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