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---
tags:
- image-classification
- ecology
- fungi
- FGVC
library_name: DanishFungi
license: cc-by-nc-4.0
---
# Model card for BVRA/DF23M-resnet34.a1_in1k-299
## Model Details
- **Model Type:** resnet34.a1_in1k
- **Model Stats:**
- Params (M): ??
- Image size: 299 x 299
- **Papers:**
- **Original:** ??
- **Train Dataset:** DF23M --> 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/DF23M-resnet34.a1_in1k-299", pretrained=True)
model = model.eval()
train_transforms = T.Compose([T.Resize(299),
T.ToTensor(),
T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])])
img = Image.open(PATH_TO_YOUR_IMAGE)
output = model(train_transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor
# output is a (1, num_features) shaped tensor
```
## Citation
https://openaccess.thecvf.com/content/WACV2022/papers/Picek_Danish_Fungi_2020_-_Not_Just_Another_Image_Recognition_Dataset_WACV_2022_paper.pdf
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