{"url":"/dataset/embrapa-add-256","name":"Embrapa ADD 256","full_name":"Embrapa Apples by Drones Detection Dataset","description_markdown":"[![DOI](https://zenodo.org/badge/419452503.svg)](https://zenodo.org/badge/latestdoi/419452503)\r\n\r\nThis is a detailed description of the dataset, a data sheet for the dataset as proposed by [Gebru *et al.*](https://arxiv.org/abs/1803.09010)\r\n\r\nMotivation for Dataset Creation\r\n-------------------------------\r\n\r\n### Why was the dataset created?\r\n\r\nEmbrapa ADD 256 (*Apples by Drones Detection Dataset — 256 × 256*) was created\r\nto provide images and annotation for research on *apple detection in orchards for UAV-based monitoring in apple production. \r\n\r\n### What (other) tasks could the dataset be used for?\r\n\r\nApple detection in *low-resolution scenarios*, similar to the aerial\r\nimages employed here.\r\n\r\n### Who funded the creation of the dataset?\r\n\r\nThe building of the ADD256 dataset was supported by the Embrapa SEG\r\nProject 01.14.09.001.05.04, *Image-based metrology for Precision\r\nAgriculture and Phenotyping*, and [FAPESP](https://fapesp.br/) under \r\ngrant (2017/19282-7).\r\n\r\nDataset Composition \r\n-------------------\r\n\r\n### What are the instances? \r\n\r\nEach instance consists of an RGB image and an annotation describing apples \r\nlocations as _circular markers_ (i.e., presenting **center and radius**).\r\n\r\n### How many instances of each type are there? \r\n\r\nThe dataset consists of 1,139 images containing 2,471 apples. \r\n\r\n### What data does each instance consist of? \r\n\r\nEach instance contains an 8-bits RGB image. Its corresponding annotation\r\nis found in the JSON files: each apple marker is composed by its center (cx, cy)\r\nand its radius (in pixels), as seen below:\r\n\r\n    \"gebler-003-06.jpg\": [\r\n      {\r\n        \"cx\": 116,\r\n        \"cy\": 117,\r\n        \"r\": 10\r\n      },\r\n      {\r\n        \"cx\": 134,\r\n        \"cy\": 113,\r\n        \"r\": 10\r\n      },\r\n      {\r\n        \"cx\": 221,\r\n        \"cy\": 95,\r\n        \"r\": 11\r\n      },\r\n      {\r\n        \"cx\": 206,\r\n        \"cy\": 61,\r\n        \"r\": 11\r\n      },\r\n      {\r\n        \"cx\": 92,\r\n        \"cy\": 1,\r\n        \"r\": 10\r\n      }\r\n    ],\r\n\r\n`Dataset.ipynb` is a Jupyter Notebook presenting a code example for reading \r\nthe data as a PyTorch's Dataset (it should be straightforward to adapt the code\r\nfor other frameworks as Keras/TensorFlow, fastai/PyTorch, Scikit-learn, etc.)\r\n\r\n### Is everything included or does the data rely on external resources? \r\n\r\nEverything is included in the dataset.\r\n\r\n### Are there recommended data splits or evaluation measures? \r\n\r\nThe dataset comes with specified train/test splits. The splits are found\r\nin lists stored as JSON files.\r\n\r\n  |         |  Number of images  | Number of annotated apples |\r\n  | ---     | ---                | ---                        |\r\n  |Training | 1,025              |  2,204                     | \r\n  |Test     |   114              |    267                     |  \r\n  |Total    | 1,139              |  2,471                     |             \r\n\r\n*Dataset recommended split.*\r\n\r\nStandard measures from the information retrieval and computer vision\r\nliterature should be employed: precision and recall, *F1-score* and\r\naverage precision as seen in [COCO](http://cocodataset.org)\r\nand [Pascal VOC](http://host.robots.ox.ac.uk/pascal/VOC).\r\n\r\n### What experiments were initially run on this dataset? \r\n\r\nThe first experiments run on this dataset are described in [*A methodology for detection \r\nand location of fruits in apples orchards from aerial images*](https://arxiv.org/abs/2110.12331)\r\nby Santos & Gebler (2021).\r\n\r\nData Collection Process \r\n-----------------------\r\n\r\n### How was the data collected?\r\n\r\nThe data employed in the development of the methodology came from two plots located\r\nat the Embrapa’s Temperate Climate Fruit Growing Experimental Station at Vacaria-RS\r\n(28°30’58.2”S, 50°52’52.2”W). Plants of \r\nthe varieties _Fuji_ and _Gala_ are present in the dataset, in equal proportions. The images were \r\ntaken during December 13, 2018, by an UAV (DJI Phantom 4 Pro) that flew over the rows of \r\nthe field at a height of 12 m. The images mix nadir and non-nadir views, allowing a more extensive view of the \r\ncanopies. A subset from the images was random selected and 256 × 256 pixels *patches* were extracted.\r\n\r\n### Who was involved in the data collection process?\r\n\r\nT. T. Santos and L. Gebler captured the images in\r\nfield. T. T. Santos performed the annotation.\r\n\r\n### How was the data associated with each instance acquired?\r\n\r\nThe circular markers were annotated using the [VGG Image Annotator (VIA)](https://www.robots.ox.ac.uk/~vgg/software/via/).\r\n\r\n**WARNING**: Find non-ripe apples in low-resolution images of orchards is a challenging task *even for humans*. ADD256 was annotated by a single \r\nannotator. So, users of this dataset should consider it a *noisy dataset*. \r\n\r\n\r\nData Preprocessing\r\n------------------\r\n\r\n### What preprocessing/cleaning was done? \r\n\r\nNo preprocessing was applied.\r\n\r\nDataset Distribution\r\n--------------------\r\n\r\n### How is the dataset distributed?\r\n\r\nThe dataset is [available at GitHub](https://github.com/thsant/add256).\r\n\r\n### When will the dataset be released/first distributed?\r\n\r\nThe dataset was released in October 2021.\r\n\r\n### What license (if any) is it distributed under?\r\n\r\nThe data is released under [**Creative Commons BY-NC 4.0 (Attribution-NonCommercial 4.0 International license)**](https://creativecommons.org/licenses/by-nc/4.0/). \r\nThere is a request to cite the corresponding paper if the dataset is used. For\r\ncommercial use, contact Embrapa Agricultural Informatics business office.\r\n\r\n### Are there any fees or access/export restrictions?\r\n\r\nThere are no fees or restrictions. For commercial use, contact Embrapa\r\nAgricultural Informatics business office.\r\n\r\nDataset Maintenance\r\n-------------------\r\n\r\n### Who is supporting/hosting/maintaining the dataset?\r\n\r\nThe dataset is hosted at Embrapa Agricultural Informatics and all\r\ncomments or requests can be sent to [Thiago T. Santos](https://github.com/thsant)\r\n(maintainer).\r\n\r\n### Will the dataset be updated?\r\n\r\nThere is no scheduled updates. \r\n\r\n### If others want to extend/augment/build on this dataset, is there a mechanism for them to do so?\r\n\r\nContributors should contact the maintainer by e-mail.\r\n\r\n### No warranty\r\n\r\nThe maintainers and their institutions are *exempt from any liability,\r\njudicial or extrajudicial, for any losses or damages arising from the\r\nuse of the data contained in the image database*.","description_withheld":null,"homepage":"https://github.com/thsant/add256","introduced_date":"2021-10-20","introduced_date_note":null,"introduced_by":null,"license":{"name":"Creative Commons BY-NCI 4.0","url":"https://github.com/thsant/add256/blob/main/LICENSE"},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Embrapa ADD 256"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}