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--- |
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license: etalab-2.0 |
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pipeline_tag: object-detection |
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base_model: Ultralytics/YOLO11 |
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--- |
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This model has be trained for the Panoramax project in order to detect: |
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- people face to blur them |
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- licence plates to blur them |
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- road signs to classify them with other models |
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The last model has been trained on yolo11l with imgsz of 2048 and 300 epochs, the older one on yolo8s. |
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Here is the last run validation : |
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``` |
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Validating runs/detect/train5/weights/best.pt... |
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Ultralytics 8.3.29 🚀 Python-3.12.3 torch-2.5.1+cu124 CUDA:0 (NVIDIA GeForce RTX 4090, 24207MiB) |
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YOLO11l summary (fused): 464 layers, 25,281,625 parameters, 0 gradients, 86.6 GFLOPs |
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Class Images Instances Box(P R mAP50 mAP50-95): 100%|██████████| 83/83 [00:08<00:00, 9.78it/s] |
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all 329 1209 0.812 0.768 0.815 0.412 |
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sign 231 507 0.879 0.836 0.898 0.561 |
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plate 202 410 0.833 0.849 0.889 0.438 |
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face 118 292 0.724 0.619 0.657 0.237 |
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Speed: 1.2ms preprocess, 18.4ms inference, 0.0ms loss, 1.6ms postprocess per image |
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``` |
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