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covid-19-detection

Covid-19 Detection using Computer Vision, Machine Learning and Deep Learning

https://github.com/sarahajjibrahim/covid-19-detection

Science Score: 44.0%

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Keywords

ai cnn computer-vision covid-19 covid-19detection deep-learning machine-learning segmentation
Last synced: 7 months ago · JSON representation ·

Repository

Covid-19 Detection using Computer Vision, Machine Learning and Deep Learning

Basic Info
  • Host: GitHub
  • Owner: sarahajjibrahim
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 13.1 MB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Topics
ai cnn computer-vision covid-19 covid-19detection deep-learning machine-learning segmentation
Created over 3 years ago · Last pushed over 3 years ago
Metadata Files
Readme Citation

README.md

Covid-19 Detection using Deep Learning and Segmentation

How to run experiment: 1) Go to experiments folder 2) 3 files for segmentation (floodsegmentation.py, unetsegmentation.py, kmeans_segmentation.py ) 3) Choose the file you need for segmentation type to obtain segmented images 4) Segmented images are now ready to be classified 5) Test several DL and ML models to classify images and obtain results (classification.py)

Run WebApp (Using flask) to run experiment on single image using best model (classifies images using CNN): 1) On spyder, run app.py 2) Go to 127.0.0.1:5000/ 3) Choose an x-ray image 4) To check the behaviour of model against filters, choose a certain filter 5) Submit x-ray and filter to display result

For training U-net segmentation model on masks: 1) Download the CXRpng, masks and test folders from Lung segmentation from Chest X-Ray dataset 2) Copy the folders (CXRpng, masks, test) under \Experiments\data\unsegmented + unet masks\

For Data analysis and evaluation: 1) Download the Normal and Covid data without or without masks from COVID-19 Radiography Database 2) Copy the folders (COVID, Normal) under \Experiments\data\unsegmented\

Owner

  • Login: sarahajjibrahim
  • Kind: user

Citation (CITATION.cff) 

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: ' Covid-19-Detection-using-Deep-learning-and-Segmentation'
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Sara
    family-names: Al Hajj Ibrahim
    email: sarahhajibrahim1@gmail.com
    affiliation: Ontario tech university
    orcid: 'https://orcid.org/0000-0002-1794-5364'

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