yolo12n_coreml_fp32_auto
Accuracy Evaluation Results
Evaluation Dataset: coco
| Metric | Value |
|---|---|
| mAP@0.5 | 0.431 (43.1%) |
| mAP@0.5:0.95 | 0.322 (32.2%) |
| Precision | 0.375 (37.5%) |
| Recall | 0.137 (13.7%) |
| F1 Score | 0.201 (20.1%) |
| Evaluation FPS | 89.1 |
| Avg Inference Time | 11.22 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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# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("SharpAI/yolo12n-coreml") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True)