/Agricultural_datasets

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Datasets for Agricultural research

This is a collection of datasets for either image or 3D object detection or segmentation, that can be be download from the internet and are already found in FOLA (Agroscope internal network) For the case of 3D data, the dataset may or may not be annotated. PLEASE let me know if you know about another dataset :)

2D

Name Identification Class Type Paper Authors Year URL URL2 Description Modifications Status URL:
RumexWeeds RumexWeeds ['Plant'] ['object detection', 'instance segmentation'] RumexWeeds: A grassland dataset for agricultural robotics Güldenring et al 2023 https://dtu-pas.github.io/RumexWeeds/ https://data.dtu.dk/ndownloader/files/39268307 Rumex detection and segmentation nan nan
Flowers WSUA ['flowers', 'apple', 'peach', 'pear'] ['object detection'] Dias et al 2018 nan nan
ACFR Orchard Fruit Dataset acfr-fruit-almonds ['fruit', 'almond'] ['object detection'] Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry Underwood and Bargoti 2016 https://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/ Small tilles of fruits in trees 20240411: Was divided in val, train and test using the txt provides by authors DONE nan
AppleScabFDs ASF ['fruit', 'apple'] ['classification'] Kodors et al 2021 https://www.kaggle.com/datasets/projectlzp201910094/applescabfds Behind nan
WSU_apple WSUA ['fruit', 'apple'] Object detection Santosh Bhusal, Manoj Karkee and Qin Zhang 2019 https://rex.libraries.wsu.edu/esploro/outputs/dataset/Apple-Dataset-Benchmark-from-Orchard-Environment/99900502619401842#details Apple Dataset Benchmark from Orchard Environment in Modern Fruiting Wall This dataset contain multiple datasets nan nan
Agroscope apple Agroscope_apple ['fruit', 'apple'] ['object detection'] Chiang 2024 Agroscope dataset for apple fruit counting Labels from ppt to txt DONE nan
acfr-multifruit-2016 AM ['fruit', 'apple'] ['object detection'] Bargoti et al. 2016 http://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/ The dataset was gathered by the agriculture team at the Australian Centre for Field Robotics Only apples were keep. The original dataset have circles as annotations nan nan
ACFR Orchard Fruit Dataset acfr-fruit-apples ['fruit', 'apple'] ['object detection', 'instance segmentation'] Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry Underwood and Bargoti 2016 https://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/ Small tilles of fruits in trees 20240411: Was divided in val, train and test using the txt provides by authors DONE nan
KFuji RGB-DS database KFS ['fruit', 'apple'] ['object detection'] Gené-Mola et al. 2019 http://www.grap.udl.cat/en/publications/KFuji_RGBDS_database.html https://zenodo.org/record/3715991#.YrQqfNJByV4 annotations were changed from x1-y1-widh-height to x1y1x2y2 format nan nan
Minneapple MA ['fruit', 'apple'] ['Instance segmentation'] Häni et al 2019 https://github.com/nicolaihaeni/MinneApple 1000 apples tree images with more than 41k manual annotations DONE, USED nan nan
WSU_apple_depth WSUAD ['fruit', 'apple'] ['object detection'] Longsheng Fu, Manoj Karkee and Qin Zhang 2020 https://rex.libraries.wsu.edu/esploro/outputs/dataset/Scifresh-Apple-Orignial-and-DepthFilter-RGB/99900501726801842 Scifresh Apple Orignial and DepthFilter RGB Images nan nan
PApple_RGB-D-Size dataset PAS ['fruit', 'apple'] ['instance segmentation'] Ferrer Ferrer M et al 2022 2022 http://www.grap.udl.cat/en/publications/PApple_RGB-D-Size.html https://gofile-36514d3739.fr3.quickconnect.to/sharing/brPZduTyi annotations were changed from instance segmentation to object segmentation x1y1x2y2 format nan nan
deepFruits DF ['fruit', 'apple', 'capsicum', 'strawberry'] ['object detection'] Inkyu et al 2016 hhttp://enddl22.net/wordpress/datasets/deepcrops-datasets-and-annotation-tool Object detection on 7 species. Only three were downloaded (apple, capsicum and strawberry) Different size. nan nan
Deep_blueberry DB ['fruit', 'blueberry'] ['object detection', 'instance segmentation'] Gonzalez et al. 2019 https://ieeexplore.ieee.org/document/8787818 10.1109/ACCESS.2019.2933062 Blue berry detection on 293 images and instance segmentation on 7 images Annotation files were modified as were not done in VIA. Additionaly the instance segmentation pictures (7) were rotated as they dont match the provided pictures nan nan
WGN_broccoli_RGBD WGNB ['fruit', 'broccoli'] ['instance segmentation'] Blok 2021 2021 https://data.4tu.nl/articles/dataset/Data_underlying_the_publication_Image-based_size_estimation_of_broccoli_heads_under_varying_degrees_of_occlusion/13603787 RGBD for annodal network nan nan
ACFR Orchard Fruit Dataset acfr-fruit-mangoes ['fruit', 'mango'] ['object detection'] Image Based Mango Fruit Detection, Localisation and Yield Estimation Using Multiple View Geometry Underwood and Bargoti 2016 https://data.acfr.usyd.edu.au/ag/treecrops/2016-multifruit/ Small tilles of fruits in trees 20240411: Was divided in val, train and test using the txt provides by authors DONE nan
MOrangeT MOR ['fruit', 'orange'] ['object detection'] Santos et al 2024 nan Oranges in trees. include green oranges nan https://www.redape.dados.embrapa.br/dataset.xhtml?persistentId=doi:10.48432/OI7BFG
strawberry Digital Images SDI ['fruit', 'strawberry'] ['instance segmentation'] Perez-Borrero et al 2020 https://strawdi.github.io/ 3.1K images of strawberries on field DONE, USED nan nan
strawberry-semantic-segmentation SSS ['fruit', 'strawberry'] ['instance segmentation'] NaN NaN https://www.kaggle.com/datasets/woodiedudy/strawberry-segmentation-dataset 141 strawberries images with masks for berries, leaves, stems and flowers nan nan
strawberry-disease-detection-dataset SD ['fruit', 'strawberry'] ['object detection'] Afzaal et al 2021 https://www.kaggle.com/usmanafzaal/strawberry-disease-detection-dataset 2500 images for 7 diferent diseases in strawberry nan nan
strawberry-dataset-for-object-detection SDO ['fruit', 'strawberry'] ['object detection'] Pastell et al 2022 https://zenodo.org/record/6126677#.YrQMe9JByV5 https://www.luke.fi/en/projects/poimintarobottieip-01 813 images in two classes Reclassfied to 4 different classes nan nan
strawberry-skripsie SSK ['fruit', 'strawberry'] ['object detection'] NaN 2021 https://universe.roboflow.com/skripsie/strawberry.00/15 450 images in one class Reclassfied to 4 different classes nan nan
strawberry detection STL ['fruit', 'strawberry'] ['instance segmentation'] Perez-Borrero et al 2020 https://strawdi.github.io/ 3.1K images of strawberries on field DONE, USED nan nan
laboro_tomato LT ['fruit', 'tomato'] ['object detection', 'instance segmentation'] Laboro AI 2019 https://github.com/laboroai/LaboroTomato Tomatos (Normal and cherry) in three maturity status Added object detection in YOLOv5 Format DONE nan
tomatOD TD ['fruit', 'tomato'] ['object detection'] Tsironis et al. 2020 2021 https://github.com/up2metric/tomatOD 277 images for 2418 annotated tomato fruits in three categories (1592 unripe, 395 semi-ripe, 431 fully ripe nan nan
Rob2Pheno RP ['fruit', 'tomato'] ['instance segmentation'] Afonso et al 2021 https://research.wur.nl/en/datasets/rob2pheno-annotated-tomato-image-dataset 123 RGBD pictures took with Realsense D435 nan nan
tomato_detection TE ['fruit', 'tomato'] ['object detection'] ?? 2020 https://makeml.app/datasets/tomato 895 images for tomatoes without categories (class =1, tomatoes) nan nan
Plant_phenotyping PP ['leaf'] ['Instance segmentation'] Plant phenotyping 2014, 2015, 2017 https://www.plant-phenotyping.org 3 Datasets for leaf instance segmentation on Arabidopsis and Tobacco nan nan
PlantVillage PV ['leaf'] ['classification'] Hugues and Salathe 2016 https://data.mendeley.com/datasets/tywbtsjrjv/1 https://www.tensorflow.org/datasets/catalog/plant_village PlantVillage dataset consists of 54303 healthy and unhealthy leaf images divided into 38 categories by species and disease nan nan
PlantDoc PD ['leaf'] ['object detection'] Singh et al. 2020 https://github.com/pratikkayal/PlantDoc-Dataset https://public.roboflow.com/object-detection/plantdoc Disease detection on 13 plant species resized to 416 x 416 thanks to roboflow nan nan
AppleScabLDs ASL ['leaf', 'apple'] ['classification'] Kodors et al 2021 https://www.kaggle.com/datasets/projectlzp201910094/applescablds Behind nan
Plant-pathology-2020-fgvc7 PPA ['leaf', 'apple'] ['instance segmentation'] Thapa et al. 2020 2020 https://www.kaggle.com/c/plant-pathology-2020-fgvc7 Disease detection in leaves of apple trees. nan nan
downly_mildew_images DM ['leaf', 'grape'] ['instance segmentation'] Abdelghafour et al 2021 https://pubmed.ncbi.nlm.nih.gov/34258341/ Instance segmentation in grape, specialy focus on downly mildew WAITING TO BE PROCESSED nan nan
strawberry tipburn detection STD ['leaf', 'strawberry'] ['classification'] Hairi and Avsar 2022 https://www.kaggle.com/datasets/ercanavsar/images-of-strawberry-leaves-for-tipburn-detection nan nan
tomato_leaves_disease TLD ['leaf', 'tomato'] ['classification'] NaN 2021 https://www.kaggle.com/datasets/kaustubhb999/tomatoleaf nan nan

3D

Name Identification Class Paper Authors Year URL URL2 Equipment Description Modifications Status
Grapevine_prunning_data Grapevine_prunning_data Bush - No leaves 3D Skeletonization of Complex Grapevines for Robotic Pruning Schneider et al 2023 https://labs.ri.cmu.edu/aiira/resources/ https://drive.google.com/drive/folders/1O_i01eBknf8hUb0zXSWHcSAw2sB1OJcz RGBD - PointGrey CM3 Wine plants None Raw
Blueberries Blueberries Bush - With leaves 3D point cloud data to quantitatively characterize size and shape of shrub crops Jiang 2019 https://doi.org/10.1038/s41438-019-0123-9 https://figshare.com/s/2abb4eeadfda4103545b ZEB1 scanner 47 bushes of raspberry plants with leaves None Raw
ROSE-X ROSE-X Bush - With leaves ROSE-X: an annotated data set for evaluation of 3D plant organ segmentation methods Dutagaci et al 2020 https://plantmethods.biomedcentral.com/articles/10.1186/s13007-020-00573-w Siemens X-ray Rose plants on 3D None Raw
VineLIDAR VineLIDAR Bush - With leaves High resolution LiDAR dataset acquired using UAV (unmanned aerial vehicle) over two vineyards and two years located in 'Tomiño', Pontevedra, Spain Vélez, S., Ariza-Sentís, M., & Valente, J. 2023 https://zenodo.org/records/8113105 DJI Zenmuse L1 High-resolution UAV-LiDAR vineyard dataset acquired over two years in northern Spain None Raw
Brocoli Brocoli Organ Image-based size estimation of broccoli heads under varying degrees of occlusion Blok, P., van Henten, E., van Evert, F. and Kootstra, G. 2021 https://doi.org/10.1016/j.biosystemseng.2021.06.001 https://git.wur.nl/blok012/sizecnn RGBD - Realsense D435 Brocoli heads for occlusion studies None Raw
CVPPA@ECCV_2024_bell_peper CVPPA@ECCV_2024_bell_peper Organ Efficient and Accurate Transformer-Based 3D Shape Completion and Reconstruction of Fruits for Agricultural Robots Magistri et al 2024 https://www.ipb.uni-bonn.de/data/shape_completion/index.html RGBD - Realsense D435 Sweet peper rgb frames for reconstruction None Raw
Biomass_evaluation_LIDAR Biomass_evaluation_LIDAR Trees - No leaves Advancing Fine Branch Biomass Estimation with Lidar and Structural Models 2024 https://github.com/VEZY/Biomass_evaluation_LiDAR Riegl VZ-400 Walnut trees without leaves None Raw
cacao_cameroon cacao_cameroon Trees - With leaves Terrestrial LiDAR point cloud dataset of cocoa trees grown in agroforestry systems in Cameroon Peynaud, E. and Momo, S. 2024 https://doi.org/10.1016/j.dib.2024.110108 https://dataverse.cirad.fr/dataset.xhtml?persistentId=doi:10.18167/DVN1/5HZB1F Leica C10 Cocoa tree point clouds obtained by terrestrial Lidar scanning (TLS) in agroforestry systems in Cameroon None Raw
FOR-instance FOR-instance Trees - With leaves FOR-instance (FOR-instance: a UAV laser scanning benchmark dataset for semantic and instance segmentation of individual trees) Puliti et al 2023 https://arxiv.org/abs/2309.01279 Riegl - Multiple sensors Trees datasets None Raw
TUMBA Trees - With leaves Tumbarumba Wet Eucalypt Terrestrial LiDAR, 2022 Shaun et al 2022 https://researchdata.edu.au/tumbarumba-wet-eucalypt-lidar-2022/2766669 Riegl VZ-2000i Terrestrial Laser Scanner Australian eucalyptus None Raw
Weisser_2024 Weisser_2024 Trees - With leaves Manually labeled terrestrial laser scanning point clouds of individual trees for leaf-wood separation Weisser et al 2024 https://heidata.uni-heidelberg.de/dataset.xhtml?persistentId=doi:10.11588/data/UUMEDI https://doi.org/10.11588/data/UUMEDI RIEGL VZ-400 TLSRIEGL VZ-400 TLS Forestry trees None Raw
Vicari_2018a Vicari_2018a Trees - With leaves Leaf and wood classification framework for terrestrial LiDAR point clouds: Simulated data validation dataset Vicari et al 2018 https://zenodo.org/records/1324158 Simulation Forestry trees None Raw
Vicari_2018b Vicari_2018b Trees - With leaves Leaf and wood classification framework for terrestrial LiDAR point clouds: Field data validation dataset Vicari et al 2018 https://zenodo.org/records/1324156 Riegl VZ-400 Forestry trees None Raw
Westling_2021 Westling_2021 Trees - With leaves Graph-based methods for analyzing orchard tree structure using noisy point cloud data Westling et al 2021 https://data.mendeley.com/datasets/d6k5v2rmyx/1 Multiple Agricultural trees None Raw
Momo_takoudjou_2018 Momo_takoudjou_2018 Trees - With leaves Using terrestrial laser scanning data to estimate large tropical trees biomass and calibrate allometric models: a comparison with traditional destructive approach Momo takoudjou et al 2018 https://datadryad.org/stash/dataset/doi:10.5061/dryad.10hq7 Leica C10 Scanstation tropical trees None Raw
Wytham woods Wytham woods Trees - With leaves Virtual forest for radiative transfer modelling: realistic stand reconstruction from terrestrial LiDAR Calders et al 2018 https://bitbucket.org/tree_research/wytham_woods_3d_model/src/master/ RIEGL VZ-400 forestry trees None Raw