Upload README.md with huggingface_hub

README.md

@@ -5,19 +5,19 @@ tags:
 - ecology
 - fungi
 - FGVC
-library_name: DanishFungi
+library_name: FungiTastic Dataset
 license: cc-by-nc-4.0
 ---
-# Model card for BVRA/vit_base_patch16_384.in1k_ft_df24_384
+# Model card for BVRA/vit_base_patch16_384.in1k_ft_fungitastic_384
 
 ## Model Details
-- **Model Type:** Danish Fungi Classification 
+- **Model Type:** Fine-grained classification of fungi species
 - **Model Stats:**
   - Params (M): 88.3
   - Image size: 384 x 384
 - **Papers:**
-- **Original:** ??
-- **Train Dataset:** DF24 --> https://sites.google.com/view/danish-fungi-dataset
+  - **Original:** --> ???
+  - **Train Dataset:** FungiTastic --> https://arxiv.org/pdf/2408.13632
 
 ## Model Usage
 ### Image Embeddings
@@ -27,7 +27,7 @@ import torch
 import torchvision.transforms as T
 from PIL import Image
 from urllib.request import urlopen
-model = timm.create_model("hf-hub:BVRA/vit_base_patch16_384.in1k_ft_df24_384", pretrained=True)
+model = timm.create_model("hf-hub:BVRA/vit_base_patch16_384.in1k_ft_fungitastic_384", pretrained=True)
 model = model.eval()
 train_transforms = T.Compose([T.Resize((384, 384)), 
                               T.ToTensor(), 
@@ -39,6 +39,14 @@ output = model(train_transforms(img).unsqueeze(0))
 
 ## Citation 
 ```bibtex
+@article{picek2024fungitastic,
+  title={FungiTastic: A multi-modal dataset and benchmark for image categorization},
+  author={Picek, Lukas and Janouskova, Klara and Sulc, Milan and Matas, Jiri},
+  journal={arXiv preprint arXiv:2408.13632},
+  year={2024}
+}
+```
+```bibtex
 @InProceedings{Picek_2022_WACV,
     author    = {Picek, Luk'a{s} and {S}ulc, Milan and Matas, Ji{r}{'\i} and Jeppesen, Thomas S. and Heilmann-Clausen, Jacob and L{e}ss{\o}e, Thomas and Fr{\o}slev, Tobias},
     title     = {Danish Fungi 2020 - Not Just Another Image Recognition Dataset},