Comments (2)
For example, do I take the directories from each patch, turn them into json files, and then store them with "from webdataset import TarWriter"? I am trying to figure out how the information is stored.
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You do not need to turn the images into a *.tar format for WebDataset. Originally, all 400K-ish [4096 × 4096] images were saved in a WebDataset format, to prevent reading directly from Openslide. However, like CLAM, its much easier to just extract features directly from the WSI rather than to 1) save the image patch, then 2) extract features.
How are you extracting features? I would modify the CLAM feature extraction pipeline to directly use HIPT_4K for feature extraction of specified 4096 x 4096 patches.
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Related Issues (20)
- Some Questions HOT 1
- Getting raw patches after CLAM preprocessing HOT 5
- Issue with Attention Visualization HOT 2
- Some questions HOT 1
- Stochastic behavior when extracting the features for one image HOT 4
- Number of epochs required for finetuning HOT 1
- 'Weakly-Supervised Training' task - Issue with fast_cluster_ids.pkl file HOT 2
- Process of training subtyping task on custom WSIs dataset using provided pretrained model HOT 2
- cannot load pretrained model weights HOT 2
- Pretrained ViTWSI-4096 model HOT 2
- Recommended GPUs HOT 2
- Worse Performance in CAMELYON16 only
- Worse Performance in CAMELYON16 only HOT 5
- How can I get ’vits_tcga_pancancer_dino_pt_patch_features‘? HOT 1
- WSI preprocessing HOT 5
- Batch-wise extract features HOT 3
- Extracting features from 4096 x 4096 patches (M x L x D)
- Using the Features in CLAM HOT 2
- name 'get_patch_attention_scores' is not defined HOT 1
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