Model card for vit_small_patch14_224.dinobloom
Model Details
Model Usage
Image Embeddings
from urllib.request import urlopen
from PIL import Image
import timm
# get example histology image
img = Image.open(
urlopen(
"https://raw.githubusercontent.com/zxaoyou/segmentation_WBC/master/Dataset%201/001.bmp"
)
)
# load model from the hub
model = timm.create_model(
model_name="hf-hub:1aurent/vit_small_patch14_224.dinobloom",
pretrained=True,
).eval()
# get model specific transforms (normalization, resize)
data_config = timm.data.resolve_model_data_config(model)
transforms = timm.data.create_transform(**data_config, is_training=False)
data = transforms(img).unsqueeze(0) # input is a (batch_size, num_channels, img_size, img_size) shaped tensor
output = model(data) # output is a (batch_size, num_features) shaped tensor
Citation
@misc{koch2024dinobloom,
title = {DinoBloom: A Foundation Model for Generalizable Cell Embeddings in Hematology},
author = {Valentin Koch and Sophia J. Wagner and Salome Kazeminia and Ece Sancar and Matthias Hehr and Julia Schnabel and Tingying Peng and Carsten Marr},
year = {2024},
eprint = {2404.05022},
archivePrefix = {arXiv},
primaryClass = {cs.CV}
}
