mirror of https://github.com/JDAI-CV/fast-reid.git
31 lines
1.2 KiB
Python
31 lines
1.2 KiB
Python
import unittest
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import numpy as np
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import os
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from glob import glob
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class TestFeatureAlign(unittest.TestCase):
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def test_caffe_pytorch_feat_align(self):
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caffe_feat_path = "/export/home/lxy/cvpalgo-fast-reid/tools/deploy/caffe_R50_output"
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pytorch_feat_path = "/export/home/lxy/cvpalgo-fast-reid/demo/logs/R50_256x128_pytorch_feat_output"
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feat_filenames = os.listdir(caffe_feat_path)
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for feat_name in feat_filenames:
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caffe_feat = np.load(os.path.join(caffe_feat_path, feat_name))
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pytorch_feat = np.load(os.path.join(pytorch_feat_path, feat_name))
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sim = np.dot(caffe_feat, pytorch_feat.transpose())[0][0]
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assert sim > 0.97, f"Got similarity {sim} and feature of {feat_name} is not aligned"
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def test_model_performance(self):
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caffe_feat_path = "/export/home/lxy/cvpalgo-fast-reid/tools/deploy/caffe_R50_output"
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feat_filenames = os.listdir(caffe_feat_path)
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feats = []
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for feat_name in feat_filenames:
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caffe_feat = np.load(os.path.join(caffe_feat_path, feat_name))
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feats.append(caffe_feat)
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from ipdb import set_trace; set_trace()
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if __name__ == '__main__':
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unittest.main()
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