Sign language letter recognition Computer Vision Project
YOLO
Updated 7 months ago
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* 50% probability of horizontal flip
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Random Gaussian blur of between 0 and 1.25 pixels
* Random brigthness adjustment of between -25 and +25 percent
* Random rotation of between -5 and +5 degrees
* Random shear of between -5° to +5° horizontally and -5° to +5° vertically
* Randomly crop between 0 and 20 percent of the image
* Resize to 416x416 (Stretch)
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American Sign Language Letters - v1 v1
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It includes 1728 images.
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Letters are annotated in YOLO v5 PyTorch format.
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The following augmentation was applied to create 3 versions of each source image:
The following pre-processing was applied to each image:
This dataset was exported via roboflow.ai on October 20, 2020 at 4:54 PM GMT
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A description for this project has not been published yet.
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Cite This Project
LICENSE
CC BY 4.0 If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
sign-language-letter-recognition_dataset,
title = { Sign language letter recognition Dataset },
type = { Open Source Dataset },
author = { YOLO },
howpublished = { \url{ https://universe.roboflow.com/yolo-b5jrv/sign-language-letter-recognition } },
url = { https://universe.roboflow.com/yolo-b5jrv/sign-language-letter-recognition },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { apr },
note = { visited on 2024-11-28 },
}