Introduction #
RuCode Hand Segmentation 2021 Dataset is a task from a Competition on semantic segmentation of hands that display various numbers from the ASL hard alphabet.
Homepage
KaggleSummary #
RuCode Hand Segmentation 2021 is a dataset for a semantic segmentation task. Possible applications of the dataset could be in the entertainment industry.
The dataset consists of 26026 images with 124920 labeled objects belonging to 6 different classes including palm, thumb_finger, pointer_finger, and other: middle_finger, fourth_finger, and little_finger.
Images in the RuCode Hand Segmentation 2021 dataset have pixel-level semantic segmentation annotations. There are 5206 (20% of the total) unlabeled images (i.e. without annotations). There are 2 splits in the dataset: train (20820 images) and test (5206 images). Also dataset includes letter tags. The dataset was released in 2021.
Explore #
RuCode Hand Segmentation 2021 dataset has 26026 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.
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.
Class ã…¤ | Images ã…¤ | Objects ã…¤ | Count on image average | Area on image average |
|---|---|---|---|---|
thumb_fingerâž” mask | 20820 | 20820 | 1 | 2.96% |
pointer_fingerâž” mask | 20820 | 20820 | 1 | 1.02% |
palmâž” mask | 20820 | 20820 | 1 | 3.54% |
middle_fingerâž” mask | 20820 | 20820 | 1 | 1.15% |
little_fingerâž” mask | 20820 | 20820 | 1 | 0.88% |
fourth_fingerâž” mask | 20820 | 20820 | 1 | 1.03% |
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.
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
thumb_finger mask | 20820 | 2.96% | 5.92% | 0.61% | 48px | 10% | 282px | 58.75% | 125px | 26.09% | 47px | 7.34% | 259px | 40.47% |
pointer_finger mask | 20820 | 1.02% | 2.16% | 0.17% | 25px | 5.21% | 183px | 38.12% | 73px | 15.13% | 34px | 5.31% | 189px | 29.53% |
palm mask | 20820 | 3.54% | 7.69% | 0.79% | 82px | 17.08% | 241px | 50.21% | 152px | 31.63% | 109px | 17.03% | 256px | 40% |
middle_finger mask | 20820 | 1.15% | 2.24% | 0.29% | 27px | 5.62% | 186px | 38.75% | 73px | 15.13% | 37px | 5.78% | 205px | 32.03% |
little_finger mask | 20820 | 0.88% | 1.69% | 0.19% | 23px | 4.79% | 137px | 28.54% | 55px | 11.48% | 41px | 6.41% | 163px | 25.47% |
fourth_finger mask | 20820 | 1.03% | 2.23% | 0.28% | 28px | 5.83% | 307px | 63.96% | 64px | 13.41% | 45px | 7.03% | 490px | 76.56% |
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.
Objects #
Table contains all 99864 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.
Object ID ã…¤ | Class ã…¤ | Image name click row to open | Image size height x width | Height ã…¤ | Height ã…¤ | Width ã…¤ | Width ã…¤ | Area ã…¤ |
|---|---|---|---|---|---|---|---|---|
1âž” | palm mask | e000095.png | 480 x 640 | 111px | 23.12% | 154px | 24.06% | 1.41% |
2âž” | thumb_finger mask | e000095.png | 480 x 640 | 111px | 23.12% | 97px | 15.16% | 2.08% |
3âž” | pointer_finger mask | e000095.png | 480 x 640 | 78px | 16.25% | 87px | 13.59% | 0.93% |
4âž” | middle_finger mask | e000095.png | 480 x 640 | 79px | 16.46% | 96px | 15% | 1.14% |
5âž” | fourth_finger mask | e000095.png | 480 x 640 | 67px | 13.96% | 95px | 14.84% | 1% |
6âž” | little_finger mask | e000095.png | 480 x 640 | 54px | 11.25% | 88px | 13.75% | 0.78% |
7âž” | palm mask | p000683.png | 480 x 640 | 151px | 31.46% | 189px | 29.53% | 2.56% |
8âž” | thumb_finger mask | p000683.png | 480 x 640 | 87px | 18.12% | 212px | 33.12% | 2.97% |
9âž” | pointer_finger mask | p000683.png | 480 x 640 | 83px | 17.29% | 120px | 18.75% | 1.3% |
10âž” | middle_finger mask | p000683.png | 480 x 640 | 49px | 10.21% | 83px | 12.97% | 0.9% |
License #
License is unknown for the RuCode Hand Segmentation 2021 dataset.
Citation #
If you make use of the RuCode Hand Segmentation 2021 data, please cite the following reference:
@dataset{RuCode Hand Segmentation,
author={Tatiana Gaintseva},
title={RuCode Hand Segmentation},
year={2021},
url={https://www.kaggle.com/competitions/rucode-hand-segmentation/}
}
If you are happy with Dataset Ninja and use provided visualizations and tools in your work, please cite us:
@misc{ visualization-tools-for-rucode-hand-segmentation-dataset,
title = { Visualization Tools for RuCode Hand Segmentation 2021 Dataset },
type = { Computer Vision Tools },
author = { Dataset Ninja },
howpublished = { \url{ https://datasetninja.com/rucode-hand-segmentation-2021 } },
url = { https://datasetninja.com/rucode-hand-segmentation-2021 },
journal = { Dataset Ninja },
publisher = { Dataset Ninja },
year = { 2024 },
month = { nov },
note = { visited on 2024-11-01 },
}Download #
Please visit dataset homepage to download the data.
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