---
tags:
- image-classification
- ecology
- fungi
- FGVC
library_name: DanishFungi
license: cc-by-nc-4.0
---
# Model card for BVRA/inception_v4.ft_in1k_df20m_299

## Model Details
- **Model Type:** inception_v4.ft_in1k_df20m_299
- **Model Stats:**
  - Params (M): ??
  - Image size: 299 x 299
- **Papers:**
- **Original:** ??
- **Train Dataset:** DF20M --> 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/inception_v4.ft_in1k_df20m_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