Public Mask Placement Computer Vision Project

jasperan

Updated 2 years ago

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Description

Intro

This Computer Vision repository contains images from several sources:

I've applied dataset augmentation with the following parameters, to better respond to different types of video feeds / security cameras and such:

  • Outputs per training example: 5
  • Grayscale: Apply to 10% of images
  • Blur: Up to 1.25px
  • Bounding Box: Noise: Up to 1% of pixels

I attempt to also have the model ready for B/W and grayscale security feeds, blur in case there are faces out of focus when trying to run inference in real time (not very high, only 1.25px), and 1% noise to adapt to live streams with a lower-than-average bitrate.

I've generated 5x images than the original dataset. In total, augmenting the data, I produced:

  • 10.000+ images in the training dataset (94%)
  • 478 images for validation (4%)
  • 216 images for testing (2%)

I aim to expand this dataset with YouTube videos in the future and add these samples into the testing set, to show how well the model performs with real-life examples.

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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{
                            public-mask-placement_dataset,
                            title = { Public Mask Placement Dataset },
                            type = { Open Source Dataset },
                            author = { jasperan },
                            howpublished = { \url{ https://universe.roboflow.com/jasperan/public-mask-placement } },
                            url = { https://universe.roboflow.com/jasperan/public-mask-placement },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { feb },
                            note = { visited on 2024-11-21 },
                            }
                        
                    

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