README.md

metadata

pretty_name: RoboXS
task_categories:
  - object-detection
tags:
  - yolo
  - computer-vision
  - object-detection
license: mit

RoboXS- Robotics Extended test Set

Overview

This repository contains 4 separate YOLO-format batches: A total of 21 parts of Robotics dataset were available to prepare the custom test set used to specifically assess the robustness of object detectors. The proposed idea was to create a test set of 80 images across 10 object classes, split into four increasing-scene-difficulty equal batches

• b1
• b2
• b3
• b4

Each batch contains:

• data.yaml
• images/test/*.jpg
• labels/test/*.txt

Format

This dataset is stored in raw YOLO format.

Each annotation row is: class x_center y_center width height

Coordinates are normalized.

Batch structure

b1

• images: b1/images/test/
• labels: b1/labels/test/
• classes: see b1/data.yaml

b2

• images: b2/images/test/
• labels: b2/labels/test/
• classes: see b2/data.yaml

b3

• images: b3/images/test/
• labels: b3/labels/test/
• classes: see b3/data.yaml

b4

• images: b4/images/test/
• labels: b4/labels/test/
• classes: see b4/data.yaml

Notes

The batches are preserved exactly as exported. This repository is intended for download and use in YOLO workflows.