Car_damage Computer Vision Project
Car damage
Updated 10 months ago
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* 50% probability of horizontal flip
* 50% probability of vertical flip
* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Random brigthness adjustment of between -25 and +25 percent
* Random rotation of between -15 and +15 degrees
* Resize to 640x640 (Stretch)
* Salt and pepper noise was applied to 5 percent of pixels
* annotate, and create datasets
* collaborate with your team on computer vision projects
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Car-damage are annotated in YOLOv8 format.
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The dataset includes 24154 images.
The following augmentation was applied to create 3 versions of each source image:
The following pre-processing was applied to each image:
The following transformations were applied to the bounding boxes of each image:
This dataset was exported via roboflow.com on September 28, 2023 at 12:17 PM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
bamper car-damage - v2 2023-04-15 9:13pm
visit https://github.com/roboflow/notebooks
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{
car_damage-vujct_dataset,
title = { Car_damage Dataset },
type = { Open Source Dataset },
author = { Car damage },
howpublished = { \url{ https://universe.roboflow.com/car-damage-tvsxe/car_damage-vujct } },
url = { https://universe.roboflow.com/car-damage-tvsxe/car_damage-vujct },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { jan },
note = { visited on 2024-11-21 },
}