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aisnap's Introduction

AISnap

AISnap is an easy-to-use web application that allows users to upload images and get instant classification results using machine learning. The project utilizes Vite and React for the frontend and Express.js for the backend.

Table of Contents

Getting Started

Follow these instructions to set up the AISnap project on your local machine for development and testing purposes.

Prerequisites

  • Node.js (version 14 or higher)
  • npm or yarn

Installation

  1. Clone the repository: 
    git clone https://github.com/dwk601/AISnap.git
  2. Install the dependencies: 
    cd AISnap
npm install

Running the Application

Follow these instructions to run the application on your local machine.

Frontend

  1. Start the frontend: 
    npm run dev
  2. Open the application in your browser at http://localhost:3000.

Backend

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

aisnap's People

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Create the Backend

Set up a node.js application to serve as the backend for your project. This will handle API requests and serve the pre-trained machine learning model for image classification.

Connect Frontend to Backend

Implement functionality in your React components to send the uploaded image to the node.js API endpoint and display the returned classification results on the frontend.

Test the Application

Ensure that your application is working correctly by uploading various images and verifying that the classification results are accurate and as expected.

Design the User Interface

Create the necessary components for your user interface, such as a file uploader for users to upload images, a display area to show the uploaded image, and an area to display the classification results.

Integrate the Machine Learning Model

Choose a pre-trained image classification model and load it into your node.js application using TensorFlow. Create an API endpoint that accepts an image as input and returns the predicted class and confidence score.

Deploy the Application

Deploy your backend and React frontend to a hosting service or cloud provider like Heroku

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