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Thank you very much for your work. I achieved the performance shown in the paper on the AffectNet dataset, but for the RAFDB dataset, I modified some parameters in the config.py to fit the RAFDB dataset, but the best performance was only 83%, which is far from the results in the paper. In addition to some parameters in the config.py that need to be modified, what other areas of the code need to be changed?
ps. I performed the same cropping and alignment operation as the AffectNET dataset on the original version of the RAFDB dataset (i.e. the aligned images not provided by the author) and modified the following parameters: num_classes=7, ramp_a=9/10,
The text was updated successfully, but these errors were encountered:
Sorry, I didn't solve it.发自我的 iPhone在 2023年4月18日,20:18,Arsenever ***@***.***> 写道:
Hi~
Have you solved it? : )
—Reply to this email directly, view it on GitHub, or unsubscribe.You are receiving this because you authored the thread.Message ID: ***@***.***>
Thank you very much for your work. I achieved the performance shown in the paper on the AffectNet dataset, but for the RAFDB dataset, I modified some parameters in the config.py to fit the RAFDB dataset, but the best performance was only 83%, which is far from the results in the paper. In addition to some parameters in the config.py that need to be modified, what other areas of the code need to be changed?
ps. I performed the same cropping and alignment operation as the AffectNET dataset on the original version of the RAFDB dataset (i.e. the aligned images not provided by the author) and modified the following parameters: num_classes=7, ramp_a=9/10,
The text was updated successfully, but these errors were encountered: