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32 lines
1.1 KiB
Python
32 lines
1.1 KiB
Python
import cv2
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import os
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def resize_image(seg_in, input_height, input_width):
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return cv2.resize(seg_in, (input_width, input_height), interpolation=cv2.INTER_NEAREST)
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dir_imgs = './training_data_sample_enhancement/images'
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dir_out_imgs = './training_data_sample_enhancement/images_gt'
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dir_out_labs = './training_data_sample_enhancement/labels_gt'
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ls_imgs = os.listdir(dir_imgs)
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ls_scales = [ 0.5, 0.55, 0.6, 0.65, 0.7, 0.75, 0.8, 0.85, 0.9]
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for img in ls_imgs:
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img_name = img.split('.')[0]
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img_type = img.split('.')[1]
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image = cv2.imread(os.path.join(dir_imgs, img))
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for i, scale in enumerate(ls_scales):
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height_sc = int(image.shape[0]*scale)
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width_sc = int(image.shape[1]*scale)
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image_down_scaled = resize_image(image, height_sc, width_sc)
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image_back_to_org_scale = resize_image(image_down_scaled, image.shape[0], image.shape[1])
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cv2.imwrite(os.path.join(dir_out_imgs, img_name+'_'+str(i)+'.'+img_type), image_back_to_org_scale)
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cv2.imwrite(os.path.join(dir_out_labs, img_name+'_'+str(i)+'.'+img_type), image)
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