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# Glove Labelling Model (SAM 2.1 Fine-Tuned) |
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This model is a fine-tuned [Segment Anything Model (SAM 2.1)](https://github.com/facebookresearch/segment-anything) designed specifically for **baseball glove segmentation**. It identifies fine-grained regions on a pitcherโs glove from video frames, with the goal of analyzing glove position, shape, and movement across pitches. |
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## ๐ Model Details |
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- **Architecture**: SAM 2.1 Hiera-L variant |
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- **Framework**: PyTorch |
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- **Training Type**: Image-only fine-tuning on custom glove segmentation data |
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- **Losses**: Dice, IoU, and mask loss |
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- **Epochs**: 50 |
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- **Batch Size**: 2 |
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- **Dataset**: Custom COCO-format sequences of glove mask annotations split by pitch |
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## ๐ท๏ธ Labels (Classes) |
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This model supports six segmentation classes: |
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- `glove_outline` |
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- `webbing` |
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- `thumb` |
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- `palm_pocket` |
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- `hand` |
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- `glove_exterior` |
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## ๐ Files in This Repo |
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| File | Description | |
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| `pytorch_model.bin` | Trained PyTorch weights (`.pt` file) | |
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| `config.json` | Model and dataset configuration | |
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| `README.md` | You're reading it | |
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## ๐ Deployment Options |
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You can deploy this model using: |
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- **Google Cloud Vertex AI** (via Model Garden) |
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- **TorchServe** |
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- **CVAT** (via a custom segmentation model) |
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- **Hugging Face Inference Endpoints** (manual handler required) |
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## ๐ Author |
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Created and maintained by [`caball21`](https://huggingface.co/caball21) |
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Please cite if used in academic or production applications. |
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