Object Detection
ultralytics
computer-vision
yolov8
vehicle-detection
traffic-analysis
highway-monitoring
Instructions to use vietnguyennn0705/highway-vehicle-detection-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use vietnguyennn0705/highway-vehicle-detection-code with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("vietnguyennn0705/highway-vehicle-detection-code") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
highway-vehicle-detection-code / finetune_dataset /labels /Screenshot-35-_png.rf.67cdec932edd097a51887a3fcc23d007.txt
| 7 0.31398809523809523 0.6210317460317463 0.05952380952380949 0.1018518518518519 | |
| 7 0.07249232700892856 0.850198412698413 0.14114815848214288 0.29591393849206327 | |
| 3 0.26674107142857145 0.5608465608465613 0.05580357142857144 0.06613756613756626 | |
| 1 0.42425022893772885 0.4139957264957265 0.03290979853479854 0.06486568986568986 | |
| 7 0.45166015625 0.3708767361111111 0.026153564453125 0.05995008680555555 | |
| 2 0.44580078125 0.4544270833333333 0.0246124267578125 0.032416449652777776 | |
| 2 0.366455078125 0.4544270833333333 0.0254669189453125 0.03125 | |
| 2 0.428466796875 0.5403645833333334 0.04010009765625 0.060492621527777776 | |
| 2 0.39990234375 0.4177517361111111 0.0171051025390625 0.023966471354166668 | |
| 2 0.327880859375 0.5021701388888888 0.03594970703125 0.041015625 | |
| 2 0.462158203125 0.4325086805555556 0.018798828125 0.026692708333333332 | |
| 2 0.6416015625 0.7000868055555556 0.06781005859375 0.1134982638888889 | |
| 2 0.478759765625 0.3845486111111111 0.012237548828125 0.021755642361111112 | |
| 2 0.5263671875 0.3851996527777778 0.01267242431640625 0.018717447916666668 | |
| 7 0.481689453125 0.3385416666666667 0.01332855224609375 0.029269748263888888 | |
| 2 0.7509765625 0.6111111111111112 0.06280517578125 0.08930121527777778 | |