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Given were training set and a test set of images of 3 classes. Each image had a filename that is its unique id. The dataset comprised of 3 classes: COVID-19, Viral Pneumonia, and Normal. The goal of the project was to create a classifier capable of determining the class of the X-ray image.

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Mahi1901/Covid-19-Image-Classification

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Covid-19-Image-Classification

Given were training set and a test set of images of 3 classes. Each image had a filename that is its unique id. The dataset comprised of 3 classes: COVID-19, Viral Pneumonia, and Normal. The goal of the project was to create a classifier capable of determining the class of the X-ray image.

The project is inspired from a dataset from Kaggle.

The dataset (below 4 files) has to be downloaded from Olympus platform of Great Learning.  testimage.npy  testLabels.csv  trainimage.npy  trainLabels.csv

The context was to differentiate an X-ray image of a normal person from an unhealthy one and the ability to do so effectively meant better diagnosis.

Pre-processing of image data, visualization of images, building CNN and evaluation of the model were done.

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Given were training set and a test set of images of 3 classes. Each image had a filename that is its unique id. The dataset comprised of 3 classes: COVID-19, Viral Pneumonia, and Normal. The goal of the project was to create a classifier capable of determining the class of the X-ray image.

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