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Fruit_Vegetable_Recognition

★ 90 Open GitHub ↗

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

// repository documentation

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# Fruits🍍-Vegetable🍅 Classification

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)

## [Watch Tutorial for this project](https://youtu.be/cF6rMXZcuCs)
<img src="https://github.com/Spidy20/Fruit_Vegetable_Recognition/blob/master/yt_thumb.jpg">

## Usage:-

- Clone my repository.
- Open CMD in working directory.
- Run following command.

```
  pip install -r requirements.txt
  ```
- `Fruits_Vegetable_Classification.py` is the main Python file of Streamlit Web-Application. 
- `Fruit_Veg_Classification_Mobilenet.ipynb` is the Notebook file of the Training
- Dataset that I have used is [Fruit and Vegetable Image Recognition](https://www.kaggle.com/kritikseth/fruit-and-vegetable-image-recognition).
- To run app, write following command in CMD. or use any IDE.

```
  streamlit run Fruits_Vegetable_Classification.py
  ```

- For more explanation of this project see the tutorial on Machine Learning Hub YouTube channel.

## Screenshots

## Just follow☝️ me and Star⭐ my repository

# [Buy me a Coffee☕](https://www.buymeacoffee.com/spidy20)
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Fruit_Vegetable_Recognition

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