Giter VIP home page Giter VIP logo

python-cnn-image-classification-fruits-360's Introduction

Python-CNN-Image-Classification

Fruits Detection using CNN model.

Dataset used :

Fruits 360

A dataset of images consists of various fruits and vegetables.

About Dataset

  • Total number of images: 90483.
  • Training set size: 67692 images (one fruit or vegetable per image).
  • Test set size: 22688 images (one fruit or vegetable per image).
  • Multi-fruits set size: 103 images (more than one fruit (or fruit class) per image)
  • Number of classes: 131 (fruits and vegetables).
  • Image size: 100x100 pixels.

Result

You can have this dataset from : https://www.kaggle.com/moltean/fruits

python-cnn-image-classification-fruits-360's People

Contributors

rafetkandar avatar

Stargazers

avatar

Watchers

avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.