Open dressedanonymous opened 2 years ago
Thanks for publishing a very useful model and sample code. We've been using your "Face Portrait v2 model" in our experimental NFT project mypfp.io, an anime-like NFT avatar generator service. Since it was implemented in PyTorch, we were able to quickly develop an API using Flask.
We've put a sample video on mypfp.io for you to play with if you want and we would be happy if you could add some collaboration projects section on the README.md.
Thanks!
mypfp.io NFT minted in the video mypfp_short.mp4
You sure license allows that?
there is no training code available in this repo -> you didn't train anything yourself and just used weights trained on dataset you didn't own or even saw, and most likely is original animegan2 dataset. original animegan2 and it's dataset is "for non-commercial purposes such as academic research, teaching, scientific publications." as written on project page.
About Face Portrait v2 model, it says they used training sets prepared by themselves to derive weights and publish its weight and model under the MIT license. It is not related to the original project.
there is no proof of their words since dataset and train code are not provided, and results (weights) cant be replicated.
Have you ever checked original datasets? Anyone who has studied machine learning even a little bit can easily imagine how difficult it would be to create such a portrait-specific model from the original data set.
ha, have YOU seen datasets weights you used was trained on? was able to reproduce the weights with ~same result thus claims of author are believable true? So far it looks like model is trained on random googled images/movies with zero respect to rights, and author claims "all ok it is mit" while providing zero proof
If you feel that way, then why don't you just not use it yourself?
I'm actually curious what the authors of this repository intended with the license. My non-legal interpretation is that the MIT license would include the weights, but I'd like to here from the repo owner themselves.
My understanding is that the copyright and licensing associated with a dataset need not necessarily apply to the model and consecutive generated outputs. Working with separate licenses for the code, datasets, weights and outputs can be incredibly confusing, and it's fair to say that it's up in the air.
This could be really interesting. I think such someone will be interested in NFT Avatars. If someone is looking for an answer whether it is worth investing in nft avatars, I highly recommend this post: https://gamerseo.com/blog/are-nft-avatars-worth-the-hype-around-them/
Thanks for publishing a very useful model and sample code. We've been using your "Face Portrait v2 model" in our experimental NFT project mypfp.io, an anime-like NFT avatar generator service. Since it was implemented in PyTorch, we were able to quickly develop an API using Flask.
We've put a sample video on mypfp.io for you to play with if you want and we would be happy if you could add some collaboration projects section on the README.md.
Thanks!
mypfp.io NFT minted in the video
https://user-images.githubusercontent.com/94442111/141962737-b5d1ad1f-9729-447f-b9fa-c82ce5b27972.mp4