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smc
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PANDA_ViT

Image Classification
Transformers
PyTorch
vit
Eval Results (legacy)
Model card Files
xet
 Community
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How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("image-classification", model="smc/PANDA_ViT")
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/hub/parrots.png")
# Load model directly
from transformers import AutoImageProcessor, AutoModelForImageClassification

processor = AutoImageProcessor.from_pretrained("smc/PANDA_ViT")
model = AutoModelForImageClassification.from_pretrained("smc/PANDA_ViT")
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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:

ISUP 1: ISUP 2: ISUP 3: ISUP 4: ISUP 5:

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Evaluation results