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--- |
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tags: |
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- image-classification |
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- ecology |
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- animals |
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- re-identification |
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library_name: wildlife-datasets |
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license: cc-by-nc-4.0 |
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--- |
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# Model card for MegaDescriptor-L-224 |
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A Swin-L image feature model. Supervisely pre-trained on animal re-identification datasets. |
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## Model Details |
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- **Model Type:** Animal re-identification / feature backbone |
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- **Model Stats:** |
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- Params (M): 228.6 |
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- Image size: 224 x 224 |
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- Architecture: swin_large_patch4_window7_224 |
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- **Paper:** [WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification](https://openaccess.thecvf.com/content/WACV2024/html/Cermak_WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification_WACV_2024_paper.html) |
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- **Related Papers:** |
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- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://arxiv.org/abs/2103.14030) |
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- [DINOv2: Learning Robust Visual Features without Supervision](https://arxiv.org/pdf/2304.07193.pdf) |
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- **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets |
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## Model Usage |
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### Image Embeddings |
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```python |
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import timm |
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import torch |
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import torchvision.transforms as T |
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from PIL import Image |
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from urllib.request import urlopen |
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model = timm.create_model("hf-hub:BVRA/MegaDescriptor-L-224", pretrained=True) |
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model = model.eval() |
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train_transforms = T.Compose([T.Resize(224), |
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T.ToTensor(), |
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T.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5])]) |
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img = Image.open(urlopen( |
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'https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/beignets-task-guide.png' |
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)) |
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output = model(train_transforms(img).unsqueeze(0)) # output is (batch_size, num_features) shaped tensor |
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# output is a (1, num_features) shaped tensor |
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``` |
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## Citation |
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```bibtex |
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@inproceedings{vcermak2024wildlifedatasets, |
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title={WildlifeDatasets: An open-source toolkit for animal re-identification}, |
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author={{\v{C}}erm{\'a}k, Vojt{\v{e}}ch and Picek, Lukas and Adam, Luk{\'a}{\v{s}} and Papafitsoros, Kostas}, |
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booktitle={Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision}, |
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pages={5953--5963}, |
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year={2024} |
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} |
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``` |