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

Details on quantitative results #432

Open
HoiM opened this issue Oct 8, 2024 · 3 comments
Open

Details on quantitative results #432

HoiM opened this issue Oct 8, 2024 · 3 comments

Comments

@HoiM
Copy link

HoiM commented Oct 8, 2024

Thank you for your work. When calculating CLIP-I and CLIP-T, did you use text prompt as an input into the model? Is the image prompt the only input?

@xiaohu2015
Copy link
Collaborator

coco dataset have text captions

@HoiM
Copy link
Author

HoiM commented Oct 11, 2024

coco dataset have text captions

I know it has captions. What I plan to do is to conduct same evaluation with my own IP-Adapter.

I don't know if I should use text prompt when the model generates image samples.

@greasebig
Copy link

greasebig commented Feb 8, 2025

@xiaohu2015 hi, some questions about paper.

1.in your paper, says "we generate 4 images conditioned on the image prompt for each sample in the dataset, resulting in total 20,000 generated images for each method", did you generate 4 different images by different seed? or different captions?

2.when you got quantitative results, do your generated images have the same size with each validate coco image? (like width=600, height=400, same with coco eval annotations)

Would you be willing to provide the code for validating the quantitative indicators to other researchers?

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

3 participants