Skip to content

Latest commit

 

History

History
169 lines (125 loc) · 5.76 KB

README.md

File metadata and controls

169 lines (125 loc) · 5.76 KB


API For Garbage Identifiers With Machine Learning Models

Table of Contents
  1. About The Project
  2. Getting Started
  3. Road Map

Project Home Page

This project is about identify the garbage with 6 categories ewest, metal, plastic, paper, non-recyclable and glass with Supervise machine learning models


Built With

  • Python
  • Fast_API
  • Tensorflow

## Getting Started

Here are the instructions about settings up project in local environment

Prerequisites

  • Python3.10

Installation

  1. Clone the repo

    git clone [email protected]:kumarsubedi93/garbage-detection.git
  2. Create python virtual environment

     python3 -m venv env
  3. Activate virtual environment

    source env/bin/activate
  4. Install all require packages

     pip install -r requirements.txt
  5. Get Machine learning models by following link and place inside ml-models/

    https://www.dropbox.com/s/jxlv29rh8otxrtx/garbage_model_weights.h5?dl=0
    
  6. Run project by using below command

     python main.py  
    
  7. The project up and running in localhost:9000 port & go to localhost:9000/docs to get API Endpoint.


Roadmap

  • Add More data on training models

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

  1. Fork the Project
  2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
  3. Commit your Changes (git commit -m 'Add some AmazingFeature')
  4. Push to the Branch (git push origin feature/AmazingFeature)
  5. Open a Pull Request

License

Distributed under the MIT License. See LICENSE.txt for more information.