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ArSL21L Dataset

142023286
Taggeneral
Taskobject detection
Release YearMade in 2022
LicenseCC BY 4.0
Download895 MB

Introduction #

Released 2022-02-11 Β·Ganzorig Batnasan, Munkhjargal Gochoo, Munkh Erdene Otgonboldet al.

The authors present their collected and annotated ArSL21L: Arabic Sign Language Letter Dataset consisting of 14202 images of 32 letter signs with various backgrounds collected from 50 people. They benchmarked the ArSL21L dataset on state-of-the-art object detection models, i.e., 4 versions of YOLOv5.

Motivation

For individuals with hearing loss (PwHL), establishing social connections with the mainstream population can be challenging. This often necessitates interactive computer systems capable of understanding sign language. With the growing popularity of Metaverse applications employing augmented reality (AR) and virtual reality (VR), there’s an opportunity to facilitate remote sign language instruction through avatars that mimic gestures, powered by AI (Artificial Intelligence) systems. While numerous methods and datasets exist for English sign language, resources for Arabic sign language are limited. Thus, the authors introduce the Arabic Sign Language Letters Dataset (ArSL21L), comprising 14,202 images depicting 32 letter signs against various backgrounds. These images were collected from 50 individuals and annotated for clarity and consistency.

image

Arabic sign language.

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Dataset LinkHomepageDataset LinkResearch PaperDataset LinkKaggle

Summary #

ArSL21L: Arabic Sign Language Letter Dataset is a dataset for an object detection task. It is used in the educational domain.

The dataset consists of 14202 images with 14208 labeled objects belonging to 32 different classes including thaa, al, dha, and other: fa, ghain, ha, khaa, la, meem, saad, seen, sheen, ta, thal, toot, yaa, haa, ain, jeem, ya, aleff, bb, kaaf, gaaf, taa, laam, zay, dhad, ra, nun, waw, and dal.

Images in the ArSL21L dataset have bounding box annotations. All images are labeled (i.e. with annotations). There are 2 splits in the dataset: train (9955 images) and val (4247 images). The dataset was released in 2022 by the United Arab Emirates University.

Dataset Poster

Explore #

ArSL21L dataset has 14202 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 ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
OpenSample annotation mask from ArSL21LSample image from ArSL21L
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Have a look at 14202 images
View images along with annotations and tags, search and filter by various parameters

Class balance #

There are 32 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 1-10 of 32
Class
γ…€
Images
γ…€
Objects
γ…€
Count on image
average
Area on image
average
thaaβž”
rectangle
451
451
1
14.06%
yaaβž”
rectangle
450
450
1
15.95%
tootβž”
rectangle
450
450
1
13.18%
thalβž”
rectangle
450
450
1
14.94%
taβž”
rectangle
450
450
1
14.16%
sheenβž”
rectangle
450
450
1
19.35%
seenβž”
rectangle
450
450
1
15.56%
saadβž”
rectangle
450
450
1
11.47%
meemβž”
rectangle
450
450
1
13.37%
laβž”
rectangle
450
450
1
15.07%

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 1-10 of 32
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
thaa
rectangle
451
14.06%
67.96%
1.75%
69px
16.59%
398px
95.67%
187px
44.96%
37px
8.89%
304px
73.08%
al
rectangle
451
21.03%
82.78%
1.85%
68px
16.35%
402px
96.63%
192px
46.24%
47px
11.3%
380px
91.35%
yaa
rectangle
450
15.95%
76.37%
1.83%
61px
14.66%
391px
93.99%
153px
36.72%
48px
11.54%
370px
88.94%
toot
rectangle
450
13.18%
81.23%
1.62%
66px
15.87%
398px
95.67%
163px
39.16%
37px
8.89%
358px
86.06%
thal
rectangle
450
14.94%
71.64%
2.36%
54px
12.98%
388px
93.27%
158px
37.96%
57px
13.7%
415px
99.76%
ta
rectangle
450
14.16%
61.43%
1.37%
64px
15.38%
406px
97.6%
187px
45.05%
33px
7.93%
289px
69.47%
sheen
rectangle
450
19.35%
83.37%
1.9%
70px
16.83%
408px
98.08%
191px
45.89%
47px
11.3%
376px
90.38%
seen
rectangle
450
15.56%
72.41%
1.78%
73px
17.55%
414px
99.52%
187px
44.89%
40px
9.62%
351px
84.38%
saad
rectangle
450
11.47%
71.99%
1.02%
45px
10.82%
358px
86.06%
128px
30.75%
36px
8.65%
369px
88.7%
meem
rectangle
450
13.36%
75.83%
1.5%
59px
14.18%
391px
93.99%
161px
38.7%
37px
8.89%
391px
93.99%

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 14208 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 14208
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”
nun
rectangle
1201_23_M_nun_5.jpg
416 x 416
163px
39.18%
128px
30.77%
12.06%
2βž”
seen
rectangle
1020_22_M_seen_4.jpg
416 x 416
240px
57.69%
175px
42.07%
24.27%
3βž”
ghain
rectangle
1201_23_M_ghain_2.jpg
416 x 416
248px
59.62%
276px
66.35%
39.55%
4βž”
yaa
rectangle
202_18_M_yaa_0.jpg
416 x 416
269px
64.66%
339px
81.49%
52.69%
5βž”
jeem
rectangle
1056_19_F_jeem_1.jpg
416 x 416
212px
50.96%
174px
41.83%
21.32%
6βž”
seen
rectangle
1007_29_M_seen_7.jpg
416 x 416
104px
25%
65px
15.62%
3.91%
7βž”
dal
rectangle
229_20_M_dal_7.jpg
416 x 416
171px
41.11%
164px
39.42%
16.21%
8βž”
thal
rectangle
202_18_M_thal_0.jpg
416 x 416
298px
71.63%
249px
59.86%
42.88%
9βž”
sheen
rectangle
202_18_M_sheen_0.jpg
416 x 416
353px
84.86%
250px
60.1%
51%
10βž”
toot
rectangle
1020_22_M_toot_5.jpg
416 x 416
239px
57.45%
197px
47.36%
27.21%

License #

ArSL21L: Arabic Sign Language Letter Dataset is under CC BY 4.0 license.

Source

Citation #

If you make use of the ArSL21L data, please cite the following reference:

@dataset{ArSL21L,
  author={Ganzorig Batnasan and Munkhjargal Gochoo and Munkh Erdene Otgonbold and Fady Alnajjar and Timothy Shih},
  title={ArSL21L: Arabic Sign Language Letter Dataset},
  year={2022},
  url={https://data.mendeley.com/datasets/f63xhm286w/1}
}

Source

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

@misc{ visualization-tools-for-arsl21l-dataset,
  title = { Visualization Tools for ArSL21L Dataset },
  type = { Computer Vision Tools },
  author = { Dataset Ninja },
  howpublished = { \url{ https://datasetninja.com/arsl21l } },
  url = { https://datasetninja.com/arsl21l },
  journal = { Dataset Ninja },
  publisher = { Dataset Ninja },
  year = { 2024 },
  month = { apr },
  note = { visited on 2024-04-14 },
}

Download #

Dataset ArSL21L 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='ArSL21L', 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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