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KaraAgro AI Cocoa Dataset

119788482
Tagagriculture
Taskobject detection
Release YearMade in 2022
LicenseCC0 1.0
Download11 GB

Introduction #

Released 2022-07-29 ·Akogo Darlington, Nakatumba-Nabende Joyce, Christabel Acquayeet al.

The The KaraAgroAI Cocoa Dataset was created by authors to provide an open and accessible Cocoa dataset with well-labeled, sufficiently curated, and prepared Cocoa crop imagery that will be used by data scientists, researchers, the wider machine learning community, and social entrepreneurs within Sub-Saharan Africa and worldwide for various machine learning experiments so as to build solutions towards in-field Cocoa crop disease diagnosis and spatial analysis.

Note, similar The KaraAgroAI Cocoa Dataset datasets are also available on the DatasetNinja.com:

Motivation

Despite the fact that the agricultural sector is a national economic development priority in Sub-Saharan Africa, crop pests and diseases have been the challenge affecting major food security crops like cocoa. Cocoa Swollen Shoot Virus Disease (CSSVD) can substantially reduce yield by about 70% and even cause the death of cocoa trees within 2–3 years of infection at all stages of cocoa growth. It is one of the major disease problems affecting cocoa production in West Africa, most especially, in Ghana, Côte D’Ivoire, Nigeria, and Togo. Anthracnose, caused by Colletotrichum lupini, is the world’s most important lupin disease. The current state of data collection and crop pest and disease diagnosis is transitioning from disease identification using visible symptoms to the use of data-driven solutions applying machine learning and computer vision techniques. The image data previously collected is biased and not reproducible It has also not been sufficiently curated, prepared, and shared with the wider community.

Dataset Creation

The dataset was created to provide an open, well-labelled, sufficiently curated and accessible cocoa image dataset. Data scientists, researchers, and the broader machine learning community can use it for various machine learning experiments to build cocoa crop disease diagnosis and spatial analysis solutions. The dataset was created by a team of data scientists, agricultural scientists and agricultural officers from the KaraAgro AI Foundation, with support from the University of Ghana - Forest and Horticultural Crops Research Centre, Kade. It contains different instances that were captured across all the 7 cocoa growing regions of Ghana. The data associated with each instance was acquired from cocoa farms. These were different farms that were identified within the districts of the 7 cocoa growing prominent regions across the country. The data was collected using the KaraAgro AI - Collect app, a software program that uses a module that enables crowdsourcing of crop disease surveillance data from farms. This application was installed on Android devices. Data collectors used these Android devices to collect the cocoa data. This data was collected in a period of 4 months from September 2021 to December 2021. Each instance is associated with a class label based on the status of the crop i.e. diseased or healthy.

image

Cocoa Data Labels.

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Dataset LinkHomepageDataset LinkDatasheet

Summary #

The KaraAgroAI Cocoa Dataset is a dataset for an object detection task. It is used in the agricultural industry.

The dataset consists of 11978 images with 21712 labeled objects belonging to 8 different classes including cocoa-swollen-shoot-virus-leaf, anthracnose-leaf, healthy-cocoa-leaf, and other: healthy-cocoa-pod, anthracnose pod, cocoa-swollen-shoot-virus-pod, healthy-cocoa, and cocoa-swollen-shoot-virus-stem.

Images in the KaraAgro AI Cocoa dataset have bounding box annotations. There are 2 (0% of the total) unlabeled images (i.e. without annotations). There are no pre-defined train/val/test splits in the dataset. Alternatively, the dataset could be split into 3 health statuses: cssvd (5806 images), anthracnose (3215 images), and healthy (2957 images). The dataset was released in 2022 by the University of Ghana.

Here are the visualized examples for the classes:

Explore #

KaraAgro AI Cocoa dataset has 11978 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 KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
OpenSample annotation mask from KaraAgro AI CocoaSample image from KaraAgro AI Cocoa
👀
Have a look at 11978 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 8 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 1-8 of 8
Class
Images
Objects
Count on image
average
Area on image
average
cocoa-swollen-shoot-virus-leaf
rectangle
5638
8165
1.45
62.35%
anthracnose-leaf
rectangle
2996
4777
1.59
61.35%
healthy-cocoa-leaf
rectangle
2143
6130
2.86
57.7%
healthy-cocoa-pod
rectangle
842
2013
2.39
26.25%
anthracnose pod
rectangle
229
289
1.26
43.32%
cocoa-swollen-shoot-virus-pod
rectangle
116
158
1.36
16.84%
healthy-cocoa
rectangle
86
98
1.14
32.41%
cocoa-swollen-shoot-virus-stem
rectangle
58
82
1.41
38.69%

Co-occurrence matrix #

Co-occurrence matrix is an extremely valuable tool that shows you the images for every pair of classes: how many images have objects of both classes at the same time. If you click any cell, you will see those images. We added the tooltip with an explanation for every cell for your convenience, just hover the mouse over a cell to preview the description.

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 1-8 of 8
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
cocoa-swollen-shoot-virus-leaf
rectangle
8165
44.75%
100%
0%
1px
0.03%
4128px
100%
999px
64.75%
1px
0.08%
3096px
100%
healthy-cocoa-leaf
rectangle
6130
24.46%
99.52%
0%
2px
0.48%
3264px
100%
632px
48.45%
3px
0.72%
4026px
100%
anthracnose-leaf
rectangle
4777
42%
100%
0%
1px
0.08%
4119px
100%
1622px
65.57%
3px
0.31%
4127px
100%
healthy-cocoa-pod
rectangle
2013
11.62%
84.54%
0.06%
7px
1.68%
4052px
98.93%
668px
30.61%
14px
1.66%
2774px
90.94%
anthracnose pod
rectangle
289
36.21%
96.08%
0%
1px
0.08%
3903px
99.9%
1191px
60.14%
3px
0.31%
2716px
99.95%
cocoa-swollen-shoot-virus-pod
rectangle
158
13.09%
41.03%
1.02%
121px
9.57%
2549px
61.75%
655px
30.75%
100px
6.51%
1943px
75.98%
healthy-cocoa
rectangle
98
28.44%
74.45%
4.99%
754px
24.33%
3182px
97.49%
1755px
54.82%
480px
19.61%
3200px
98.04%
cocoa-swollen-shoot-virus-stem
rectangle
82
28.41%
79.26%
1.75%
243px
19.45%
1269px
100%
782px
68.11%
86px
8.98%
856px
79.26%

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 21712 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 21712
Object ID
Class
Image name
click row to open
Image size
height x width
Height
Height
Width
Width
Area
1
anthracnose pod
rectangle
20211027_142553-5_43_55_jpg.rf.2570f686362ad1de749687cb159b1166.jpg
2048 x 1536
1437px
70.17%
866px
56.38%
39.56%
2
anthracnose pod
rectangle
20211027_142553-5_43_55_jpg.rf.2570f686362ad1de749687cb159b1166.jpg
2048 x 1536
1179px
57.57%
908px
59.11%
34.03%
3
cocoa-swollen-shoot-virus-leaf
rectangle
IMG-20220206-WA0442-9_52_59.jpg
810 x 1080
674px
83.21%
1028px
95.19%
79.2%
4
cocoa-swollen-shoot-virus-leaf
rectangle
IMG_20211025_100832-11_8_19.jpg
3264 x 2448
1487px
45.56%
659px
26.92%
12.26%
5
healthy-cocoa-leaf
rectangle
IMG_20211018_114018_5-11_10_12.jpg
3264 x 2448
2734px
83.76%
1326px
54.17%
45.37%
6
healthy-cocoa-leaf
rectangle
IMG_20211018_114018_5-11_10_12.jpg
3264 x 2448
1515px
46.42%
1462px
59.72%
27.72%
7
healthy-cocoa-pod
rectangle
IMG_20211108_121424-11_5_16_jpg.rf.6b41ecadeefebb798c537dd35b24b2ea.jpg
416 x 416
276px
66.35%
271px
65.14%
43.22%
8
healthy-cocoa-leaf
rectangle
-5805312977254071302_121-16_20_18.jpg
1280 x 960
463px
36.17%
395px
41.15%
14.88%
9
healthy-cocoa-leaf
rectangle
-5805312977254071302_121-16_20_18.jpg
1280 x 960
733px
57.27%
353px
36.77%
21.06%
10
cocoa-swollen-shoot-virus-leaf
rectangle
IMG_20211023_134338-14_8_3.jpg
3264 x 2448
1586px
48.59%
567px
23.16%
11.25%

License #

The KaraAgroAI Cocoa Dataset is under CC0 1.0 license.

Source

Citation #

If you make use of the KaraAgro AI Cocoa data, please cite the following reference:

@data{DVN/BBGQSP_2022,
  author = {Darlington Akogo and Christabel Acquaye and Emmanuel Amoako and Jerry Buaba and Issah Samori and Joseph, Okani Honger and Stephen Torkpo and Markin, Grace and Bright, Hodasi and Lawrence Gyami Sarfoa},
  publisher = {Harvard Dataverse},
  title = {{The KaraAgroAI Cocoa Dataset}},
  year = {2022},
  version = {V6},
  doi = {10.7910/DVN/BBGQSP},
  url = {https://doi.org/10.7910/DVN/BBGQSP}
}

Source

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

@misc{ visualization-tools-for-kara-agro-ai-cocoa-dataset,
  title = { Visualization Tools for KaraAgro AI Cocoa Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/kara-agro-ai-cocoa } },
  url = { https://datasetninja.com/kara-agro-ai-cocoa },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { feb },
  note = { visited on 2024-02-24 },
}

Download #

Dataset KaraAgro AI Cocoa 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='KaraAgro AI Cocoa', 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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