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import os |
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import shutil |
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from tqdm import tqdm |
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import cv2 |
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import numpy as np |
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root_folder = '../data/video_dataset/YoutubeVOS/train' |
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mask_folder = os.path.join(root_folder,'mask') |
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mask_dilate_folder = os.path.join(root_folder,'mask_dilate') |
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os.makedirs(mask_dilate_folder,exist_ok=True) |
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vid_list = os.listdir(mask_folder) |
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pbar = tqdm(enumerate(vid_list),total=len(vid_list)) |
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for i, vid_name in pbar: |
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folder_path = os.path.join(mask_folder,vid_name) |
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folder_path_ = os.path.join(mask_dilate_folder,vid_name) |
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os.makedirs(folder_path_,exist_ok=True) |
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file_list = os.listdir(folder_path) |
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file_list = [i for i in file_list if i.endswith('.png')] |
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file_list.sort() |
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for i, image_name in enumerate(file_list): |
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gt = cv2.imread(os.path.join(folder_path,image_name),cv2.IMREAD_GRAYSCALE) |
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kernel = np.ones((40, 40), np.uint8) |
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gt = cv2.dilate(gt,kernel,20) |
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gt = gt.clip(0, 255).round().astype('uint8') |
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cv2.imwrite(os.path.join(folder_path_,image_name),gt) |
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