Instructions to use mayanktak15/yolo8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use mayanktak15/yolo8 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("mayanktak15/yolo8") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
| # Examples | |
| Put local test images in this directory, for example: | |
| - `examples/input.jpg` | |
| - `examples/annotated_output.jpg` | |
| - `examples/detections.json` | |
| Run image inference: | |
| ```bash | |
| python inference.py \ | |
| --image examples/input.jpg \ | |
| --output examples/annotated_output.jpg \ | |
| --json examples/detections.json | |
| ``` | |
| Run the existing video tracking pipeline: | |
| ```bash | |
| python -m src.main \ | |
| --input data/raw/input.mp4 \ | |
| --output data/processed/tracked_output.mp4 | |
| ``` | |