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Part 1: Document Description
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Citation |
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Title: |
BUTom-ST21: Spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels |
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Identification Number: |
doi:10.60507/FK2/TTPCNV |
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Distributor: |
bonndata |
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Date of Distribution: |
2026-07-17 |
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Version: |
1 |
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Bibliographic Citation: |
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, V1 |
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Citation |
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Title: |
BUTom-ST21: Spatial-temporal tomato data enabling detection, segmentation, tracking, and video-instance segmentation using strong and weak labels |
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Identification Number: |
doi:10.60507/FK2/TTPCNV |
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Authoring Entity: |
Halstead, Michael (University of Bonn) |
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Guclu, Esra (University of Bonn) |
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Farag, Mohamed (University of Bonn) |
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Pallotta, Enrico (University of Bonn) |
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Hund, Christian (University of Bonn) |
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Roscher, Ribana (University of Bonn) |
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Bennewitz, Maren (University of Bonn) |
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Gall, Juergen (University of Bonn) |
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McCool, Chris (CSIRO) |
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Distributor: |
bonndata |
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Access Authority: |
Güclü, Esra |
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Depositor: |
Güclü, Esra |
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Date of Deposit: |
2026-07-14 |
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Holdings Information: |
https://doi.org/10.60507/FK2/TTPCNV |
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Study Scope |
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Keywords: |
Agricultural Sciences |
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Abstract: |
The BUTom-ST21 alleviates the data paucity issue within the horticulture and tomato domain. We employed BUTom21 still image dataset and generated spatial-temporal tomato dataset using a neural-radiance field based approach. In total we have 217 video sequences (123 train/ 72 valid/ 22 eval) can be used for image-based/video-based detection and segmentation, and multi object tracking. The train and validation sets are weakly labeled(pseudo-labeled), and evaluation set is hand-labeled ground-truth. BUTom-ST21 has 7749, and 4536 pseudo-labeled images across the training and validation set, and 1386 images hand-labeled in the evaluation set. Additionally it has camera poses per sequence, enabling the use of 3D reconstruction purposes in horticultural field. |
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Date of Collection: |
2021-08-18-2021-09-10 |
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Kind of Data: |
Images; Numerical; Spreadsheet; Structured; Qualitative |
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Methodology and Processing |
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Sources Statement |
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Data Access |
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Notes: |
<a href="http://creativecommons.org/licenses/by/4.0">CC BY 4.0</a> |
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Other Study Description Materials |
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Related Studies |
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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 |
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Guclu, Esra; Halstead, Michael; Denman, Simon; McCool, Chris, 2025, "BUP-ST20: Weakly Labelled Spatial Temporal Sweet Pepper Data", https://doi.org/10.60507/FK2/NUMVO1, bonndata |
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Related Publications |
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Citation |
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Title: |
Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall, Juergen; McCool, Chris, 2026, "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 |
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Identification Number: |
10.48550/arXiv.2607.14934 |
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Bibliographic Citation: |
Halstead, Michael; Guclu, Esra; Farag, Mohamed; Pallotta, Enrico; Hund, Christian; Roscher, Ribana; Bennewitz, Maren; Gall, Juergen; McCool, Chris, 2026, "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 |
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Citation |
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Title: |
Guclu, Esra; Halstead, Michael; Denman, Simon; McCool, Chris, 2025, "BUP-ST20: Weakly Labelled Spatial Temporal Sweet Pepper Data", The International Journal of Robotics Research (IJRR), 2025 |
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Identification Number: |
10.1177/02783649251379093 |
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Bibliographic Citation: |
Guclu, Esra; Halstead, Michael; Denman, Simon; McCool, Chris, 2025, "BUP-ST20: Weakly Labelled Spatial Temporal Sweet Pepper Data", The International Journal of Robotics Research (IJRR), 2025 |
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Label: |
annotated_seq_frame_list.yaml |
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Notes: |
application/yaml |
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Label: |
butomst21_depth.tar.gz.aa |
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Notes: |
audio/x-pn-audibleaudio |
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butomst21_depth.tar.gz.ab |
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Notes: |
application/octet-stream |
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butomst21_eval_annotations.tar.gz |
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Notes: |
application/gzip |
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butomst21_poses.tar.gz |
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Notes: |
application/gzip |
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butomst21_pseudo_labels_m2f.tar.gz |
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Notes: |
application/gzip |
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butomst21_pseudo_labels_Yolo26.tar.gz |
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Notes: |
application/gzip |
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butomst21_rgb.tar.gz.aa |
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Notes: |
audio/x-pn-audibleaudio |
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butomst21_rgb.tar.gz.ab |
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application/octet-stream |
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butomst21_rgb.tar.gz.ac |
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application/pkix-attr-cert |
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butomst21_rgb.tar.gz.ad |
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application/octet-stream |
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butomst21_rgb.tar.gz.ae |
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Notes: |
application/octet-stream |
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Label: |
butomst21_rgb.tar.gz.af |
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Notes: |
application/octet-stream |
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butomst21_rgb.tar.gz.ag |
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Notes: |
image/x-applix-graphics |
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BUTomST21_structure.md |
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Notes: |
text/markdown |
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camera_parameters.yaml |
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Notes: |
application/yaml |
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Label: |
Halstead_BUTomST21_ReadMe.txt |
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Notes: |
text/plain |
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image_camera_row_identity.yaml |
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Notes: |
application/yaml |
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pagnerf_seq_frames.yaml |
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Notes: |
application/yaml |
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Label: |
train_val_eval_splits.yaml |
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Notes: |
application/yaml |