yolo11m_coreml_fp32_auto
Accuracy Evaluation Results
Evaluation Dataset: coco
| Metric | Value |
|---|---|
| mAP@0.5 | 0.549 (54.9%) |
| mAP@0.5:0.95 | 0.424 (42.4%) |
| Precision | 0.488 (48.8%) |
| Recall | 0.259 (25.9%) |
| F1 Score | 0.338 (33.8%) |
| Evaluation FPS | 59.5 |
| Avg Inference Time | 16.79 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/yolo11m-coreml", "<weights>.pt") model = YOLO(weights) source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True)