Object Detection
ultralytics
ONNX
English
yolov8
aerial-imagery
drone
vehicle-detection
birds-eye-view
geo-trax
trajectory
urban-traffic
tracking
Eval Results (legacy)
Instructions to use rfonod/geo-trax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use rfonod/geo-trax with ultralytics:
from ultralytics import YOLOvv8 model = YOLOvv8.from_pretrained("rfonod/geo-trax") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
docs: make the software citation version-independent
Browse files
README.md
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@@ -282,19 +282,18 @@ If you use this model, please cite the associated publication:
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```
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If you additionally use the [Geo-trax software](https://github.com/rfonod/geo-trax), please
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also cite its Zenodo archive
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[Zenodo record](https://doi.org/10.5281/zenodo.12119542) and add a matching `version` field.
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```bibtex
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@software{
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author
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title
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url
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```
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```
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If you additionally use the [Geo-trax software](https://github.com/rfonod/geo-trax), please
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also cite its Zenodo archive, filling in the version and year you used. The DOI below is the
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*concept* DOI, which always resolves to the latest release; to cite one release specifically,
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use that version's own DOI from the [Zenodo record](https://doi.org/10.5281/zenodo.12119542).
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```bibtex
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@software{fonod_geotrax,
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author = {Fonod, Robert},
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title = {Geo-trax: A Comprehensive Framework for Georeferenced Vehicle Trajectory Extraction from Drone Imagery},
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url = {https://github.com/rfonod/geo-trax},
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doi = {10.5281/zenodo.12119542},
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version = {1.x.x},
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year = {202x}
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}
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```
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