gemstones detection Computer Vision Project
dsad
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)
* Equal probability of one of the following 90-degree rotations: none, clockwise, counter-clockwise
* Random Gaussian blur of between 0 and 1.5 pixels
* Random brigthness adjustment of between -25 and +25 percent
* Random brigthness adjustment of between -30 and +30 percent
* Random rotation of between -23 and +23 degrees
* Resize to 640x640 (Stretch)
* Salt and pepper noise was applied to 5 percent of pixels
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==============================
Crystals - v1 crystals_beta_1
For state of the art Computer Vision training notebooks you can use with this dataset,
Gemstones are annotated in YOLOv8 format.
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 6794 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 November 9, 2023 at 7:16 PM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
object visit https://github.com/roboflow/notebooks
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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{
gemstones-detection_dataset,
title = { gemstones detection Dataset },
type = { Open Source Dataset },
author = { dsad },
howpublished = { \url{ https://universe.roboflow.com/dsad-5afef/gemstones-detection } },
url = { https://universe.roboflow.com/dsad-5afef/gemstones-detection },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { mar },
note = { visited on 2024-12-26 },
}