-
Notifications
You must be signed in to change notification settings - Fork 51
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Question about using or-resnet for original --> rot experiments #16
Comments
Hi @dingjiansw101 |
On the construct of my OR-Resnet, I can get a normal accuracy if I do not do random rotation operation on the test set. But when I random rotate the test images, it got low accuracy. Can you give an implementation for pytorch? I am not sure what's wrong with my code. Have you tried to do original --> rot experiments on mnist for resnet or vgg? |
Hi @dingjiansw101,
|
I use the network defined in the demo.py, it is ok to reproduce the similar results for original --> rot experiments on mnist. But when I changed to or-resnet, it got very low results, the accuracy is no more than 50%(even lower than the simple OR-CNN defined in demo.py ). I do not know what's wrong with it. The following is my code.
https://paste.ubuntu.com/p/NssKJbxDqZ/
What's more, when I do original --> rot experiments on cifar-10. I use the network defined in the demo.py. And got results of 35.26 and 44.97 for without/with orn respectively.
Look forward to your reply.
The text was updated successfully, but these errors were encountered: