Sign Language detection Computer Vision Project

Sign Language Detection

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)
* annotate, and create datasets
* collaborate with your team on computer vision projects
* collect & organize images
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* understand unstructured image data
* use active learning to improve your dataset over time
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American Sign Language Letters - v1 v1
It includes 1728 images.
Letters are annotated in YOLO v7 PyTorch format.
Roboflow is an end-to-end computer vision platform that helps you
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.com on July 13, 2022 at 5:23 PM GMT

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-detection-uovoy_dataset,
                            title = { Sign Language detection Dataset },
                            type = { Open Source Dataset },
                            author = { Sign Language Detection },
                            howpublished = { \url{ https://universe.roboflow.com/sign-language-detection-qyvj2/sign-language-detection-uovoy } },
                            url = { https://universe.roboflow.com/sign-language-detection-qyvj2/sign-language-detection-uovoy },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2024 },
                            month = { apr },
                            note = { visited on 2024-11-13 },
                            }
                        
                    

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