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Create FastAPI app for deploying the HiFi GAN model

License: MIT License

Python 86.55% CSS 2.80% HTML 7.35% JavaScript 3.29%

ml_deployment's Introduction

Deploying AI Models on Cloud

The repo contains code for deploying a solution on AWS. We will be using Fast API for building the app.

Environment

  • fastapi==0.63.0
  • librosa==0.8.0
  • matplotlib==3.1.2
  • numpy==1.19.5
  • Pillow==8.1.0
  • pypesq==1.2.4
  • pystoi==0.3.3
  • starlette==0.13.6
  • torch==1.7.1
  • torchaudio==0.7.2
  • tqdm==4.47.0
  • uvicorn==0.13.3
  • Werkzeug==1.0.1

Project Description

The files and folders in this project and their usage is as follows.

  • models: Contains pytorch model architecture used in this project. These models are loaded and updated using the saved checkpoints to run inference.

  • sound_samples: Containes samples to run inference.

  • static: Contains static files, css files, images to display and js files.

  • templates: Contains templates for web app.

  • uploads: Folder to store uploaded files.

  • utils: Utility files for various supporting functions. Contains files for creating spectrograms, parameters for inference, data file to pre and post process audio files.

  • app.py app file

  • main.py File containing all of the functionality in the app. It imports certain other files to run properly.

  • Inference.py Script to run inference o the audio clips.

Local Run

To run the app locally run the following

git clone [email protected]:speakupai/ml_deployment.git
cd ml_deployment

$ python app.py

The app should look like this

ml_deployment's People

Contributors

taimur1871 avatar

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