Vegetable-classifier

Classifying the different kinds of vegetables using Convolutional Neural Network(CNN)

This application shows how to build a simple vegetable classifier using Convloutional Neural Network.

Introduction

This proposed work presents a novel approach to vegetable grading using deep convolution neural networks. The aim is to build an accurate, fast and reliable vegetable grading system, which is a vital element of an autonomous agricultural platform. Computer vision and pattern recognition are emerging fast and will continue to grow together with local feature detection methods. In the proposed work uses the Convolutional Neural Network (CNN) for object category recognition by extracting and learning the object. This proposed work applied a deep learning to vegetable object recognition, and divided into a N number of classes on the basis of characteristics. This proposed work will help to get single result from different vegetable vendors.

Requirements

• Opencv
• keras
• numpy
• Tkinter
• urllib
• IP cam application in ur phone

You can install all the required libraries by running the following command

pip install requiement.txt

Functionalities

• Pre processing the image
• CNN network build a classifier

Procedure

• Install the IP cam application in your mobile(those who are not having web cams)
• Run train_scr.py to train the model
• Enter URL generated by IP cam in gui_app.py file
• Run gui_app.py file to get a final prediction