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A Swin-B image feature model. Supervisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 109.1 - Image size: 224 x 224 - Architecture: swin_base_patch4_window7_224 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows - DINOv2: Learning Robust Visual Features without Supervision - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗A CLIP based image feature model. Supervisely pre-trained on animal re-identification datasets. Original model: timm/vit_large_patch14_clip_336.openai_ft_in12k_in1k
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View details ↗A DINOv2 based image feature model. Supervisely pre-trained on animal re-identification datasets. Original model: timm/vit_large_patch14_dinov2.lvd142m - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 304.4 - GMACs: 507.1 - Activations (M): 1058.8 - Image size: 518 x 518
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View details ↗A Swin-L image feature model. Supervisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 228.6 - Image size: 224 x 224 - Architecture: swin_large_patch4_window7_224 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows - DINOv2: Learning Robust Visual Features without Supervision - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗A Swin-L image feature model. Superwisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 228.8 - Image size: 384 x 384 - Architecture: swin_large_patch4_window12_384 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows - DINOv2: Learning Robust Visual Features without Supervision - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗A Swin-S image feature model. Supervisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 49.6 - Image size: 224 x 224 - Architecture: swin_small_patch4_window7_224 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows - DINOv2: Learning Robust Visual Features without Supervision - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗A Swin-T image feature model. Superwisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Params (M): 28.3 - Image size: 224 x 224 - Architecture: swin_tiny_patch4_window7_224 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - Swin Transformer: Hierarchical Vision Transformer using Shifted Windows - DINOv2: Learning Robust Visual Features without Supervision - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗A EfficientNetB3 based image feature model. Supervisely pre-trained on animal re-identification datasets. - **Model Type:** Animal re-identification / feature backbone - **Model Stats:** - Architecture: EfficientNetB3 - Params (M): 12.2 - GMACs: 1.6 - Activations (M): 21.5 - Image size: 288 x 288 - **Paper:** WildlifeDatasets_An_Open-Source_Toolkit_for_Animal_Re-Identification - **Related Papers:** - EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks - **Pretrain Dataset:** All available re-identification datasets --> https://github.com/WildlifeDatasets/wildlife-datasets
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View details ↗--- tags: - image-classification - ecology - fungi - FGVC library_name: DanishFungi license: cc-by-nc-4.0 ---
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View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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View details ↗TurtleDetector
BVRA基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
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