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| tags: | |
| - image-classification | |
| - ecology | |
| - fungi | |
| - FGVC | |
| library_name: DanishFungi | |
| license: cc-by-nc-4.0 | |
| # Model card for BVRA/vit_large_patch16_384.ft_df20m_384 | |
| ## Model Details | |
| - **Model Type:** Danish Fungi Classification | |
| - **Model Stats:** | |
| - Params (M): 303.9M | |
| - Image size: 384 x 384 | |
| - **Papers:** | |
| - **Original:** An image is worth 16x16 words: Transformers for image recognition at scale --> https://arxiv.org/pdf/2010.11929 | |
| - **Train Dataset:** DF20 --> https://github.com/BohemianVRA/DanishFungiDataset/ | |
| ## 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/vit_large_patch16_384.ft_df20m_384", pretrained=True) | |
| model = model.eval() | |
| train_transforms = T.Compose([T.Resize((384, 384)), | |
| 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 a (1, num_features) shaped tensor | |
| ``` | |
| ## Citation | |
| ```bibtex | |
| @InProceedings{Picek_2022_WACV, | |
| author = {Picek, Lukas and Sulc, Milan and Matas, Jiri 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} | |
| } | |
| @article{picek2022automatic, | |
| title={Automatic Fungi Recognition: Deep Learning Meets Mycology}, | |
| author={Picek, Lukas and Sulc, Milan and Matas, Jiri 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} | |
| } | |
| ``` | |