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30 lines
848 B
Python
30 lines
848 B
Python
# input: frame list, first frame mask
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# output: segmentation results on all frames
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import os
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import glob
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import numpy as np
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from PIL import Image
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class XMem:
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# based on https://github.com/hkchengrex/XMem
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pass
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if __name__ == '__main__':
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# video frames
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video_path_list = glob.glob(os.path.join('/ssd1/gaomingqi/datasets/davis/JPEGImages/480p/dance-twirl', '*.jpg'))
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video_path_list.sort()
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# first frame
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first_frame_path = '/ssd1/gaomingqi/datasets/davis/Annotations/480p/dance-twirl/00000.png'
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# load frames
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frames = []
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for video_path in video_path_list:
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frames.append(np.array(Image.open(video_path).convert('RGB')))
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frames = np.stack(frames, 0) # N, H, W, C
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# load first frame annotation
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first_frame_annotation = np.array(Image.open(first_frame_path).convert('P')) # H, W, C
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