Skip to content

himanshunaidu/covid_ldpcd

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

5 Commits
 
 
 
 
 
 
 
 
 
 

Repository files navigation

covid_ldpcp

LDPCP (Local Directional Pattern CoroNet Descriptor) Method for identifying COVID cases from Chest X-ray images

Involves 3 folders that form a cohesive feature extraction and classification system: Dataset, Feature_Extract and SVM

Dataset Folder

Contains functions for creating, analyzing, processing and augmenting the dataset being utilized. More details of the functions given in /Dataset/info.txt (To be added) /Dataset/config.py needs to be updated with the relevant details for use

The dataset created for the classification purpose is given in the following github repository: <to_be_added>

Feature_Extract Folder

Contains functions for extracting the dataset for neural network use, and the neural networks that were used for feature extraction. The features are saved in a MYSQL database Also contains some utility functions for getting training statistics of the neural network performance. More details of the functions given in /Feature_Extract/info.txt (To be added) /Feature_Extract/config.py needs to be updated with the relevant details for use

SVM Folder

Contains functions for extracting the saved features from MySQL, and also the SVM for final classification. More details of the functions given in /SVM/info.txt (To be added) /SVM/config.py needs to be updated with the relevant details for use

About

LDPCD: Local Directional Pattern with Convolutional Neural Network for COVID-19 Detection

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

 
 
 

Contributors

Languages