-
Notifications
You must be signed in to change notification settings - Fork 40
Hello, how to finetune own datasets #11
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
Comments
@wudizuixiaosa You just need to write your own Dataset Class in datasets.py. Also, don't forget change the data_path and nb_classes in args of main_finetune.py. |
Thank you for your reply. I know that we can change the data_path and class in finetune..py. I've also seen dataset.py project, but I see that the settings in it are based on Imagenet. As I am a beginner, my foundation is not good, and I am very interested in your project. So can you give me an example? Let's assume that there are two kinds of dogs and cats in my dataset. How can I define them? Mainly, I don't see relevant parameter settings in the project. |
By the way, which format of dataset should i choose,coco,voc or Unlabeled pictures in folders of corresponding categories? |
Please follow the dataset format of Imagenet. Basically, you can need to build two folders named dog and cat then put images into the corresponding folder. |
Oh, thank you for replying so quickly,i am coming to try it now |
train The folder structure is similar to the above illustration. |
What should I do if I want to fine tune the current pre training model to my own dataset instead of Imagenet's Val dataset? Can you answer it? Thank you very much
The text was updated successfully, but these errors were encountered: