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Black Pod Rot Dataset

243661769
Tagagriculture
Taskinstance segmentation
Release YearMade in 2021
Licenseunknown

Summary #

Dataset LinkHomepage

Black Pod Rot and Pod Borer on Cocoa Pod is a dataset for instance segmentation, semantic segmentation, and object detection tasks. Possible applications of the dataset could be in the agricultural industry.

The dataset consists of 2436 images with 9377 labeled objects belonging to 6 different classes including cocoa, cocoa_bbox, black_pod_rot, and other: black_pod_rot_bbox, pod_borer, and pod_borer_bbox.

Images in the Black Pod Rot dataset have pixel-level instance segmentation and bounding box annotations. Due to the nature of the instance segmentation task, it can be automatically transformed into a semantic segmentation task (only one mask for every class). All images are labeled (i.e. with annotations). There are 2 splits in the dataset: train (1930 images) and val (506 images). The dataset was released in 2021.

Dataset Poster

Explore #

Black Pod Rot dataset has 2436 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 Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
OpenSample annotation mask from Black Pod RotSample image from Black Pod Rot
πŸ‘€
Have a look at 2436 images
Because of dataset's license preview is limited to 12 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 6 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 1-6 of 6
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
cocoa_bboxβž”
rectangle
2434
3594
1.48
27.08%
cocoaβž”
polygon
2434
3595
1.48
20.81%
black_pod_rot_bboxβž”
rectangle
623
906
1.45
9.89%
black_pod_rotβž”
polygon
623
906
1.45
6.77%
pod_borer_bboxβž”
rectangle
105
188
1.79
7.1%
pod_borerβž”
polygon
105
188
1.79
4.38%

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 1-6 of 6
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
polygon
3595
14.07%
42.02%
0.04%
38px
3.52%
2160px
100%
843px
59.08%
19px
1.76%
1074px
72.59%
cocoa_bbox
rectangle
3594
18.72%
54.3%
0.06%
37px
3.43%
2160px
100%
843px
59.08%
19px
1.76%
1073px
72.69%
black_pod_rot_bbox
rectangle
906
6.89%
41.04%
0.05%
23px
2.13%
999px
92.5%
311px
28.5%
20px
1.85%
621px
57.5%
black_pod_rot
polygon
906
4.64%
32.84%
0.03%
23px
2.13%
1000px
92.59%
311px
28.51%
20px
1.85%
621px
57.5%
pod_borer_bbox
rectangle
188
3.98%
33.08%
0.07%
29px
2.69%
875px
88.02%
224px
21.28%
19px
1.76%
458px
42.41%
pod_borer
polygon
188
2.42%
24.51%
0.04%
30px
2.78%
875px
88.02%
224px
21.31%
19px
1.76%
459px
42.5%

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 9377 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 9377
Object ID
γ…€
Class
γ…€
Image name
click row to open
Image size
height x width
Height
γ…€
Height
γ…€
Width
γ…€
Width
γ…€
Area
γ…€
1βž”
cocoa
polygon
healthy_2997.jpg
1080 x 1080
992px
91.85%
441px
40.83%
28.75%
2βž”
cocoa_bbox
rectangle
healthy_2997.jpg
1080 x 1080
992px
91.85%
441px
40.83%
37.51%
3βž”
black_pod_rot
polygon
healthy_3086.jpg
1080 x 1080
171px
15.83%
88px
8.15%
0.93%
4βž”
black_pod_rot_bbox
rectangle
healthy_3086.jpg
1080 x 1080
171px
15.83%
88px
8.15%
1.29%
5βž”
cocoa
polygon
healthy_3086.jpg
1080 x 1080
1001px
92.69%
387px
35.83%
25.06%
6βž”
cocoa_bbox
rectangle
healthy_3086.jpg
1080 x 1080
1001px
92.69%
387px
35.83%
33.21%
7βž”
cocoa
polygon
healthy_977.jpg
2160 x 2160
1722px
79.72%
657px
30.42%
18.17%
8βž”
cocoa_bbox
rectangle
healthy_977.jpg
2160 x 2160
1722px
79.72%
657px
30.42%
24.25%
9βž”
cocoa
polygon
healthy_977.jpg
2160 x 2160
789px
36.53%
234px
10.83%
2.93%
10βž”
cocoa_bbox
rectangle
healthy_977.jpg
2160 x 2160
789px
36.53%
234px
10.83%
3.96%

License #

License is unknown for the Black Pod Rot and Pod Borer on Cocoa Pod dataset.

Source

Citation #

If you make use of the Black Pod Rot data, please cite the following reference:

@dataset{Black Pod Rot,
  author={Kenfack Anafack Alex},
  title={Black Pod Rot and Pod Borer on Cocoa Pod},
  year={2021},
  url={https://www.kaggle.com/datasets/kenfackbruno/black-pod-rot-and-pod-borer-on-cocoa-pod}
}

Source

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

@misc{ visualization-tools-for-black-pod-rot-dataset,
  title = { Visualization Tools for Black Pod Rot Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/black-pod-rot } },
  url = { https://datasetninja.com/black-pod-rot },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { mar },
  note = { visited on 2024-03-05 },
}

Download #

Please visit dataset homepage to download the data.

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Disclaimer #

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