| --- |
| license: cc-by-4.0 |
| language: |
| - en |
|
|
| task_categories: |
| - object-detection |
|
|
| task_ids: |
| - object-detection |
|
|
| tags: |
| - yolo |
| - yolov8 |
| - computer-vision |
| - object-detection |
| - traffic |
| - road |
| - vehicles |
| - intelligent-transportation |
| - traffic-monitoring |
| - autonomous-driving |
|
|
| pretty_name: Road Object Detection Dataset (YOLOv8) |
|
|
| annotations_creators: |
| - expert-generated |
|
|
| source_datasets: |
| - Roboflow |
| --- |
| |
| # 🚦 Road Object Detection Dataset (YOLOv8) |
|
|
| <div align="center"> |
|
|
|  |
|  |
|  |
|  |
|
|
| **A multi-class road scene object detection dataset for training and benchmarking modern object detection models.** |
|
|
| </div> |
|
|
| --- |
|
|
| ## 📌 Overview |
|
|
| This dataset contains **annotated road scene images** in **YOLOv8 format** for multi-class object detection. |
|
|
| It is suitable for developing and evaluating deep learning models for: |
|
|
| - 🚗 Vehicle Detection |
| - 🚦 Traffic Monitoring |
| - 🏙️ Smart City Applications |
| - 🚘 Autonomous Driving Research |
| - 📹 Intelligent Transportation Systems (ITS) |
|
|
| --- |
|
|
| # 📂 Dataset Structure |
|
|
| ``` |
| Road_Object_Detection_Dataset/ |
| │ |
| ├── data.yaml |
| │ |
| ├── train/ |
| │ ├── images/ |
| │ └── labels/ |
| │ |
| ├── valid/ |
| │ ├── images/ |
| │ └── labels/ |
| │ |
| └── test/ |
| ├── images/ |
| └── labels/ |
| ``` |
|
|
| --- |
|
|
| # 🏷️ Classes |
|
|
| | ID | Class | |
| |---:|--------| |
| | 0 | 🚲 Bike | |
| | 1 | 🚌 Bus | |
| | 2 | 🚗 Car | |
| | 3 | 🚶 Person | |
| | 4 | 🚦 Traffic Signal | |
| | 5 | 🚚 Truck | |
|
|
| --- |
|
|
| # 📝 Annotation Format |
|
|
| The dataset follows the **YOLOv8** annotation format. |
|
|
| Each label file contains one object per line: |
|
|
| ```text |
| class x_center y_center width height |
| ``` |
|
|
| where all coordinates are **normalized** between **0 and 1**. |
|
|
| Example: |
|
|
| ```text |
| 2 0.523 0.418 0.247 0.182 |
| ``` |
|
|
| --- |
|
|
| # 🚀 Training Example |
|
|
| ```python |
| from ultralytics import YOLO |
| |
| model = YOLO("yolov8n.pt") |
| |
| model.train( |
| data="data.yaml", |
| epochs=100, |
| imgsz=640 |
| ) |
| ``` |
|
|
| --- |
|
|
| # 🎯 Applications |
|
|
| - Object Detection |
| - Vehicle Detection |
| - Traffic Analysis |
| - Road Scene Understanding |
| - Smart Transportation |
| - Autonomous Driving |
| - AI Surveillance |
| - Academic Research |
|
|
| --- |
|
|
| # 📋 Dataset Information |
|
|
| | Property | Value | |
| |----------|--------| |
| | Task | Object Detection | |
| | Annotation Format | YOLOv8 | |
| | Number of Classes | 6 | |
| | Data Split | Train / Validation / Test | |
| | License | CC BY 4.0 | |
|
|
| --- |
|
|
| # 📜 Citation |
|
|
| If you use this dataset in your research, please cite it appropriately. |
|
|
| ```bibtex |
| @dataset{road_object_detection_yolov8, |
| title={Road Object Detection Dataset (YOLOv8)}, |
| author={Soban Hussain}, |
| year={2026}, |
| publisher={Hugging Face}, |
| } |
| ``` |
|
|
| --- |
|
|
| # 📄 License |
|
|
| This dataset is distributed under the **CC BY 4.0** License. |
|
|
| --- |
|
|
| <div align="center"> |
|
|
| ### ⭐ If you find this dataset useful, consider giving it a star on Hugging Face. |
|
|
| Happy Training! |
|
|
| </div> |
