0:crop_size, w - crop_size:w] | |
bottom_left = img_np[h - crop_size:h, 0:crop_size] | |
bottom_right = img_np[h - crop_size:h, w - crop_size:w] | |
corners = [top_left, top_right, bottom_left, bottom_right] | |
max_diff = 0 | |
for i, j in itertools.product(range(len(corners)), range(len(corners))): | |
if j <= i: | |
continue | |
diff = np.absolute(corners[i] - corners[j]) | |
diff[diff < pixel_value_diff_tolerance] = 0 | |
percentage_diff = np.count_nonzero(diff) / (crop_size**2 * 3) | |
max_diff = max(max_diff, percentage_diff) | |
if percentage_diff > discrepancy_threshold: | |
# print(f"Corners {i} and {j} are not similar. Percentage: {percentage_diff:.3f}") | |
# display(PIL.Image.fromarray(corners[i].astype(np.uint8))) | |
# display(PIL.Image.fromarray(corners[j].astype(np.uint8))) | |
# display(image.resize((256, 256))) | |
return False, max_diff | |
return True, max_diff |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment