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StainNet-Base is a foundation model for histology images from immunohistochemistry and special stains. Arxiv preprint paper: [https://arxiv.org/abs/2512.10326]1import timm
2import torch
3import torchvision.transforms as transforms
4
5
6model = timm.create_model('hf_hub:JWonderLand/StainNet-Base', pretrained=True)
7
8preprocess = transforms.Compose([
9 transforms.Resize(224, interpolation=transforms.InterpolationMode.BICUBIC),
10 transforms.ToTensor(),
11 transforms.Normalize(mean=(0.5, 0.5, 0.5), std=(0.5, 0.5, 0.5)),
12 ])
13
14model = model.to('cuda')
15model.eval()
16
17input = torch.randn([1, 3, 224, 224]).cuda()
18
19with torch.no_grad():
20 output = model(input) # [1, 768]StainNet-Base is helpful to you, please cite our work.@misc{li2025stainnet,
title={StainNet: A Special Staining Self-Supervised Vision Transformer for Computational Pathology},
author={Jiawen Li and Jiali Hu and Xitong Ling and Yongqiang Lv and Yuxuan Chen and Yizhi Wang and Tian Guan and Yifei Liu and Yonghong He},
year={2025},
eprint={2512.10326},
archivePrefix={arXiv},
primaryClass={cs.CV},
url={https://arxiv.org/abs/2512.10326},
}