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README.md
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@@ -31,10 +31,6 @@ This model was trained to detect sea urchins using the YOLO11 architecture. Trai
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The model's weights can be found [here](./yolo11x_urchin_trained.pt) | Also available in various formats:
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- **[PyTorch (best.pt)](./train/weights/best.pt)**: Standard format for PyTorch-based applications.
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- **[Latest PyTorch Checkpoint (last.pt)](./train/weights/last.pt)**: The latest checkpoint from training.
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- **[ONNX (best.onnx)](./train/weights/best.onnx)**: ForONNX runtime.
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- **[TorchScript (best.torchscript)](./train/weights/best.torchscript)**
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- **[NCNN](./train/weights/best_ncnn_model/model.ncnn.bin)**: Efficient for mobile platforms and embedded systems.
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# Intended Use
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- Real-time detections on underwater footage
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The model's weights can be found [here](./yolo11x_urchin_trained.pt) | Also available in various formats:
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- **[PyTorch (best.pt)](./train/weights/best.pt)**: Standard format for PyTorch-based applications.
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# Intended Use
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- Real-time detections on underwater footage
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