brandontrabucco / da-fusion

Effective Data Augmentation With Diffusion Models
MIT License
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The ability to generate medical images #21

Open yo3nglau opened 8 months ago

yo3nglau commented 8 months ago

Hello @brandontrabucco ,

Thanks for your reputed work.

I have reproduced the plausible outcomes of generation on the Pascal dataset. Can we generate/augment medical images that distinguish a lot from common/natural images? I have fine-tuned DA-Fusion with the customized medical dataset; notwithstanding, over-fancy results are produced by executing generating_images.py, which is impossible for augmentation. Specifically, I built the dataset as a subclass of semantic_aug/few_shot_dataset.py and followed the identical configurations in the official codes. I also noted that the results of different .bin files from customized-x-y vary; what does x and y mean? Similarly, I attempted to augment medical images with generate_augmentations.py, setting --embed-path with learned_embeds.bin derived from fine-tuning operations mentioned above. I feel it is an inappropriate trial because of the default setting of ***.pt, which I have no idea to obtain thus far. In short, I have a customized medical dataset and corresponding labels and intend to achieve favorable augmentations with DA-Fusion thanks to its image-image generation.

I would appreciate any guidance or suggestions.

Best, Young

Parsa744 commented 3 months ago

Dear Young, Can you share your work with us? best Parsa