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-26-_png.rf.24e4cf99a30424bc8a87e47c1f5d4994.txt
| 3 0.828869047619048 0.6752645502645506 0.12351190476190484 0.20502645502645514 | |
| 2 0.5859375 0.45703125 0.0222930908203125 0.033881293402777776 | |
| 2 0.385009765625 0.5021701388888888 0.03167724609375 0.046061197916666664 | |
| 2 0.646484375 0.5559895833333334 0.04168701171875 0.062337239583333336 | |
| 2 0.5546875 0.4761284722222222 0.0282135009765625 0.04820421006944445 | |
| 2 0.36865234375 0.7161458333333334 0.06768798828125 0.10145399305555555 | |
| 2 0.439697265625 0.5104166666666666 0.03131103515625 0.049126519097222224 | |
| 2 0.59033203125 0.4134114583333333 0.015899658203125 0.023328993055555556 | |
| 2 0.53515625 0.4008246527777778 0.01495361328125 0.023234049479166668 | |
| 2 0.59423828125 0.6111111111111112 0.047149658203125 0.07975260416666667 | |
| 2 0.46875 0.4053819444444444 0.01422882080078125 0.0220947265625 | |
| 2 0.65478515625 0.48046875 0.033203125 0.05270724826388889 | |
| 2 0.446533203125 0.3962673611111111 0.0129241943359375 0.020453559027777776 | |
| 1 0.39013671875 0.4264322916666667 0.04840087890625 0.07411024305555555 | |
| 2 0.4794921875 0.380859375 0.01229095458984375 0.017659505208333332 | |
| 2 0.56005859375 0.3726128472222222 0.009674072265625 0.016927083333333332 | |
| 2 0.436279296875 0.3812934027777778 0.01029205322265625 0.017266167534722224 | |
| 2 0.444091796875 0.3715277777777778 0.01029205322265625 0.016737196180555556 | |
| 2 0.5244140625 0.3739149305555556 0.01024627685546875 0.016221788194444444 | |
| 2 0.45751953125 0.3810763888888889 0.01142120361328125 0.017266167534722224 | |
| 2 0.53955078125 0.3687065972222222 0.00937652587890625 0.016533745659722224 | |