Upload layer_diff_dataset/change_mask_try.py with huggingface_hub
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layer_diff_dataset/change_mask_try.py
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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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# 对mask进行膨胀
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# root_folder = '../data/aim-500'
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root_folder = '../data/P3M-10k/validation/P3M-500-NP'
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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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# m_1 = len(os.listdir(mask_folder))
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# m_2 = len(os.listdir(mask_dilate_folder))
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# print(m_1,m_2)
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# exit(0)
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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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# if i==10:
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# break
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# folder_path = '/mnt/workspace/workgroup/sihui.jsh/layer_diff_dataset/YoutubeVOS/mask/0043f083b5'
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img_path = os.path.join(mask_folder,vid_name)
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# print(img_path)
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img_path_ = os.path.join(mask_dilate_folder,vid_name)
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# folder_path = '/mnt/workspace/workgroup/sihui.jsh/layer_diff_dataset/YoutubeVOS/mask/0043f083b5'
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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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# pbar = tqdm(enumerate(file_list),total=len(file_list))
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# for i, image_name in enumerate(file_list):
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gt = cv2.imread(img_path,cv2.IMREAD_GRAYSCALE)
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# gt = cv2.resize(gt,(512,512))
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kernel_size = 100
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kernel = np.ones((kernel_size, kernel_size), 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(img_path_,gt)
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# print(img_path_)
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# exit()
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