yolo11s_coreml_fp32_auto
Accuracy Evaluation Results
Evaluation Dataset: coco
| Metric | Value |
|---|---|
| mAP@0.5 | 0.505 (50.5%) |
| mAP@0.5:0.95 | 0.382 (38.2%) |
| Precision | 0.441 (44.1%) |
| Recall | 0.204 (20.4%) |
| F1 Score | 0.279 (27.9%) |
| Evaluation FPS | 93.0 |
| Avg Inference Time | 10.75 ms |
These metrics were computed using the Aegis AI evaluation framework on the coco dataset.
This model was automatically converted and uploaded by the Aegis AI Model Conversion Tool.
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from huggingface_hub import hf_hub_download from ultralytics import YOLO # pick the weights file from this repo's "Files and versions" tab weights = hf_hub_download("SharpAI/yolo11s-coreml", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True)