freshness fruits and vegetables Object Detection Dataset and Pre-Trained Model by college

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Here are a few use cases for this project:

Grocery Store Quality Control: This computer vision model can be used by grocery stores and supermarkets to automatically check and sort fruits and vegetables according to their freshness levels. It can help to separate fresh produce from rotten ones, ensuring that consumers always have access to high quality produce.
Supply Chain Management: The model can help suppliers to visually inspect produce before it is sent to grocery stores or food processing companies. This will increase efficiency of the supply chain and reduce food waste.
Food Processing Plants: Food processing plants, particularly those that deal with canned fruits and vegetables, can use this model to sort and categorize fresh and rotten produce for different processing stages.
Agricultural Quality Inspection: Farms can employ this computer vision model to detect rotten fruits and vegetables right on the fields, allowing them to improve their quality control measures and avoid transporting rotten produce.
Personal Use - Health & Wellness Apps: This model can be incorporated into mobile applications, helping individuals at home to identify if their fruits and vegetables are still fresh and good for consumption. This will help people to consume healthier food and reduce food waste at home.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

YOLOv8

This project has a YOLOv8 model checkpoint available for inference with Roboflow Deploy. YOLOv8 is a new state-of-the-art real-time object detection model.

Cite This Project

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

@misc{
                            freshness-fruits-and-vegetables_dataset,
                            title = { freshness  fruits and vegetables Dataset },
                            type = { Open Source Dataset },
                            author = { college },
                            howpublished = { \url{ https://universe.roboflow.com/college-74jj5/freshness-fruits-and-vegetables } },
                            url = { https://universe.roboflow.com/college-74jj5/freshness-fruits-and-vegetables },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2023 },
                            month = { aug },
                            note = { visited on 2024-05-02 },
                            }