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--- |
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license: apache-2.0 |
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tags: |
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- object-detection |
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- vision-transformer |
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- coco |
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- faster-rcnn |
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- positional-embeddings |
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- simple-vit |
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datasets: |
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- coco |
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library_name: mmdetection |
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--- |
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# Simple ViT - Object Detection on COCO |
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Faster R-CNN with Simple ViT-Tiny backbone (learned positional embeddings) |
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## Model Details |
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- **Architecture**: Faster R-CNN with ViT-Tiny backbone |
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- **Backbone**: Simple ViT (192-dim, 12 layers, 3 heads) |
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- **Positional Embedding**: SIMPLE |
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- **Training Resolution**: 512x512 |
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- **Dataset**: COCO 2017 |
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- **Framework**: MMDetection |
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## Training Configuration |
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| Parameter | Value | |
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|-----------|-------| |
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| Image Size | 512x512 | |
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| Patch Size | 16x16 | |
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| Hidden Dim | 192 | |
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| Layers | 12 | |
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| Heads | 3 | |
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| MLP Dim | 768 | |
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## Checkpoint Info |
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- **Filename**: `best_coco_bbox_mAP_epoch_12.pth` |
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- **Size**: 114.9 MB |
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- **Epoch**: 12 |
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## Usage |
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```python |
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from mmdet.apis import init_detector, inference_detector |
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config_file = 'detection/configs/faster_rcnn_simple_vit_tiny_coco.py' |
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checkpoint_file = 'best_coco_bbox_mAP_epoch_12.pth' |
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model = init_detector(config_file, checkpoint_file, device='cuda:0') |
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result = inference_detector(model, 'test.jpg') |
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``` |
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## Citation |
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If you use this model, please cite: |
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```bibtex |
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@misc{vit_detection_coco, |
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title={Vision Transformer Object Detection with Simple ViT}, |
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year={2026}, |
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publisher={Hugging Face}, |
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} |
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``` |
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## License |
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Apache 2.0 |
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