You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
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
The text was updated successfully, but these errors were encountered:
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 ofsemantic_aug/few_shot_dataset.py
and followed the identical configurations in the official codes. I also noted that the results of different.bin
files fromcustomized-x-y
vary; what doesx
andy
mean? Similarly, I attempted to augment medical images withgenerate_augmentations.py
, setting--embed-path
withlearned_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
The text was updated successfully, but these errors were encountered: