IIIT-Synthetic-R-Manipuri

Language

Manipuri

Modality

Printed

Details Description

The IIIT-Synthetic-R-Manipuri dataset consists of synthetically created 6,37,200 word images along with their corresponding annotations. To create synthetic images, freely available Unicode fonts are used to render synthetic word images. The number of fonts used for Manipuri is 1108. We use ImageMagick, Pango, and Cairo tools to render text onto images. To mimic the typical document images, we generate images whose background is always lighter (higher intensity) than the foreground. Each word is rendered as an image using a random font. Font size, font styling such as bold and italic, foreground and background intensities, kerning, and skew are varied for each image to generate a diverse set of samples. A random one-fourth of the images are smoothed using a Gaussian filter with a standard deviation (𝜎) of 0.5. Finally, all the images are resized to a height of 32 while keeping the original aspect ratio. This dataset is divided into Training, Validation, and Test Sets consisting of 4,75,090, 67,870, and 1,35,740 word images and their corresponding ground truth transcriptions. There are 76,621 Manipuri words in the training set.

Training Set:

train.zip contains folder named “images” with 4,75,090 word level images, “train_gt.txt” containing image name and ground truth text separated by “Tab space” and “list_of_words.txt” contains list of 76,621 words in the Training set.

Validation Set:

val.zip contains folder named “images” with 67,870 word level images, and “val_gt.txt” containing image name and ground truth text separated by “Tab space”.

Test Set:

test.zip contains folder named “images” with 1,35,740 word level images, and “test_gt.txt” containing image name and ground truth text separated by “Tab space”.

Downloads

Train Test Val Logout

Sample Word Level Images from Training Set

Image Ground Truth
āĻšā§ƒāĻĻā§Ÿā§‡
āύāĻžāĻŽ
āĻ…āύ⧁āϰ⧇āĻžāϧ
āϏāĻŽāĻžāĻœā§‡
āϝ⧇āϤ⧇
āϰ⧇āϖ⧇
āĻŦāϞāĻŋ⧟āĻž
āϝāĻžā§Ÿ
āϏāĻŽāĻ¸ā§āϤ
āύāĻž,
āϚāĻŋāĻ āĻŋ
āĻšāĻžāϤ⧇
āĻĻ⧇āĻ–āϤ⧇
āĻ—āĻŋā§Ÿā§‡
āĻ—ā§‹āĻˇā§āĻ ā§€āϰ
āϏāĻœā§āϜāĻž
āĻšāĻžāϤāϤāĻžāϞāĻŋ
āĻŦāϞāϞ⧇āύ,
āϏāϤ⧇āϰ-āφāĻ āĻžāϰ
āϝāĻžāϗ⧇āϰ
āφāϰ
āĻ‹āĻ•ā§
āύāĻžāĻ“āύāĻŋ
āĻ•āĻĨāĻžāĻ“
āϏāĻžāĻ°ā§āĻŦāϭ⧌āĻŽāĻ¤ā§āĻŦ
āĻ—ā§ƒāĻšā§‡āϰ
āϘ⧁āϰ⧇
āϝāĻžā§Ÿ
āĻĻāĻžāϏ
āϝ⧇āĻŽāύ
āĨ¤
āϝāĻžā§Ÿ
āĻ­āĻžāχ
āĻ•āĻŋ
āĻ›āĻŋāϞ
?
āφāϛ⧇,
āĻ›āĻžāϤ⧁
āϗ⧇āϞ
āĻāϤ
āϏāĻŽāĻ¸ā§āϤ
āφāĻŽāĻŋ
āϗ⧇āϞ⧇āύ
āĻĢ⧁āϞ
āϛ⧋āĻŸâ€“āφāϗ⧇
āϖ⧁āĻŦ
āϏ⧇-āĻ–āĻŦāϰ
āϧ⧋āϤāĻŋ
āĻ—ā§‹āĻ›āĻžāύ⧋
āϟāĻŋāϟāĻŋāϰ
āĻ…āĻĨāĻŦāĻž
āĻŦāĻĻāĻŦ⧁
āĻĢ⧁āϟāĻŋā§Ÿā§‡
āϜāĻžāύāĻžā§Ÿ
āĻ•āĻžāϞ
āĻ•āĻžāϛ⧇
āĻĢ⧇āϞāϞāĻžāĻŽ
āĻŦāϞ⧇
āĻĻāĻŋāĻ˛ā§āϞāĻŋ
āφāϗ⧇āχ
āĻŦāĻ¨ā§āϧ⧁āϰ
āϞ⧀āύāĻž
āĻ•āĻŋ
āĨ¤
āύāĻž
āĻŦāĻŦāĻŋāϰ
āϭ⧁āϞ⧇
āĻ•āϰ⧇
āĻŦāĻŋ⧜āĻŦāĻŋ⧜
āĻŽā§āĻ–
āϤāĻžāϰ
?
āύāĻŋā§Ÿā§‡
āϝāĻžā§Ÿ
āϧāĻžāϰāĻŖāĻžā§Ÿ
āϤ⧈āϰāĻŋ
āύāĻžāĻŽ
āϏāĻŽā§Ÿā§‡
āϤāĻžāρāϰ
āĻĒāĻ°ā§āϝāĻ¨ā§āϤ
āχāĻšā§āϛ⧇āϰ
āĻĻ⧇āĻ–ā§‹-
āĻĨ⧇āϕ⧇
?
āĻĒāĻžāĻ āĻžāϤ⧇
āĻšā§‡āϏ⧇
āϤāĻŋāύāĻŋ
āĻŦ⧇āĻļ
āĻŽā§āϖ⧇
āϤāĻžāĻšāĻžāĻĻ⧇āϰ
āϏ⧇
āĻĻāĻžāĻĻāĻž
āϞāĻ‡ā§ŸāĻž
āĻļ⧁āχāϤ⧇
⧎
āύāĻŋāĻĻā§āϰāĻžā§Ÿ
āĻāϤ
āϘāϰ⧇
āĻŽāϤ⧋
āωāĻŽā§‡āĻļ

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