IRIS-Recognition 3 Computer Vision Project
HADJEM
Updated 9 months ago
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* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Random brigthness adjustment of between -1 and +1 percent
* Random rotation of between -1 and +1 degrees
* Random shear of between -1° to +1° horizontally and -0° to +0° vertically
* Resize to 640x640 (Stretch)
* annotate, and create datasets
* collaborate with your team on computer vision projects
* collect & organize images
* export, train, and deploy computer vision models
* understand and search unstructured image data
* use active learning to improve your dataset over time
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For state of the art Computer Vision training notebooks you can use with this dataset,
IRIS are annotated in YOLO v5 PyTorch format.
IRIS-0mp
IRIS-10mp
IRIS-12mp
IRIS-13mp
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IRIS-15mp
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IRIS-1mp
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IRIS-2mp
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IRIS-7mp
IRIS-8mp
IRIS-9mp
IRIS-Recognition - v15 V15PFE
IRIS-f2mp
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 2166 images.
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 March 31, 2024 at 8:17 AM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
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{
iris-recognition-3_dataset,
title = { IRIS-Recognition 3 Dataset },
type = { Open Source Dataset },
author = { HADJEM },
howpublished = { \url{ https://universe.roboflow.com/hadjem/iris-recognition-3 } },
url = { https://universe.roboflow.com/hadjem/iris-recognition-3 },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { mar },
note = { visited on 2024-12-28 },
}