whirlwind-ams/hsl-objects-v1

HSL Objects v1

5,037 images with COCO-style bounding box annotations for object detection in the RoboCup Humanoid Soccer League (HSL). Split 80/10/10 into train (4,029), validation (504), and test (504).

Classes

ID	Class
1	Ball
2	Goalpost
3	K1
4	L-Intersections
5	Penalty Marks
6	T-Intersections
7	X-Intersections

Sample Structure

Each example contains:

• image_id (int64) -- unique image identifier
• image (Image) -- RGB image
• width / height (int64) -- image dimensions in pixels
• objects -- annotation dictionary:
  • id (list[int64]) -- object instance IDs
  • category (list[int64]) -- category IDs (1--7)
  • bbox (list[list[float64]]) -- bounding boxes in COCO format [x, y, width, height]
  • area (list[float64]) -- bounding box areas in pixels

Sources

• RoboCup Asia Pacific Beijing Masters 2025
• RoboCup Salvador 2025
• RoboCup German Open 2025
• RoboCup German Open 2026
• Intelligent Robotics Lab, University of Amsterdam

Usage

from datasets import load_dataset
ds = load_dataset("whirlwind-ams/hsl-objects-v1")

Citation

If you use this dataset, please cite:

@misc{hsl_objects_v1,
  title={HSL Objects v1},
  author={Whirlwind Amsterdam},
  year={2025},
  publisher={Hugging Face},
  howpublished={\url{https://huggingface.co/datasets/whirlwind-ams/hsl-objects-v1}}
}