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-37-_png.rf.29ee2a2f1da4c066d7583db8eae3f3f7.txt
| 2 0.2845982142857144 0.683862433862434 0.06175595238095246 0.08730158730158727 | |
| 1 0.201264880952381 0.5965608465608467 0.17187500000000006 0.23280423280423293 | |
| 2 0.422119140625 0.5646701388888888 0.04010009765625 0.06141493055555555 | |
| 2 0.35986328125 0.5342881944444444 0.038909912109375 0.0498046875 | |
| 2 0.465576171875 0.4099392361111111 0.017242431640625 0.022189670138888888 | |
| 2 0.45458984375 0.4440104166666667 0.0218658447265625 0.029947916666666668 | |
| 2 0.5888671875 0.4142795138888889 0.01763916015625 0.023057725694444444 | |
| 2 0.416259765625 0.4398871527777778 0.0216217041015625 0.033148871527777776 | |
| 2 0.448486328125 0.3910590277777778 0.011962890625 0.016927083333333332 | |
| 2 0.54931640625 0.392578125 0.01116180419921875 0.019300672743055556 | |
| 3 0.330322265625 0.4891493055555556 0.03533935546875 0.05422634548611111 | |
| 2 0.2462158203125 0.9435763888888888 0.1473388671875 0.1047092013888889 | |
| 2 0.47314453125 0.3895399305555556 0.01229095458984375 0.017198350694444444 | |
| 2 0.54150390625 0.3723958333333333 0.00933837890625 0.013576931423611112 | |