Hiking Trail Semantic Segmentation Image Dataset

Usage Instructions

1. Dataset Contents

This dataset contains images of hiking trails with corresponding annotations in two formats: 

• Coco segmentation masks
• YOLOv8-oriented bounding boxes

The dataset is split into training, validation, and test sets. 

2. Image Format

• Resolution: 640x360 pixels
• Pre-processing steps: none

3. Annotation Formats

a. COCO segmentation

• provides pixel-level annotations for each terrain class
• Format: JSON files following COCO dataset structures
• Each segmentation mask corresponds to an image file

b. YOLOv8-oriented Bounding Boxes

• Provides oriented bounding box annotations for each terrain class
• Format: Text files in YOLOv8 format
• Each text file corresponds to an image file

The dataset can also be found in the RoboFlow Universe here: https://universe.roboflow.com/reu-rover-project/arboretum-less-classes, where you may download it in any format you may need. 

4. Classes

The dataset includes 8 terrain classes: 

1. Grass
2. Rock
3. Trail
4. Root
5. Structure
6. Tree trunk
7. Vegetation
8. Rough trail

5. Using the Annotations

• For COCO segmentation, use standard COCO API or custom scripts to load and process the annotations. 
• For YOLOv8 bounding boxes, refer to the YOLOv8 documentation for loading and using the annotations: https://github.com/ultralytics/ultralytics

6. Pre-trained Model

A pre-trained YOLOv8 model is included with the dataset. To use it please refer to the official YOLOv8 documentation: https://github.com/ultralytics/ultralytics