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A repository with a demo on how to quickly deploy a machine learning model via FastAPI

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Model Quick Deploy

This repository was made for a talk given in 2021 at Drexel ADS

What is in this repository?

A repository with a demo on how to quickly deploy a machine learning model via FastAPI

This is a quick and dirty way to deploy a model via FastAPI both on your computer and on Google Colab using Ngrok. I would highly recommend not using this as is and doing some processing cleanup and adding authentication for your API at least.

Model being deployed: Intel's MiDaS from PyTorch Hub

How to use this repository?

You can either run the code for this deployment via Open In Colab

OR

Clone the repository and run:

  1. pip install -r requirements.txt
  2. uvicorn main:app

What does the model do?

MiDaS computes relative inverse depth from a single image. The repository provides multiple models that cover different use cases ranging from a small, high-speed model to a very large model that provide the highest accuracy. The models have been trained on 10 distinct datasets using multi-objective optimization to ensure high quality on a wide range of inputs. (credits: PyTorch hub page for MiDaS)

Link to original paper for the model

My curated list of courses

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