chocolate Computer Vision Project
nina
Updated 6 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)
* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise, upside-down
* Random Gaussian blur of between 0 and 0.5 pixels
* Random brigthness adjustment of between -16 and +16 percent
* Random exposure adjustment of between -6 and +6 percent
* Resize to 600x600 (Fit (white edges))
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Chocolates are annotated in YOLO v5 PyTorch format.
It includes 267 images.
The following augmentation was applied to create 5 versions of each source image:
The following pre-processing was applied to each image:
This dataset was exported via roboflow.ai on February 7, 2022 at 5:29 PM GMT
Valentine's Chocolates - v4 Fixed Annotations
blackchocolate
cheesechocolate
chocolate darkchocolate
milkchocolate
purplechocolate
redchocolate
resberrychocolate
whitechocolate
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LICENSE
CC BY 4.0 If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
chocolate-pywbw_dataset,
title = { chocolate Dataset },
type = { Open Source Dataset },
author = { nina },
howpublished = { \url{ https://universe.roboflow.com/nina-p99gp/chocolate-pywbw } },
url = { https://universe.roboflow.com/nina-p99gp/chocolate-pywbw },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { may },
note = { visited on 2024-11-14 },
}