https://github.com/vs-uulm/yolo-for-autonomous-driving
Easy Training of YOLO Models with Car Datasets for Autonomous Driving
https://github.com/vs-uulm/yolo-for-autonomous-driving
autonomous-car autonomous-driving computer-vision machine-learning object-detection python pytorch yolov11 yolov12
Last synced: 2 months ago
JSON representation
Easy Training of YOLO Models with Car Datasets for Autonomous Driving
- Host: GitHub
- URL: https://github.com/vs-uulm/yolo-for-autonomous-driving
- Owner: vs-uulm
- License: agpl-3.0
- Created: 2025-03-04T14:00:41.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-03-04T15:32:27.000Z (over 1 year ago)
- Last Synced: 2025-03-04T16:36:30.514Z (over 1 year ago)
- Topics: autonomous-car, autonomous-driving, computer-vision, machine-learning, object-detection, python, pytorch, yolov11, yolov12
- Language: Python
- Homepage:
- Size: 234 KB
- Stars: 0
- Watchers: 12
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# YOLO Models for Autonomous Driving
This project is a comprehensive toolkit for researchers and developers working on autonomous driving datasets. It automates the conversion of different file formats into the YOLO format and facilitates training of various YOLO model versions.
## Features
- **Multi-format Converter:**
Convert common autonomous driving dataset annotations (e.g., Pascal VOC, COCO, [KITTI](https://www.cvlibs.net/datasets/kitti/eval_tracking.php), [BDD100K](https://arxiv.org/abs/1805.04687) into the YOLO format.
- **YOLO Trainer:**
Seamlessly train different versions of YOLO (v10, [v11](https://github.com/ultralytics/ultralytics), ·[v12](https://arxiv.org/abs/2502.12524), etc.) using pre-configured training pipelines.
- **Modular and Extensible:**
Designed with modularity in mind, allowing you to add new conversion modules or support additional YOLO versions as needed.
## Getting Started
### Prerequisites
- Python 3.10
- Git
- [uv](https://github.com/astral-sh/uv)
### Installation
```bash
git clone git@github.com:vs-uulm/yolo-for-autonomous-driving.git
cd yolo-for-autonomous-driving
uv sync
```
## Usage Example
### Download and Convert KITTI Dataset to YOLO Format
```bash
uv run convert_dataset_to_yolo_format.py ./config/converter/kitti.yaml
```
### Train YOLOv11s with KITTI from Scratch and Pretrained from COCO
```bash
uv run train_yolos.py ./config/trainer/yolov11_kitti.yaml
```
### Check The Model Quality
```bash
cd runs
```