idow09
7b3d9f02ec
prevent failure when no training_results available ( #409 )
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Use `chkpt.get('training_results')` instead of `chkpt.get('training_results')` so if the dict doesn't contain this key it won't throw a `KeyError
2019-07-31 14:12:27 +02:00
Yonghye Kwon
97edba0b7a
Remove Unused Argument of parser : --var ( #408 )
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Remove Unused Argument of parser : --var
2019-07-31 14:05:43 +02:00
Glenn Jocher
07ffc4e7f9
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Glenn Jocher
9ef8d42f0e
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Glenn Jocher
e8303a366f
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Glenn Jocher
b11bb91804
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Glenn Jocher
c413aaefea
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Glenn Jocher
8615b3a7c3
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Glenn Jocher
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Glenn Jocher
7a81cc2499
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Glenn Jocher
bd92457604
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
b459587cb0
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Glenn Jocher
813024116b
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Glenn Jocher
034d2949b9
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Glenn Jocher
09b3670579
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Glenn Jocher
8501aed49f
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
bb38391342
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Glenn Jocher
bd9789aa00
equal layer weights
2019-07-12 12:23:17 +02:00
Glenn Jocher
5886200401
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Glenn Jocher
a2909c59f8
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
4f6ef59d92
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Glenn Jocher
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Glenn Jocher
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Glenn Jocher
0bd763f528
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Glenn Jocher
feeaf734f2
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Glenn Jocher
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Glenn Jocher
60bc2c1fbd
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Glenn Jocher
94669fb704
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Glenn Jocher
291c3ec9c7
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glenn-jocher
70f6379601
GIoU to default
2019-07-07 23:24:34 +02:00
glenn-jocher
32a52dfb02
GIoU to default
2019-07-05 12:33:37 +02:00
glenn-jocher
429bd3b8a9
GIoU to default
2019-07-05 11:41:43 +02:00
glenn-jocher
b649a95c9a
GIoU to default
2019-07-05 00:36:37 +02:00
glenn-jocher
abf59f1565
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glenn-jocher
d0eace6cec
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glenn-jocher
109991198c
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glenn-jocher
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glenn-jocher
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glenn-jocher
a8cf64af31
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2019-07-02 18:21:28 +02:00
Yonghye Kwon
ccf757b3ea
changed the criteria for the best weight file ( #356 )
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* changed the criteria for the best weight file
changed the criteria for the best weight file from loss to mAP
I trained the model on my custom dataset. But I failed to get a good results when I load the weight file that has the lowest loss on test dataset.
I thought that the loss used in YOLO is not proper criteria for detection performance. So I changed the criteria from loss to mAP.
what do you think of this?
* Update train.py
2019-07-02 12:24:18 +02:00
glenn-jocher
1fd871abd8
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glenn-jocher
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glenn-jocher
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glenn-jocher
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glenn-jocher
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glenn-jocher
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glenn-jocher
63036deeb7
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glenn-jocher
32f5ea955b
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glenn-jocher
db2674aa31
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glenn-jocher
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Glenn Jocher
45540c787f
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Glenn Jocher
1d76751e1f
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