What it does

Currently it classifies X-rays as Normal or Infected (Pneumonia) with 92% accuracy. Pneumonia/Normal dataset was used because the dataset was readily available online and the Pneumonia X-rays are very similar to covid-19 X-rays.

How I built it

Because the data was very limited, the X-ray images were first standardized and then augmented to produce as many copies (variant copies) as possible. This way the network could be trained far better. Speaking of the network, a convolutional neural network was implemented to pick up on key features and classify the X-rays.

Challenges I ran into

Arranging the data into it's labels and image contents

Creating batches of data

Accomplishments that I'm proud of

Successfully training the model and achieving 92% accuracy.

What I learned

Convolutional neural networks

Image Augmentation

What's next for Pneumonia(Covid)-Detector.io

Create a similar model but exactly for Covid-19 once the data becomes available.

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