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how can I get same mAP as paper #5

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johnson00111 opened this issue Sep 26, 2018 · 4 comments
Open

how can I get same mAP as paper #5

johnson00111 opened this issue Sep 26, 2018 · 4 comments

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@johnson00111
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I run this code in 12,24,32,48 bits(epochs51)
each of them in six times
but only 12 bits can get mAP higher than the mAP shown in the paper(0.401)
In 32 bits get 0.4599 but paper say the method can get 0.531
and 48 bit get 0.4487 but paper's mAP is 0.558

Is there some setting need to change or how many epochs is prefect ?

@ht014
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ht014 commented Sep 26, 2018

Hello, you can try to train only several epochs, e.g. 4 epoches.

@johnson00111
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johnson00111 commented Sep 28, 2018

I try again train the model with 4 epoches for six time but only get mAP in the following table
Bitsnum | 12bits | 24bits | 32bits | 48bits
Codes1 | 0.4748 | 0.4735 | 0.4723 | 0.4606
Codes2 | 0.4308 | 0.4366 | 0.4600 | 0.4632
Codes3 | 0.4341 | 0.4686 | 0.4528 | 0.4399
Codes4 | 0.3941 | 0.4360 | 0.4368 | 0.4782
Codes5 | 0.4284 | 0.4142 | 0.4698 | 0.4822
Codes6 | 0.4911 | 0.4701 | 0.4723 | 0.4480

In 12 bits mAP is good enough, but when bits number goes bigger the mAP still the same
May I ask which tensorflow and prettytensor version you use?

@ximi2018
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I run this code in 12,24,32,48 bits(epochs51)
each of them in six times
but only 12 bits can get mAP higher than the mAP shown in the paper(0.401)
In 32 bits get 0.4599 but paper say the method can get 0.531
and 48 bit get 0.4487 but paper's mAP is 0.558
Is there some setting need to change or how many epochs is prefect ?

Hello,I have the same problem. Have you finally solved it

@zhjy2016
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I try again train the model with 4 epoches for six time but only get mAP in the following table
Bitsnum | 12bits | 24bits | 32bits | 48bits
Codes1 | 0.4748 | 0.4735 | 0.4723 | 0.4606
Codes2 | 0.4308 | 0.4366 | 0.4600 | 0.4632
Codes3 | 0.4341 | 0.4686 | 0.4528 | 0.4399
Codes4 | 0.3941 | 0.4360 | 0.4368 | 0.4782
Codes5 | 0.4284 | 0.4142 | 0.4698 | 0.4822
Codes6 | 0.4911 | 0.4701 | 0.4723 | 0.4480
In 12 bits mAP is good enough, but when bits number goes bigger the mAP still the same
May I ask which tensorflow and prettytensor version you use?

I have this problem, too, how did you solve the problem finally? Could you please share?

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