benchmarks added
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README.md
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@@ -32,6 +32,23 @@ The model's weights can be found [here](./yolo11x_urchin_trained.pt) | Also avai
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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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- Post-processed video/imagery for detecting sea urchins in underwater environments
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- **[PyTorch (best.pt)](./train/weights/best.pt)**: Standard format for PyTorch-based applications.
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## Benchmarks
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|index|Format|Status❔|Size \(MB\)|metrics/mAP50-95\(B\)|Inference time \(ms/im\)|FPS|
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|---|---|---|---|---|---|---|
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|0|PyTorch|✅|38\.7|0\.5694|23\.69|42\.21|
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|1|TorchScript|✅|77\.1|0\.5619|21\.34|46\.86|
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|2|ONNX|❎|76\.7|NaN|NaN|NaN|
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|3|OpenVINO|❌|0\.0|NaN|NaN|NaN|
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|4|TensorRT|✅|86\.4|0\.5619|20\.72|48\.27|
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|5|CoreML|❌|0\.0|NaN|NaN|NaN|
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|6|TensorFlow SavedModel|✅|193\.1|0\.5619|40\.84|24\.48|
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|7|TensorFlow GraphDef|✅|76\.8|0\.5619|38\.65|25\.88|
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|11|PaddlePaddle|✅|153\.4|0\.5619|30\.63|32\.65|
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|12|MNN|✅|76\.6|0\.5615|1133\.73|0\.88|
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|13|NCNN|✅|76\.6|0\.5619|1068\.97|0\.94|
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|14|IMX|❌|0\.0|NaN|NaN|NaN|
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|15|RKNN|❌|0\.0|NaN|NaN|NaN|
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# Intended Use
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- Real-time detections on underwater footage
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- Post-processed video/imagery for detecting sea urchins in underwater environments
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