---
language:
- en
pretty_name: Pucks surrogate Laserweeder
license: other
license_name: laser-dataset-replication-license-v1.0
license_link: LICENSE
tags:
- AgTech
annotations_creators:
- machine-generated
language_creators:
- found
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- object-detection
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
dataset_info:
  features:
  - name: image_id
    dtype: int32
  - name: image
    dtype: image
  - name: annotated_image
    dtype: image
  - name: resolution
    sequence: int32
    length: 2
  - name: bboxes
    sequence:
      sequence: float32
      length: 4
  - name: category_ids
    sequence: int32
  splits:
  - name: train
    num_bytes: 316722721.0
    num_examples: 118
  - name: validation
    num_bytes: 48332168.0
    num_examples: 18
  - name: test
    num_bytes: 24279368.0
    num_examples: 9
  download_size: 389352498
  dataset_size: 389334257.0
---

<h1 align="center"><strong>Pucks dataset</strong></h1>

## Dataset Overview

<div align="justify">

The Pucks Dataset is part of the L&Aser surrogate target recognition pipeline developed by Laudando & Associates LLC. This dataset contains high-resolution field images annotated with bounding boxes around small circular surrogate targets (“pucks”) used to simulate real weed targets for the L&Aser weeding system.

</div>

## Contents

- Raw RGB images collected in field conditions using a NVIDIA Jetson and monocular camera

- Bounding boxes in COCO-style format generated using a neural network

- Annotated visual overlays for quick inspection

## Preview Format

<div align="justify">

This dataset is optimized for visual inspection on the Hugging Face Hub, with an additional ```annotated_image``` column for rapid validation. The raw COCO JSON and images are included in their original form for reproducibility and training.

</div>

## Example Use

```python
from datasets import load_dataset

ds = load_dataset("Laudando-Associates-LLC/pucks", split="train")
img = ds[0]["image"]
ann = ds[0]["bboxes"]
```

## Recording Date

<div align="justify">

The data was originally collected in ROS 2 bag format in April 2024 during controlled field trials conducted by Laudando & Associates LLC.
This dataset is a stripped-down version containing only the extracted RGB images and their corresponding object detection annotations.

</div>

## License

<div align="justify">

This dataset is provided under the L&Aser Dataset Replication License (Version 1.0). See [LICENSE](LICENSE) for full terms.

</div>