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import sys |
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import os |
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LOCAL_PATH = os.path.dirname(os.path.abspath(__file__)) |
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TEST_PATH = os.path.join(LOCAL_PATH, "../../../", "test") |
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sys.path.append(TEST_PATH) |
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from paddleseg.utils.download import download_file_and_uncompress |
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model_urls = { |
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"pphumanseg_lite_portrait_398x224": |
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"https://paddleseg.bj.bcebos.com/dygraph/ppseg/ppseg_lite_portrait_398x224.tar.gz", |
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"deeplabv3p_resnet50_os8_humanseg_512x512_100k": |
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"https://paddleseg.bj.bcebos.com/dygraph/humanseg/train/deeplabv3p_resnet50_os8_humanseg_512x512_100k.zip", |
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"fcn_hrnetw18_small_v1_humanseg_192x192": |
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"https://paddleseg.bj.bcebos.com/dygraph/humanseg/train/fcn_hrnetw18_small_v1_humanseg_192x192.zip", |
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"pphumanseg_lite_generic_human_192x192": |
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"https://paddleseg.bj.bcebos.com/dygraph/humanseg/train/pphumanseg_lite_generic_192x192.zip", |
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} |
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if __name__ == "__main__": |
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for model_name, url in model_urls.items(): |
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download_file_and_uncompress( |
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url=url, |
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savepath=LOCAL_PATH, |
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extrapath=LOCAL_PATH, |
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extraname=model_name) |
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print("Pretrained model download success!") |
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