Datasets:

Modalities:
Text
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Datasets
pandas
License:
parent_label
stringclasses
15 values
label
stringclasses
263 values
video_path
stringlengths
25
55
include_50
bool
2 classes
Colours
50. Yellow
Colours/50. Yellow/MVI_5194.MOV
false
Clothes
43. Pant
Clothes/43. Pant/MVI_3709.MOV
false
Jobs
99. Job
Jobs/99. Job/MVI_4796.MOV
false
Jobs
91. Priest
Jobs/91. Priest/MVI_5345.MOV
false
Adjectives
96. wet
Adjectives/96. wet/MVI_5246.MOV
false
Home
33. Pencil
Home/33. Pencil/MVI_8786.MP4
false
Places
23. Court
Places/23. Court/MVI_3531.MOV
false
Days_and_Time
77. Month
Days_and_Time/77. Month/MVI_5045.MOV
false
Electronics
59. Television
Electronics/59. Television/MVI_4557.MOV
false
Days_and_Time
72. Saturday
Days_and_Time/72. Saturday/MVI_9159.MP4
false
Society
12. Peace
Society/12. Peace/MVI_8960.MP4
false
Home
48. Card
Home/48. Card/MVI_4446.MOV
false
Seasons
62. Spring
Seasons/62. Spring/MVI_5425.MOV
false
Places
26. University
Places/26. University/MVI_3376.MOV
false
Places
35. Bank
Places/26. University/MVI_3376.MOV
false
Places
34. Ground
Places/34. Ground/MVI_3579.MOV
false
Animals
1. Dog
Animals/1. Dog/MVI_3030.MOV
false
Adjectives
3. happy
Adjectives/3. happy/MVI_9297.MOV
false
Society
20. Price
Society/20. Price/MVI_8986.MP4
false
People
74. Queen
People/74. Queen/MVI_4101.MOV
false
People
70. Grandmother
People/70. Grandmother/MVI_4087.MOV
false
Places
29. Library
Places/29. Library/MVI_3477.MOV
false
Adjectives
89. warm
Adjectives/89. warm/MVI_5141.MOV
false
Adjectives
89. warm
Adjectives/89. warm/MVI_9495.MOV
false
People
59. Daughter
People/59. Daughter/MVI_4934.MOV
false
Places
26. University
Places/26. University/MVI_3625.MOV
false
Adjectives
81. wide
Adjectives/81. wide/MVI_9390.MOV
false
Adjectives
2. quiet
Adjectives/2. quiet/MVI_9452.MOV
false
People
72. Wife
People/72. Wife/MVI_5265.MOV
false
Days_and_Time
70. Thursday
Days_and_Time/70. Thursday/MVI_4606.MOV
false
Days_and_Time
75. Yesterday
Days_and_Time/75. Yesterday/MVI_5037.MOV
false
Days_and_Time
76. Week
Days_and_Time/76. Week/MVI_4627.MOV
false
Home
39. Key
Home/39. Key/MVI_4408.MOV
false
Adjectives
30. dirty
Adjectives/30. dirty/MVI_9813.MOV
false
Places
29. Library
Places/29. Library/MVI_3479.MOV
false
Days_and_Time
74. Tomorrow
Days_and_Time/74. Tomorrow/MVI_4619.MOV
false
Adjectives
32. weak
Adjectives/32. weak/MVI_9695.MOV
false
Home
38. Page
Home/38. Page/MVI_4407.MOV
false
Adjectives
11. rich
Adjectives/11. rich/MVI_9599.MOV
false
Colours
47. Red
Colours/47. Red/MVI_4897.MOV
false
Home
38. Page
Home/38. Page/MVI_8809.MP4
false
Animals
4. Bird
Home/38. Page/MVI_8809.MP4
false
Electronics
53. Fan
Electronics/53. Fan/MVI_4534.MOV
false
Colours
51. Brown
Colours/51. Brown/MVI_5199.MOV
false
Places
31. Temple
Places/31. Temple/MVI_3565.MOV
false
People
67. Sister
People/67. Sister/MVI_3785.MOV
false
Animals
2. Cat
Animals/2. Cat/MVI_3090.MOV
false
Days_and_Time
66. Sunday
Days_and_Time/66. Sunday/MVI_5442.MOV
false
Means_of_Transportation
13. Bicycle
Means_of_Transportation/13. Bicycle/MVI_8588.MP4
false
Society
7. Team
Society/7. Team/MVI_8683.MP4
false
Home
29. Door
Home/29. Door/MVI_4367.MOV
false
Jobs
89. Waiter
Jobs/89. Waiter/MVI_4763.MOV
false
Animals
4. Bird
Animals/4. Bird/MVI_8568.MP4
false
People
65. Woman
People/65. Woman/MVI_5092.MOV
false
Society
17. Sport
Society/17. Sport/MVI_8978.MP4
false
People
61. Father
People/61. Father/MVI_4940.MOV
false
Clothes
41. Shirt
Clothes/41. Shirt/MVI_3847.MOV
false
Adjectives
80. tall
Adjectives/80. tall/MVI_9387.MOV
false
Pronouns
47. they
Pronouns/47. they/MVI_0027.MOV
false
Pronouns
45. we
Pronouns/45. we/MVI_9903.MOV
false
Places
32. Market
Places/32. Market/MVI_3406.MOV
false
Adjectives
35. heavy
Adjectives/35. heavy/MVI_9707.MOV
false
Clothes
39. Suit
Clothes/39. Suit/MVI_3841.MOV
false
Adjectives
88. cold
Adjectives/88. cold/MVI_9250.MOV
false
Adjectives
13. thick
Adjectives/13. thick/MVI_9608.MOV
false
Days_and_Time
83. Afternoon
Days_and_Time/83. Afternoon/MVI_9192.MP4
false
Means_of_Transportation
12. Truck
Means_of_Transportation/12. Truck/MVI_3149.MOV
false
People
67. Sister
People/67. Sister/MVI_8632.MP4
false
Places
32. Market
Places/32. Market/MVI_3324.MOV
false
Home
41. Letter
Home/41. Letter/MVI_9056.MP4
false
Jobs
98. Actor
Jobs/98. Actor/MVI_4516.MOV
false
Society
16. Gun
Society/16. Gun/MVI_4313.MOV
false
Jobs
93. Soldier
Jobs/93. Soldier/MVI_4497.MOV
false
Animals
1. Dog
Animals/1. Dog/MVI_4147.MOV
false
Days_and_Time
86. Time
Days_and_Time/86. Time/MVI_5524.MOV
false
Electronics
59. Television
Electronics/59. Television/MVI_5415.MOV
false
Days_and_Time
73. Today
Days_and_Time/73. Today/MVI_5471.MOV
false
Places
24. School
Places/24. School/MVI_3458.MOV
false
Adjectives
88. cold
Adjectives/88. cold/MVI_9332.MOV
false
People
81. Friend
People/81. Friend/MVI_5145.MOV
false
Places
19. House
Places/19. House/MVI_3350.MOV
false
Adjectives
12. poor
Adjectives/12. poor/MVI_9738.MOV
false
Adjectives
1. loud
Adjectives/1. loud/MVI_9536.MOV
false
Home
26. Bed
Home/26. Bed/MVI_8759.MP4
false
People
70. Grandmother
People/70. Grandmother/MVI_3795.MOV
false
Society
13. Attack
Society/13. Attack/MVI_4836.MOV
false
Means_of_Transportation
11. Car
Means_of_Transportation/11. Car/MVI_3174.MOV
false
Adjectives
22. loose
Adjectives/22. loose/MVI_9650.MOV
false
Jobs
97. Reporter
Jobs/97. Reporter/MVI_4512.MOV
false
Home
49. Ring
Home/49. Ring/MVI_4954.MOV
false
Home
31. Kitchen
Home/31. Kitchen/MVI_4897.MOV
false
Adjectives
1. loud
Adjectives/1. loud/MVI_5336.MOV
false
Home
31. Kitchen
Home/31. Kitchen/MVI_8779.MP4
false
Society
13. Attack
Society/13. Attack/MVI_8709.MP4
false
Clothes
44. Shoes
Clothes/44. Shoes/MVI_4010.MOV
false
Greetings
55. Thank you
Greetings/55. Thank you/MVI_9985.MOV
false
Jobs
94. Artist
Jobs/94. Artist/MVI_4779.MOV
false
Adjectives
2. quiet
Adjectives/2. quiet/MVI_9538.MOV
false
Colours
55. White
Colours/55. White/MVI_5209.MOV
false
Adjectives
78. long
Adjectives/78. long/MVI_5108.MOV
false

Dataset Card for INCLUDE

Dataset Summary

This dataset contains all videos in the INCLUDE dataset. As huggingface does not support video uploads at this time, the HF dataset contains metadata about each video such as the parent class, the video class, the path to the video and whether its a part of the INCLUDE-50 dataset (use include_50==True to get only include_50 videos). The videos themselves can be downloaded from Zenodo using the provided bash script.

Video download instructions

  1. Copy paste the following code into a file. Save the file as download_script.sh
#!/bin/bash

# The base URL for the API request
base_url="https://zenodo.org/api/records/4010759"

# Fetch the JSON metadata from Zenodo
response=$(curl -s "$base_url")

# Parse JSON to extract file URLs and names using jq
echo "$response" | jq -r '.files[] | .links.self + " " + .key' | while read -r file_url file_name
do
  # Use curl to download each file and save it with the respective name
  echo "Downloading $file_name from $file_url..."
  curl -o "$file_name" "$file_url"
  echo "$file_name downloaded."
done

echo "All files downloaded."

# Loop through all zip files in the current directory
for file in *.zip; do
    # Unzip each file into a directory with the same name as the zip file without the extension
    unzip "${file%.zip}"
done

echo "All files unzipped."
  1. Make the above file executable by opening a terminal window and running chmod +x download_script.sh
  2. Execute the above file in the directory you want to store the videos by running ./download_script.sh

Use the video_paths mentioned in the huggingface 'video_path' column to access the corresponding video.

Supported Tasks

This dataset was created for the goals of education and Isolated Sign Language Recognition, but may be used for other purposes.

Data Splits

The dataset is split into train and test splits as described in the paper

Dataset Creation

All details on dataset creation can be found in the INCLUDE paper.

Personal and Sensitive Information

These videos represent real people and their unique ways of communication. We urge all users of the dataset to respect their privacy - do not use these videos for any purposes that might infringe on the privacy or dignity of the individuals featured. Please ensure that the usage of these videos aligns with ethical standards and promotes understanding and inclusivity.

Discussion of Biases

India is a diverse country, and does not have one uniform sign language. The videos in this dataset were shot in Chennai, Tamil Nadu. However, they are not the only representation of "Indian Sign Language", as ISL varies from place to place across the country.

Citation Information

If you use this dataset, please cite the following work:

@inproceedings{sridhar_include:_2020, address = {New York, NY, USA}, series = {{MM} '20}, title = {{INCLUDE}: {A} {Large} {Scale} {Dataset} for {Indian} {Sign} {Language} {Recognition}}, isbn = {9781450379885}, shorttitle = {{INCLUDE}}, url = {https://doi.org/10.1145/3394171.3413528}, doi = {10.1145/3394171.3413528}, urldate = {2024-07-16}, booktitle = {Proceedings of the 28th {ACM} {International} {Conference} on {Multimedia}}, publisher = {Association for Computing Machinery}, author = {Sridhar, Advaith and Ganesan, Rohith Gandhi and Kumar, Pratyush and Khapra, Mitesh}, month = oct, year = {2020}, pages = {1366--1375}, }

Contributions

Thanks to @Rohith, @Gokul and @Advaith for adding this dataset. For any further questions, please reach out to advaithsridhar08@gmail.com

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