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import cv2 |
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import numpy as np |
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import glob |
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import os |
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from tqdm import tqdm |
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import random |
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im_paths = glob.glob('./img/*/*') |
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random.shuffle(im_paths) |
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for im_path in tqdm(im_paths): |
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if '-L1_' in im_path: |
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alb_path = im_path.split('-L1_')[0].replace('img/','alb/') + '.png' |
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else: |
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alb_path = im_path.split('-L2_')[0].replace('img/','alb/') + '.png' |
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if not os.path.exists(alb_path): |
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print(im_path) |
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print(alb_path) |
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im = cv2.imread(im_path) |
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alb = cv2.imread(alb_path) |
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_, mask = cv2.threshold(cv2.cvtColor(alb,cv2.COLOR_BGR2GRAY), 1, 255, cv2.THRESH_BINARY) |
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im_min = np.min(im,axis=-1) |
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kernel = np.ones((3,3)) |
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mask_erode = cv2.dilate(mask,kernel=kernel) |
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mask_erode = cv2.erode(mask_erode,kernel=kernel) |
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mask_erode = cv2.erode(mask_erode,iterations=4,kernel=kernel) |
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metric = np.min(im_min[mask_erode==255]) |
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metric_num = 0 |
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if metric==0 or metric==1: |
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metric_num = np.sum(im_min[mask_erode==255]==metric) |
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if metric_num>=20: |
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alb_temp = alb.astype(np.float64) |
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alb_temp[alb_temp==0] = alb_temp[alb_temp==0]+1e-5 |
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shadow = np.clip(im.astype(np.float64)/alb_temp,0,1) |
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shadow = (shadow*255).astype(np.uint8) |
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shadow_path = im_path.replace('img/','temp/') |
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cv2.imwrite(shadow_path,shadow) |
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continue |
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alb_temp = alb.astype(np.float64) |
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alb_temp[alb_temp==0] = alb_temp[alb_temp==0]+1e-5 |
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shadow = np.clip(im.astype(np.float64)/alb_temp,0,1) |
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shadow = (shadow*255).astype(np.uint8) |
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shadow_path = im_path.replace('img/','shadow/') |
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cv2.imwrite(shadow_path,shadow) |
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mask_path = im_path.replace('img/','mask/') |
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cv2.imwrite(mask_path,mask) |
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