Skip to content
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

Some questions of the testting process in classification tasks #279

Open
crocodilegogogo opened this issue Sep 3, 2020 · 0 comments
Open

Comments

@crocodilegogogo
Copy link

I have a question. We used Deformable Conv in classification tasks. We set the training batchsize the same as im2col_step. During the test process, we put different numbers of test samples in test batch (e.g. test the testing dataset by input one sample per time, or test the testing dataset by inputing ten samples per time), and get different classification results. It seems that how many samples we input to the network each time impacts the final classification results. So why is this happening? Will you kindly give me some advice? What's the relationship between testing batchsize and im2col_step? What's the relationship between training batchsize and im2col_step?

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

1 participant