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2019-07-08 15:24:20 +02:00
291c3ec9c7
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2019-07-08 15:02:20 +02:00
70f6379601
GIoU to default
2019-07-07 23:24:34 +02:00
32a52dfb02
GIoU to default
2019-07-05 12:33:37 +02:00
429bd3b8a9
GIoU to default
2019-07-05 11:41:43 +02:00
b649a95c9a
GIoU to default
2019-07-05 00:36:37 +02:00
abf59f1565
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2019-07-03 15:37:04 +02:00
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2019-07-02 18:21:28 +02:00
ccf757b3ea
changed the criteria for the best weight file ( #356 )
...
* 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
1fd871abd8
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2019-07-01 17:44:42 +02:00
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2019-05-18 12:07:57 +02:00
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2019-05-13 22:01:10 +02:00
584e0a3be8
add *.jpeg support
2019-05-11 14:55:10 +02:00
c45cdc4fa3
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2019-05-10 17:08:00 +02:00
9ffb40b0be
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2019-05-10 16:29:37 +02:00
ddd0474111
add *.jpeg support
2019-05-10 15:28:54 +02:00
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add *.jpeg support
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ae03cf3eea
add *.jpeg support
2019-05-10 15:16:02 +02:00
31592c276f
add *.jpeg support
2019-05-10 14:15:09 +02:00
40bc015b75
updates
2019-05-08 18:54:55 +02:00
Glenn Jocher
Yonghye Kwon