Upload layer_diff_dataset/change_mask copy 2.py with huggingface_hub

layer_diff_dataset/change_mask copy 2.py

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+import os
+import shutil
+from tqdm import tqdm
+import cv2
+import numpy as np
+
+# 对mask进行膨胀
+
+root_folder = '../data/video_dataset/YoutubeVOS/train'
+mask_folder = os.path.join(root_folder,'mask')
+mask_dilate_folder = os.path.join(root_folder,'mask_dilate')
+
+os.makedirs(mask_dilate_folder,exist_ok=True)
+# m_1 = len(os.listdir(mask_folder))
+# m_2 = len(os.listdir(mask_dilate_folder))
+# print(m_1,m_2)
+# exit(0)
+vid_list = os.listdir(mask_folder)
+pbar = tqdm(enumerate(vid_list),total=len(vid_list))
+for i, vid_name in pbar:
+    # folder_path = '/mnt/workspace/workgroup/sihui.jsh/layer_diff_dataset/YoutubeVOS/mask/0043f083b5'
+    folder_path = os.path.join(mask_folder,vid_name)
+    # folder_path = '/mnt/workspace/workgroup/sihui.jsh/layer_diff_dataset/YoutubeVOS/mask/0043f083b5'
+    folder_path_ = os.path.join(mask_dilate_folder,vid_name)
+    os.makedirs(folder_path_,exist_ok=True)
+    file_list = os.listdir(folder_path)
+    file_list = [i for i in file_list if i.endswith('.png')]
+    file_list.sort()
+
+    # pbar = tqdm(enumerate(file_list),total=len(file_list))
+    for i, image_name in enumerate(file_list):
+        gt = cv2.imread(os.path.join(folder_path,image_name),cv2.IMREAD_GRAYSCALE)
+        # gt = cv2.resize(gt,(512,512))
+        kernel = np.ones((40, 40), np.uint8)
+        gt = cv2.dilate(gt,kernel,20)
+        gt = gt.clip(0, 255).round().astype('uint8')
+        cv2.imwrite(os.path.join(folder_path_,image_name),gt)
+    # exit()