med-seg-diff-pytorch
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lucidrains
Adding training scripts
@lucidrains Sounds good! Quite a fan of it already. We are mostly done with the script but will integrate accelerate and open a pr
Hi! Thanks for the code! My friend and I are making a training script using this dataset
Thank you very much for your contribution and look forward to your code!
Thanks for the code, I tried to add the training code but the result was not satisfactory.
@Time9Y yup my friend and I are having trouble getting good results too. It kinda works on 64x64 resolution but on 128 it just breaks. I'll try checking the paper for their params
oh this is disappointing
could i have made an error?
they released a public official repository btw
@lucidrains Haha no most likely we screwed up a bit. And sounds good! Will check that out. I'll add our script as a pr in a bit. Just cleaning up since it's a bit messy but maybe we can get your opinion too!
@lucidrains This should be my problem, the code you provided is clean and efficient.
@isamu-isozaki I've seen the code you submitted and it's so cool. Hope I can use it soon!
@isamu-isozaki I've received the code, it's awesome! During training process, how many iterations did you get good results after.
@Time9Y Thanks! For 64x64 around 10 epochs gave me not-too-terrible results. Self-condition is pretty interesting too. Honestly, looking forward to hearing from you if u get good results!
@isamu-isozaki Amazing, I achieved great results in 50 iterations, thanks for your contribution! This code will help our research progress.
@Time9Y Oh awesome! Glad it helped. What parameters did you guys use out of curiosity?
@isamu-isozaki The parameters are basically similar to yours, while referring to this code. https://github.com/WuJunde/MedSegDiff lr 1e-4 eopch 150 batch_size 4 UNet (1, 2, 3, 4) not use ddim
@isamu-isozaki Amazing, I achieved great results in 50 iterations, thanks for your contribution! This code will help our research progress.
great to hear! :pray:
@isamu-isozaki thank you so much for taking the time to contribute the training script!
@lucidrains Np! I wanted to contribute later to your muse repo so this was a bit of a practice run. And also, @dsbuddy helped a lot.
@lucidrains Sry, found a slight bug in training but made pr to fix it!