BUTom21: Still image tomato dataset for detection and segmentation (doi:10.60507/FK2/DHTEH1)

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Part 2: Study Description
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Document Description

Citation

Title:

BUTom21: Still image tomato dataset for detection and segmentation

Identification Number:

doi:10.60507/FK2/DHTEH1

Distributor:

bonndata

Date of Distribution:

2026-07-17

Version:

1

Bibliographic Citation:

Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall, Juergen; McCool, Chris, 2026, "BUTom21: Still image tomato dataset for detection and segmentation", https://doi.org/10.60507/FK2/DHTEH1, bonndata, V1

Study Description

Citation

Title:

BUTom21: Still image tomato dataset for detection and segmentation

Identification Number:

doi:10.60507/FK2/DHTEH1

Authoring Entity:

Halstead, Michael (University of Bonn)

Guclu, Esra (University of Bonn)

Farag, Mohamed (University of Bonn)

Pallotta, Enrico (University of Bonn)

Hund, Christian (University of Bonn)

Roscher, Ribana (University of Bonn)

Bennewitz, Maren (University of Bonn)

Gall, Juergen (University of Bonn)

McCool, Chris (CSIRO)

Distributor:

bonndata

Access Authority:

Güclü, Esra

Depositor:

Güclü, Esra

Date of Deposit:

2026-07-14

Holdings Information:

https://doi.org/10.60507/FK2/DHTEH1

Study Scope

Keywords:

Agricultural Sciences

Abstract:

BUTom21 dataset is a fully hand-annotated still image dataset of tomatoes. It contains 123, 72, 98 images respectively in the training, validation, and evaluation subsets. The dataset contains RGB and noisy depth images captured across 2 capture days and two different RealSense D435i cameras. This creates a fully pixel-wise annotated dataset for tomato detection and segmentation in a real-world robotics scenario.

Date of Collection:

2021-08-18-2021-09-10

Kind of Data:

Images; Numerical; Spreadsheet; Structured; Qualitative

Methodology and Processing

Sources Statement

Data Access

Notes:

<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a>

Other Study Description Materials

Related Studies

Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall, Juergen; McCool, Chris, 2026, "BUTom-ST21: Spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels", https://doi.org/10.60507/FK2/TTPCNV, bonndata

Related Publications

Citation

Title:

Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall Juergen; Stachniss, Cyrill; McCool, Chris,"Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels", https://arxiv.org/abs/2607.14934, arXiv

Identification Number:

10.48550/arXiv.2607.14934

Bibliographic Citation:

Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall Juergen; Stachniss, Cyrill; McCool, Chris,"Still image and spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels", https://arxiv.org/abs/2607.14934, arXiv

Other Study-Related Materials

Label:

BUTom21.tar.gz

Notes:

application/gzip

Other Study-Related Materials

Label:

BUTom21_structure.md

Notes:

text/markdown

Other Study-Related Materials

Label:

Halstead_BUTom21_ReadMe.txt

Notes:

text/plain