https://github.com/codeamt/fastefficientcoviddeployment

A COVID-19 Chest XRay classification model deployed as a Streamlit app
https://github.com/codeamt/fastefficientcoviddeployment

Last synced: about 2 months ago
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A COVID-19 Chest XRay classification model deployed as a Streamlit app

• Host: GitHub
• URL: https://github.com/codeamt/fastefficientcoviddeployment
• Owner: codeamt
• Created: 2020-06-04T03:18:52.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2024-03-10T04:17:40.000Z (10 months ago)
• Last Synced: 2024-03-10T05:24:56.488Z (10 months ago)
• Language: Python
• Homepage:
• Size: 599 MB
• Stars: 1
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Fast Efficient Covidnet

Streamlit inference service deployment submodule for Udacity's Machine Learning Engineer Nanodegree program.

 







**DISCLAIMER:** THIS TOOL SHOULD NOT BE USED FOR MEDICAL DIAGNOSIS/REPLACE CONSULTING FROM A MEDICAL EXPERT AND SHOULD SERVE EDUCATIONAL PURPOSES ONLY.

## Related Repos/Files: 

- [All repos](https://github.com/codeamt/FastEfficientCovidNet)

- [Data Engineering](https://github.com/codeamt/mle-capstone-data)

- [Model Training](https://github.com/codeamt/mle-capstone-modeling)

- [Technical Report](https://github.com/codeamt/FastEfficientCovidNet/blob/master/report.pdf)

## About 

This is a Chest X-Ray (CXR) classification API. Building on previous work of [[1]](https://arxiv.org/pdf/2003.09871v3.pdf), the CovNet model for this ML project utilizes a pre-trained EfficientNet-b1 to extract features and a fine-tuned Fast.ai classifier to differentiate between infection classes (Normal, Viral Pneumonia, or COVID-19) with 95% test accuracy. 

 

## Build Instructions

### Locally

#### Clone this repo:

```

git clone https://github.com/codeamt/mle-capstone-deployment FastEfficientCovidnet 

cd FastEfficientCovidnet

```

#### Install packages:

```

cd src

pip3 -r install requirements.txt 

```

### or Dockerized:

```

docker build -f Dockerfile -t app:latest .

```

## Running 

### Locally:

From the src of the repo:

```

streamlit run app.py

```

### with Docker: 

```

docker run -p 8501:8501 app:latest

```

## References

[1](https://arxiv.org/pdf/2003.09871.pdf) COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases

from Chest X-Ray Image. L. Wang and A. Wong., 2020.