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