Instructions to use CodexParas/car-plate-detection-yolov26 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use CodexParas/car-plate-detection-yolov26 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("CodexParas/car-plate-detection-yolov26") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| epoch,time,train/box_loss,train/cls_loss,train/dfl_loss,metrics/precision(B),metrics/recall(B),metrics/mAP50(B),metrics/mAP50-95(B),val/box_loss,val/cls_loss,val/dfl_loss,lr/pg0,lr/pg1,lr/pg2 | |
| 1,40.9929,1.50541,11.6474,0.01184,0.00192,0.51546,0.13266,0.05836,1.16886,8.04946,0.00819,0.00042,0.00042,0.00042 | |
| 2,46.4466,1.3285,9.55611,0.00923,0.00241,0.64948,0.16799,0.0988,1.06909,7.676,0.00797,0.00077486,0.00077486,0.00077486 | |
| 3,51.8508,1.3501,8.07471,0.00971,0.0033,0.8866,0.25783,0.11942,1.1623,7.5122,0.00906,0.0010426,0.0010426,0.0010426 | |
| 4,57.9865,1.37409,7.12699,0.0104,0.83354,0.34021,0.62641,0.28218,1.35971,6.75253,0.00999,0.00122322,0.00122322,0.00122322 | |
| 5,64.1604,1.37066,6.27133,0.01029,0.57933,0.51114,0.55423,0.26261,1.42443,5.78608,0.01213,0.001208,0.001208,0.001208 | |
| 6,70.1904,1.35308,5.52749,0.01051,0.64229,0.54639,0.62096,0.31168,1.36925,3.74584,0.01071,0.00101,0.00101,0.00101 | |
| 7,76.5472,1.33035,4.88973,0.00948,0.67609,0.6886,0.6727,0.34537,1.417,2.782,0.01144,0.000812,0.000812,0.000812 | |
| 8,83.1112,1.28312,4.42276,0.00933,0.6208,0.6701,0.70908,0.36348,1.43641,2.32215,0.0112,0.000614,0.000614,0.000614 | |
| 9,89.4404,1.30395,4.08956,0.00953,0.73259,0.58763,0.72863,0.39589,1.39746,2.16822,0.01053,0.000416,0.000416,0.000416 | |
| 10,95.1279,1.26597,3.91324,0.0087,0.63779,0.73196,0.74721,0.41329,1.44521,2.10263,0.01085,0.000218,0.000218,0.000218 | |