This project is about Fruits-Vegetables classification application which is built using Deep Learning + Streamlit.

An AI model trained to determine the freshness of fruits and vegetables in an input image

https://fruktkartan.se frontend

Software de uma fruteira desenvolvida em Python

Fruits/Vegetable Seller Bot With Recommendation System Integrated (Using Apriori Algorithm) And MySql Database to record all the transactions and products/stock details.

Deploying FastAI model(Fruit Classifier) on an android and ios app using flutter

Suggesting a neural architecture for classifying dates images, using MobileNetV2 Transfer Learning

📟 A simple game of hangman with 3 categories and 3 levels settings.

A dynamic HTML, CSS, and JavaScript app that tracks users' fruit and vegetable intake and assists them in reaching their daily goals.

PET CV project. The application simulates the operation of smart scales, which themselves classify the product and offer options to the customer.

Fruits Vegetable Classifier with keggle datasets using CV

Fruit and Vegetables season predictions based on monthly weather data.

Página de apresentação do projeto de frutas e vegetais

Seasonal Food

A boring 33 class fruit classifier.

Explanation video (in tamil): https://drive.google.com/file/d/1zmp3H3qrtaqBX-LtkIgABci8QbNYwb8k/view?usp=sharing

FruitVeggieRecognizer is a machine learning-based project designed to identify and classify fruits and vegetables from images. This tool can be used for educational purposes, inventory management, or as a foundation for more advanced computer vision applications.

This project is focused on training a machine learning model to recognize various fruits and vegetables from images. The trained model can be used for applications such as inventory management, dietary tracking, or educational tools.

In this work, an automatic and reproducible methodology is proposed using computer vision techniques for sorting oranges by size and defects. Master thesis written in Spanish.

Fruits & vegetable