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custom dataset #64

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lzzlxxlsz opened this issue Mar 29, 2020 · 14 comments
Open

custom dataset #64

lzzlxxlsz opened this issue Mar 29, 2020 · 14 comments

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@lzzlxxlsz
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Hello,I set the same structure of the data ,and the settings:

    self.parser.add_argument('--dataset', default='dfh', help='folder | cifar10 | mnist ')
    self.parser.add_argument('--dataroot', default='.data/dfh/', help='path to dataset')

my dataset name is dfh,and the file of dfh contains two folders : train and test.the train file contains one file of 0 , 0 file include the normal pictures .

However,when I run the train.py ,it turns the error:
FileNotFoundError: [WinError 3] 系统找不到指定的路径。: '.data/dfh/train'

thanks

@Coderxiaobai1
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you do not need to set the default option --dataroot to '.data/dfh' , just let it be ' '.

@Coderxiaobai1
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of course, it depends the generate's input setting. if not , it will never come out of the while loop

@Coderxiaobai1
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In fact, i think it must be a series like [4,8,16,32,64,128,256,512...]

@lzzlxxlsz
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thanks ,another question.If my dataset size is not the multiple of 16,before I train the modle ,should I adjust the dataset size to be the multiple of 16?

In fact, i think it must be a series like [4,8,16,32,64,128,256,512...]
你好,你在自己的数据集上跑通 了吗

@Coderxiaobai1
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there is no need to do that, you can just set --isize to 128 as long as it is smaller than 200.(your dataset)

@lzzlxxlsz
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thanks,how about the result for your dataset?

@Coderxiaobai1
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i haven't done much since i'm still exploring it.

@lzzlxxlsz
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OK,thanks a lot

@Coderxiaobai1
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please let me know if you can run the demo well on your dataset cause i am haunted much these days.😭

@lzzlxxlsz
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I run the train.py but there is nothing display.only the output folder has some loss_log.txt. does it mean runs succussfully?

@Coderxiaobai1
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you can start the visdom server to have a look when in the training process

@Viki-researcher
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you do not need to set the default option --dataroot to '.data/dfh' , just let it be ' '.
hi,why in my train the AUC is always nan,but the train generate picture is not too bad

@Linranran
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@17695996717 because there are only OK or NG samples in the test.

@Linranran
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@17695996717 the test should have the NG and OK samples simultaneously

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