Datasets:
File size: 1,303 Bytes
30876d1 3204ebb 7b0fe94 3204ebb 7b0fe94 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 | ---
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. |