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---
tags:
- image-classification
- ecology
- fungi
- FGVC
library_name: DanishFungi
license: cc-by-nc-4.0
---
# Model card for BVRA/legacy_seresnext101_32x4d.in1k_ft_df20_384
## Model Details
- **Model Type:** Danish Fungi Classification
- **Model Stats:**
- Params (M): ??
- Image size: 384 x 384
- **Papers:**
- **Original:** ??
- **Train Dataset:** DF20 --> https://sites.google.com/view/danish-fungi-dataset
## Model Usage
### Image Embeddings
```python
import timm
import torch
import torchvision.transforms as T
from PIL import Image
from urllib.request import urlopen
model = timm.create_model("hf-hub:BVRA/legacy_seresnext101_32x4d.in1k_ft_df20_384", pretrained=True)
model = model.eval()
train_transforms = T.Compose([T.Resize((384, 384)),
T.ToTensor(),
T.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225])])
img = Image.open(PATH_TO_YOUR_IMAGE)
output = model(train_transforms(img).unsqueeze(0))
# output is a (1, num_features) shaped tensor
```
## Citation
```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},
booktitle = {Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
month = {January},
year = {2022},
pages = {1525-1535}
}
```
```bibtex
@article{picek2022automatic,
title={Automatic Fungi Recognition: Deep Learning Meets Mycology},
author={Picek, Luk{'a}{ {s}} and { {S}}ulc, Milan and Matas, Ji{ {r}}{'\i} and Heilmann-Clausen, Jacob and Jeppesen, Thomas S and Lind, Emil},
journal={Sensors},
volume={22},
number={2},
pages={633},
year={2022},
publisher={Multidisciplinary Digital Publishing Institute}
}
```
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