calculate error
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@@ -1,5 +1,6 @@
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nohup python cvae.py --name="lhunor_abl_all_post_r7" > nohup/post/abl_all_post_r7.out 2>&1 &
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nohup python cvae.py --name="lhunor_abl_all_post_r7" > nohup/post/abl_all_post_r7.out 2>&1 &
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nohup python evaluate_ae.py --name lhunor_abl_all_post_r7_70k > nohup/evaluate/abl_all_post_r7_70k.out 2>&1 &
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nohup python evaluate_ae.py --name lhunor_abl_all_post_r7_70k > nohup/evaluate/abl_all_post_r7_70k.out 2>&1 &
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nohup python calculate_error.py --name error_abl_all_post_r7_70k > nohup/error/abl_all_post_r7_70k.out 2>&1 &
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one final convolutional layer for smoothing, on the final coordinates
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one final convolutional layer for smoothing, on the final coordinates
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+1
-1
@@ -59,7 +59,7 @@ if __name__ == '__main__':
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folder = config['test_dir']
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folder = config['test_dir']
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checkpoint_name = config['name']
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checkpoint_name = config['name']
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iteration = ''
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iteration = '70000'
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F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
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F = np.load("custom_utils/smpl_faces" + skirt_modifier + ".npy").astype(np.int32)
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garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
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garment_type_table = np.load('custom_data/garment_type_table_test.npy', allow_pickle=True).item()
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