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RpiTomato Dataset

25811
Tagagriculture
Taskobject detection
Release YearMade in 2021
LicenseCC BY 4.0
Download1 GB

Introduction #

Released 2021-10-25 ·Germano Moreira, Sandro Augusto Magalhães, Tiago Padilhaet al.

For RpiTomato Dataset: Greenhouse Tomatoes with Different Ripeness Stages, 60 tomatoes were selected in the greenhouse (Amorosa, Viana do Castelo, Portugal), each exhibiting various stages of ripeness. Comprehensive RGB images of these tomatoes were captured from diverse angles and perspectives. These images were taken using a Raspberry Pi Computer Model B camera, featuring a 12.3-megapixel sensor with a diagonal image size of 7.9 millimetres. A 6-millimeter wide-angle CS-mount lens with a 3-megapixel capacity was employed for image capture. In total, 258 images were acquired during this process.

This research work is conducted in the context of the ROBOCARE project. The primary objective of the project is to explore and develop intelligent precision robotic platforms designed for use in protected crop environments. The project’s overarching goal is to reduce the labour-intensive nature of agricultural tasks while simultaneously enhancing the ergonomic aspects of these operations. Such advancements are anticipated to lead to increased labour productivity and economic viability in crop cultivation. It is worth noting that the project team is actively engaged in the development of a specialized robot intended for harvesting tomatoes within greenhouse settings.

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Dataset LinkHomepageDataset LinkResearch Paper

Summary #

RpiTomato Dataset: Greenhouse Tomatoes with Different Ripeness Stages is a dataset for an object detection task. It is used in the agricultural industry.

The dataset consists of 258 images with 252 labeled objects belonging to 1 single class (tomato).

Images in the RpiTomato Dataset dataset have bounding box annotations. There are 6 (2% of the total) unlabeled images (i.e. without annotations). There are no pre-defined train/val/test splits in the dataset. The dataset was released in 2021 by the University of Porto, Portugal, Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (INESC TEC), Portugal, and University of Aveiro, Portugal.

Dataset Poster

Explore #

RpiTomato Dataset dataset has 258 images. Click on one of the examples below or open "Explore" tool anytime you need to view dataset images with annotations. This tool has extended visualization capabilities like zoom, translation, objects table, custom filters and more. Hover the mouse over the images to hide or show annotations.

OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
OpenSample annotation mask from RpiTomato DatasetSample image from RpiTomato Dataset
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Have a look at 258 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 1 annotation classes in the dataset. Find the general statistics and balances for every class in the table below. Click any row to preview images that have labels of the selected class. Sort by column to find the most rare or prevalent classes.

Search
Rows 1-1 of 1
Class
Images
Objects
Count on image
average
Area on image
average
tomato
rectangle
252
252
1
31.89%

Images #

Explore every single image in the dataset with respect to the number of annotations of each class it has. Click a row to preview selected image. Sort by any column to find anomalies and edge cases. Use horizontal scroll if the table has many columns for a large number of classes in the dataset.

Object distribution #

Interactive heatmap chart for every class with object distribution shows how many images are in the dataset with a certain number of objects of a specific class. Users can click cell and see the list of all corresponding images.

Class sizes #

The table below gives various size properties of objects for every class. Click a row to see the image with annotations of the selected class. Sort columns to find classes with the smallest or largest objects or understand the size differences between classes.

Search
Rows 1-1 of 1
Class
Object count
Avg area
Max area
Min area
Min height
Min height
Max height
Max height
Avg height
Avg height
Min width
Min width
Max width
Max width
tomato
rectangle
252
31.89%
64.56%
5.8%
930px
30.59%
3015px
99.18%
1905px
62.06%
769px
18.96%
2898px
71.45%

Spatial Heatmap #

The heatmaps below give the spatial distributions of all objects for every class. These visualizations provide insights into the most probable and rare object locations on the image. It helps analyze objects' placements in a dataset.

Spatial Heatmap

Objects #

Table contains all 252 objects. Click a row to preview an image with annotations, and use search or pagination to navigate. Sort columns to find outliers in the dataset.

Search
Rows 1-10 of 252
Object ID
Class
Image name
click row to open
Image size
height x width
Height
Height
Width
Width
Area
1
tomato
rectangle
t44-1.jpg
3040 x 4056
2394px
78.75%
2299px
56.68%
44.64%
2
tomato
rectangle
t52-2.jpg
3040 x 4056
1223px
40.23%
1556px
38.36%
15.43%
3
tomato
rectangle
t61-0.jpg
3040 x 4056
1713px
56.35%
2193px
54.07%
30.47%
4
tomato
rectangle
t59-4.jpg
3040 x 4056
2198px
72.3%
1778px
43.84%
31.69%
5
tomato
rectangle
t30-0.jpg
3040 x 4056
1942px
63.88%
2353px
58.01%
37.06%
6
tomato
rectangle
t56-2.jpg
3040 x 4056
2254px
74.14%
2299px
56.68%
42.03%
7
tomato
rectangle
t2_3.jpg
3040 x 4056
1510px
49.67%
1294px
31.9%
15.85%
8
tomato
rectangle
t20-3.jpg
3040 x 4056
1409px
46.35%
1767px
43.57%
20.19%
9
tomato
rectangle
t29-2.jpg
3040 x 4056
2067px
67.99%
2087px
51.45%
34.99%
10
tomato
rectangle
t43-1.jpg
3040 x 4056
1996px
65.66%
2386px
58.83%
38.62%

License #

RpiTomato Dataset: Greenhouse Tomatoes with Different Ripeness Stages is under CC BY 4.0 license.

Source

Citation #

If you make use of the RpiTomato data, please cite the following reference:

@dataset{moreira_germano_2021_5596363,
  author       = {Moreira, Germano and
                  Magalhães, Sandro Augusto and
                  Padilha, Tiago and
                  dos Santos, Filipe Neves and
                  Cunha, Mário},
  title        = {{RpiTomato Dataset: Greenhouse tomatoes with
                    different ripeness stages}},
  month        = oct,
  year         = 2021,
  publisher    = {Zenodo},
  doi          = {10.5281/zenodo.5596363},
  url          = {https://doi.org/10.5281/zenodo.5596363}
}

Source

If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:

@misc{ visualization-tools-for-rpi-tomato-dataset,
  title = { Visualization Tools for RpiTomato Dataset Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/rpi-tomato } },
  url = { https://datasetninja.com/rpi-tomato },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { jun },
  note = { visited on 2024-06-25 },
}

Download #

Dataset RpiTomato Dataset can be downloaded in Supervisely format:

As an alternative, it can be downloaded with dataset-tools package:

pip install --upgrade dataset-tools

… using following python code:

import dataset_tools as dtools

dtools.download(dataset='RpiTomato Dataset', dst_dir='~/dataset-ninja/')

Make sure not to overlook the python code example available on the Supervisely Developer Portal. It will give you a clear idea of how to effortlessly work with the downloaded dataset.

The data in original format can be downloaded here.

. . .

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