readme: ---
  tags:
  - image-classification
  - pytorch
  metrics:
  - accuracy
  - Cohen's Kappa
  
  model-index:
  - name: PANDA_ViT
    results:
    - task:
        name: Image Classification
        type: image-classification
      metrics:
        - name: Accuracy
          type: accuracy
          value: 0.47959184646606445
        - name: Quadratic Cohen's Kappa
          type:  Quadratic Cohen's Kappa
          value: 0.5590880513191223
  ---
  
  # PANDA_ViT
  
  An attempt to use a ViT for medical image classification (ISUP grading in prostate histopathology images). Currently uses a tiled and concatenated WSI as input
  
  Example Images (1152,1152,3) 36 WSI patches: 
  
  
  
  ISUP 0:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/0c02d3bb3a62519b31c63d0301c6843e_0.jpeg">
  
  ISUP 1:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/0cee71ab57422e04f76e09ef2186fcd5_1.jpeg">
  ISUP 2:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/00bbc1482301d16de3ff63238cfd0b34_2.jpeg">
  ISUP 3:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/0c5c2d16c0f2e399b7be641e7e7f66d9_3.jpeg">
  ISUP 4:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/0c88d7c7033e2048b1068e208b105270_4.jpeg">
  ISUP 5:
  <img width="256" height="256" src="https://huggingface.co/smc/PANDA_ViT/resolve/main/00c15b23b30a5ba061358d9641118904_5.jpeg">