Commit @4346ed603c6a868f515d028e5d080aa5b7e48063

윤영준 2023-07-12

data cleaning

@4346ed603c6a868f515d028e5d080aa5b7e48063

9ae0078

4346ed6

binary mask map test.py

--- binary mask map test.py

+++ binary mask map test.py


+import concurrent.futures
 import numpy as np
 import cv2
 import glob

 
     return shifted
 
-def binary_diff_mask(clean, dirty, thresold=0.2):
+def binary_diff_mask(clean, dirty, thresold=0.3):
     # 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)

 
     return bin_diff
 
-clean = glob.glob("data/source/clean/*.png")
+clean = glob.glob("data/source/Oxford_raindrop_dataset/clean/*.png")
 clean = sorted(clean)
-dirty = glob.glob("data/source/dirty/*.png")
+dirty = glob.glob("data/source/Oxford_raindrop_dataset/dirty/*.png")
 dirty = sorted(dirty)
 
-clean_img = cv2.imread(clean[0])
-dirty_img = cv2.imread(dirty[0])
+clean_img = cv2.imread(clean[34])
+dirty_img = cv2.imread(dirty[34])
 
 binary_diff_mask_img = binary_diff_mask(dirty_img/255, clean_img/255, thresold=0.05)
 
-k = 40
+k = 20
 
-for i in range(k*2):
+def process(i, j):
     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)
+    clean_img_copy = shift_img(clean_img, (i-k)/4, (j-k)/4)
+    binary_diff_mask_img = binary_diff_mask(dirty_img / 255, clean_img_copy / 255, threshold=0.2)
+    cv2.imwrite(f"test/test_img{(i-k)/4}-{(j-k)/4}.png", binary_diff_mask_img*255)
+
+with concurrent.futures.ProcessPoolExecutor() as executor:
+    for i in range(k*2):
+        for j in range(k*2):
+            executor.submit(process, i, j)

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...	...	@@ -1,3 +1,4 @@
	1	+import concurrent.futures
1	2	import numpy as np
2	3	import cv2
3	4	import glob
...	...	@@ -11,7 +12,7 @@
11	12
12	13	return shifted
13	14
14		-def binary_diff_mask(clean, dirty, thresold=0.2):
	15	+def binary_diff_mask(clean, dirty, thresold=0.3):
15	16	# this parts corrects gamma, and always remember, sRGB values are not in linear scale with lights intensity,
16	17	clean = np.power(clean, 1/2.2)
17	18	dirty = np.power(dirty, 1/2.2)
...	...	@@ -24,20 +25,25 @@
24	25
25	26	return bin_diff
26	27
27		-clean = glob.glob("data/source/clean/*.png")
	28	+clean = glob.glob("data/source/Oxford_raindrop_dataset/clean/*.png")
28	29	clean = sorted(clean)
29		-dirty = glob.glob("data/source/dirty/*.png")
	30	+dirty = glob.glob("data/source/Oxford_raindrop_dataset/dirty/*.png")
30	31	dirty = sorted(dirty)
31	32
32		-clean_img = cv2.imread(clean[0])
33		-dirty_img = cv2.imread(dirty[0])
	33	+clean_img = cv2.imread(clean[34])
	34	+dirty_img = cv2.imread(dirty[34])
34	35
35	36	binary_diff_mask_img = binary_diff_mask(dirty_img/255, clean_img/255, thresold=0.05)
36	37
37		-k = 40
	38	+k = 20
38	39
39		-for i in range(k*2):
	40	+def process(i, j):
40	41	print(i)
41		- clean_img_copy = shift_img(clean_img, (i-k)/4, 0)
42		- binary_diff_mask_img = binary_diff_mask(dirty_img / 255, clean_img_copy / 255, thresold=0.2)
43		- cv2.imwrite(f"test/test_img{(i-k)/4}.png", binary_diff_mask_img*255)
	42	+ clean_img_copy = shift_img(clean_img, (i-k)/4, (j-k)/4)
	43	+ binary_diff_mask_img = binary_diff_mask(dirty_img / 255, clean_img_copy / 255, threshold=0.2)
	44	+ cv2.imwrite(f"test/test_img{(i-k)/4}-{(j-k)/4}.png", binary_diff_mask_img*255)
	45	+
	46	+with concurrent.futures.ProcessPoolExecutor() as executor:
	47	+ for i in range(k*2):
	48	+ for j in range(k*2):
	49	+ executor.submit(process, i, j)

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