Korean Food Computer Vision Project

DongA University

Updated 10 months ago

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* Auto-orientation of pixel data (with EXIF-orientation stripping)
* Resize to 416x416 (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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Food are annotated in YOLOv8 format.
For state of the art Computer Vision training notebooks you can use with this dataset,
Korean Food_yolov5 - v3 ori
No image augmentation techniques were applied.
Roboflow is an end-to-end computer vision platform that helps you
The dataset includes 991 images.
The following pre-processing was applied to each image:
This dataset was exported via roboflow.com on November 24, 2023 at 7:19 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
Public Domain

If you use this dataset in a research paper, please cite it using the following BibTeX:

                        @misc{
                            korean-food-rgogz_dataset,
                            title = { Korean Food Dataset },
                            type = { Open Source Dataset },
                            author = { DongA University },
                            howpublished = { \url{ https://universe.roboflow.com/donga-university-1jxx6/korean-food-rgogz } },
                            url = { https://universe.roboflow.com/donga-university-1jxx6/korean-food-rgogz },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { nov },
                            note = { visited on 2024-09-24 },
                            }
                        
                    

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