---
license: cc-by-4.0
library_name: libreyolo
tags:
  - object-detection
  - oriented-object-detection
  - obb
  - ultra-experimental
  - yolov9
  - libreyolo
---

# LibreYOLO9t-obb

Ultra-experimental LibreYOLO YOLO9-tiny oriented object detection weights fine-tuned for vehicle OBB detection.

These weights are **ultra-experimental** development weights. They were produced while validating LibreYOLO OBB training support and should not be treated as production or benchmark-official weights.

## Source

Initialized from LibreYOLO9t detect weights. The YOLO9 implementation in LibreYOLO follows the permissive MultimediaTechLab/YOLO MIT-licensed lineage.

Fine-tuned on `My First Project - v8`, a Roboflow Universe UAV vehicle OBB dataset provided by a Roboflow user:
https://universe.roboflow.com/bobo-48pem/my-first-project-ewwrm

This model was not trained on DOTA.

## Dataset

Dataset license: Creative Commons Attribution 4.0 International (CC BY 4.0).

Classes:
- bike
- bus
- car
- other_vehicle
- taxi
- truck

Local development export metadata reported 932 source/export images, YOLOv8 Oriented Object Detection format, and Roboflow preprocessing/augmentation.

## Metrics

UAV-OBB validation split, best epoch 5:
- mAP50: 0.605965
- mAP50-95: 0.365930
- mAP75: 0.403682
- precision: 0.242334
- recall: 0.700350


## Modifications

The checkpoint is a lean LibreYOLO inference checkpoint produced from the best EMA training checkpoint. Optimizer, resume config, raw train model state, and EMA resume buffers were removed before upload.

## License

These fine-tuned weights are released under CC BY 4.0 to preserve the attribution requirements of the training dataset. See [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE).