fruit_fresh or not Computer Vision Project
AI
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)
* Resize to 640x640 (Stretch)
* annotate, and create datasets
* annotate, and create datasets * collect & organize images
* annotate, and create datasets * understand and search unstructured image data
* 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,
For state of the art Computer Vision training notebooks you can use with this dataset, visit https://github.com/roboflow/notebooks
Fruits Detection and Quality Analysis - v3 2023-06-07 11:04pm
Fruits are annotated in YOLO v5 PyTorch format.
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 2256 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 February 8, 2024 at 4:14 PM GMT
To find over 100k other datasets and pre-trained models, visit https://universe.roboflow.com
fresh frsh images not fresh
object visit https://github.com/roboflow/notebooks
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Cite This Project
LICENSE
MIT If you use this dataset in a research paper, please cite it using the following BibTeX:
@misc{
fruit_fresh-or-not_dataset,
title = { fruit_fresh or not Dataset },
type = { Open Source Dataset },
author = { AI },
howpublished = { \url{ https://universe.roboflow.com/ai-arydf/fruit_fresh-or-not } },
url = { https://universe.roboflow.com/ai-arydf/fruit_fresh-or-not },
journal = { Roboflow Universe },
publisher = { Roboflow },
year = { 2024 },
month = { feb },
note = { visited on 2024-11-24 },
}