hi, i have a question about the code

[senlin-ali]

hi,
i see the test.ipynb ,the cls model is no use in the ipynb; and i do not know if it is just train GAN model first(use outlier data and close set data ),and extract features from pretrained model and put in the D model to output value in the test...

[aimerykong]

Hi, thanks for your interest. You are right! The "cls" is the K-way classifier for the closed-set classification. OpenGAN repurposes the off-the-shelf features and learns a discriminator for open-set detection. Therefore, cls does not play a role here.

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On Wed, Nov 3, 2021 at 8:07 AM 1senlin ***@***.***> wrote: hi, i see the test.ipynb ,the cls model is no use in the ipynb; and i do not know if it is just train GAN model first(use outlier data and close set data ),and extract features from pretrained model and put in the D model to output value in the test... — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#5>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABRJSJCFHTKEFZBAVMLU66TUKEQYVANCNFSM5HIYBGTA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.

[senlin-ali]

Hi, thanks for your interest. You are right! The "cls" is the K-way classifier for the closed-set classification. OpenGAN repurposes the off-the-shelf features and learns a discriminator for open-set detection. Therefore, cls does not play a role here.
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On Wed, Nov 3, 2021 at 8:07 AM 1senlin @.***> wrote: hi, i see the test.ipynb ,the cls model is no use in the ipynb; and i do not know if it is just train GAN model first(use outlier data and close set data ),and extract features from pretrained model and put in the D model to output value in the test... — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub <#5>, or unsubscribe https://github.com/notifications/unsubscribe-auth/ABRJSJCFHTKEFZBAVMLU66TUKEQYVANCNFSM5HIYBGTA . Triage notifications on the go with GitHub Mobile for iOS https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675 or Android https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub.

thanku, i have another question, in the paper ,i see the loss should have �open training samples loss, but i do not see this in the code ,is it necessary add this if our training data contains open training samples?

[senlin-ali]

Besides, i try the training demo more than once, i find the same epochs models(for example 60 epoch) have different results (AUC) when i test with the same dataset...

[aimerykong]

Yes, adding open training samples is much better. Please refer to the second last cell for how to do so ( https://github.com/aimerykong/OpenGAN/blob/main/demo_OpenSetSegmentation_training.ipynb ) When you say "the same epochs models have different results", I guess you are referring to the cross-dataset GAN training? Does random initialization affect performance? What are the AUC's you got from your two models?

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On Wed, Nov 3, 2021 at 9:34 AM 1senlin ***@***.***> wrote: Besides, i try the training demo more than once, i find the same epochs models(for example 60 epoch) have different results (AUC) when i test with the same dataset... — You are receiving this because you commented. Reply to this email directly, view it on GitHub <#5 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/ABRJSJBI2WJ6MPFSHNAY6JTUKE26BANCNFSM5HIYBGTA> . Triage notifications on the go with GitHub Mobile for iOS <https://apps.apple.com/app/apple-store/id1477376905?ct=notification-email&mt=8&pt=524675> or Android <https://play.google.com/store/apps/details?id=com.github.android&referrer=utm_campaign%3Dnotification-email%26utm_medium%3Demail%26utm_source%3Dgithub>.