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怎么训练自己的数据呢 #3

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chunleiml opened this issue Apr 28, 2020 · 15 comments
Open

怎么训练自己的数据呢 #3

chunleiml opened this issue Apr 28, 2020 · 15 comments

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@chunleiml
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@Tianxiaomo
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目前还不支持,后续会加上的

可以大家一起实现

@17868380981
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我也在研究这个,我的微信17868380981,可以一起搞嘛

@abhigoku10
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@Tianxiaomo when can we expect the support code to train ??

@weidaolee
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我最近需要用在自己的data上,希望能參與開發。qq: 2379467558

Repository owner deleted a comment from QQ2737499951 May 9, 2020
@Tianxiaomo
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@chunleiml 应该可以训练

@ckcraig01
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@Tianxiaomo
Dear Author, thank you very much for the great work. I suppose you are working on training and reproducing the performance of original repo. When you are done, may you release the training flow? btw, Pytorch is great~ Thanks again

@17868380981
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17868380981 commented May 14, 2020 via email

@Tianxiaomo Tianxiaomo pinned this issue May 14, 2020
@Tianxiaomo Tianxiaomo unpinned this issue May 14, 2020
@Weifeng-Chen
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@chunleiml 应该可以训练

可以写一下怎么训练吗? 有哪些需要改动的?

@okideal
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okideal commented May 19, 2020

我魔改了一下可以支持自己的数据了,训练了几十个epoch后输出的框不太正确,作者大大能帮忙看下么 @Tianxiaomo

@Tianxiaomo
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什么问题,都不正确,还是有不正确的 @okideal

@okideal
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okideal commented May 19, 2020

什么问题,都不正确,还是有不正确的 @okideal

都不正确,而且相邻epoch保存的checkpoint输出的结果都相差很大,框都是散布在图片上的,没有规律。

@okideal
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okideal commented May 19, 2020

2020-05-19 09:41:24,363 train.py[line:317] DEBUG: Train step_252232: loss : 1.4532806873321533,loss xy : 12.427532196044922,loss wh : 1.475596308708191,loss obj : 6.721678256988525,loss cls : 2.627683162689209,loss l2 : 5.853010177612305
2020-05-19 09:41:28,438 train.py[line:317] DEBUG: Train step_252252: loss : 0.5830423831939697,loss xy : 4.975176811218262,loss wh : 0.122866690158844,loss obj : 4.1869707107543945,loss cls : 0.043664395809173584,loss l2 : 1.4445288181304932
2020-05-19 09:41:32,533 train.py[line:317] DEBUG: Train step_252272: loss : 1.1059558391571045,loss xy : 9.491128921508789,loss wh : 0.018527325242757797,loss obj : 1.4653393030166626,loss cls : 6.720297813415527,loss l2 : 2.798774480819702
2020-05-19 09:41:36,753 train.py[line:317] DEBUG: Train step_252292: loss : 0.7335749268531799,loss xy : 6.689797878265381,loss wh : 0.04984629526734352,loss obj : 4.740152359008789,loss cls : 0.2574022710323334,loss l2 : 1.7148456573486328
2020-05-19 09:41:40,661 train.py[line:317] DEBUG: Train step_252312: loss : 1.0617437362670898,loss xy : 14.04965877532959,loss wh : 0.08109669387340546,loss obj : 2.62939453125,loss cls : 0.22774934768676758,loss l2 : 0.8850184082984924
2020-05-19 09:41:44,627 train.py[line:317] DEBUG: Train step_252332: loss : 1.2092291116714478,loss xy : 8.662763595581055,loss wh : 0.019287779927253723,loss obj : 2.9575741291046143,loss cls : 7.708040237426758,loss l2 : 2.6127541065216064
2020-05-19 09:41:48,755 train.py[line:317] DEBUG: Train step_252352: loss : 0.8405617475509644,loss xy : 8.541584014892578,loss wh : 0.032777439802885056,loss obj : 4.75701904296875,loss cls : 0.11760733276605606,loss l2 : 1.3595856428146362
2020-05-19 09:41:52,804 train.py[line:317] DEBUG: Train step_252372: loss : 0.3742732107639313,loss xy : 4.4370269775390625,loss wh : 0.017715638503432274,loss obj : 1.478102445602417,loss cls : 0.055526264011859894,loss l2 : 0.43905097246170044
2020-05-19 09:41:56,729 train.py[line:317] DEBUG: Train step_252392: loss : 1.0849196910858154,loss xy : 11.690910339355469,loss wh : 0.05718810483813286,loss obj : 3.792856216430664,loss cls : 1.8177597522735596,loss l2 : 1.5996325016021729
训练的时候loss震荡也很大,这算正常的么?

@Tianxiaomo
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2020-05-19 09:41:24,363 train.py[line:317] DEBUG: Train step_252232: loss : 1.4532806873321533,loss xy : 12.427532196044922,loss wh : 1.475596308708191,loss obj : 6.721678256988525,loss cls : 2.627683162689209,loss l2 : 5.853010177612305
2020-05-19 09:41:28,438 train.py[line:317] DEBUG: Train step_252252: loss : 0.5830423831939697,loss xy : 4.975176811218262,loss wh : 0.122866690158844,loss obj : 4.1869707107543945,loss cls : 0.043664395809173584,loss l2 : 1.4445288181304932
2020-05-19 09:41:32,533 train.py[line:317] DEBUG: Train step_252272: loss : 1.1059558391571045,loss xy : 9.491128921508789,loss wh : 0.018527325242757797,loss obj : 1.4653393030166626,loss cls : 6.720297813415527,loss l2 : 2.798774480819702
2020-05-19 09:41:36,753 train.py[line:317] DEBUG: Train step_252292: loss : 0.7335749268531799,loss xy : 6.689797878265381,loss wh : 0.04984629526734352,loss obj : 4.740152359008789,loss cls : 0.2574022710323334,loss l2 : 1.7148456573486328
2020-05-19 09:41:40,661 train.py[line:317] DEBUG: Train step_252312: loss : 1.0617437362670898,loss xy : 14.04965877532959,loss wh : 0.08109669387340546,loss obj : 2.62939453125,loss cls : 0.22774934768676758,loss l2 : 0.8850184082984924
2020-05-19 09:41:44,627 train.py[line:317] DEBUG: Train step_252332: loss : 1.2092291116714478,loss xy : 8.662763595581055,loss wh : 0.019287779927253723,loss obj : 2.9575741291046143,loss cls : 7.708040237426758,loss l2 : 2.6127541065216064
2020-05-19 09:41:48,755 train.py[line:317] DEBUG: Train step_252352: loss : 0.8405617475509644,loss xy : 8.541584014892578,loss wh : 0.032777439802885056,loss obj : 4.75701904296875,loss cls : 0.11760733276605606,loss l2 : 1.3595856428146362
2020-05-19 09:41:52,804 train.py[line:317] DEBUG: Train step_252372: loss : 0.3742732107639313,loss xy : 4.4370269775390625,loss wh : 0.017715638503432274,loss obj : 1.478102445602417,loss cls : 0.055526264011859894,loss l2 : 0.43905097246170044
2020-05-19 09:41:56,729 train.py[line:317] DEBUG: Train step_252392: loss : 1.0849196910858154,loss xy : 11.690910339355469,loss wh : 0.05718810483813286,loss obj : 3.792856216430664,loss cls : 1.8177597522735596,loss l2 : 1.5996325016021729
训练的时候loss震荡也很大,这算正常的么?

数据增强原来有bug,另外学习率在训练时有没有调整

@okideal
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okideal commented May 19, 2020

数据增强之前我把mosaic关掉了,只用了普通的增强。学习率的话,adam自己也会调整把,只是不会指数衰减

@moonlightian
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我魔改了一下可以支持自己的数据了,训练了几十个epoch后输出的框不太正确,作者大大能帮忙看下么 @Tianxiaomo

大佬可以分享一下魔改方法嘛,最近也想在bdd100k上训练一版pytorch-v4

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