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View Code? Open in Web Editor NEWCode for a research paper "Part-Based Models Improve Adversarial Robustness" (ICLR 2023)
Home Page: https://openreview.net/forum?id=bAMTaeqluh4
License: MIT License
Code for a research paper "Part-Based Models Improve Adversarial Robustness" (ICLR 2023)
Home Page: https://openreview.net/forum?id=bAMTaeqluh4
License: MIT License
Currently, args.num_classes
does not need to be set because it is automatically handled in each dataloader. This has not been made explicit.
I downloaded data PartImageNet_Seg, from https://github.com/tacju/partimagenet. After unzipping, the dataset structure is given below:
The link using gdwon doesn't download the dataset, it only downloads the json files for train, val and test.
So,
However, the below function in preparing dataset expects the data to have a subfolder in the JPEGImages:
def get_all_image_names(path):
all_names = glob.glob(f"{path}/JPEGImages/*/*.JPEG")
all_names = [name.split("/")[-1].split(".")[0] for name in all_names]
return set(all_names)
Can you please provide more details regarding data preparation and let me know if I am making any mistake?
Can you please provide clarity on how to reproduce the results shown in the paper using the pre-trained weights:
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