My Graduation Project for Github graduation ceremony

My Final Project

Smart Doc, this project aims to develop an online Diagnosis system which could be used to diagnose Pneumonia using Chest X-Ray images and Malaria using blood-cells patches to detect if malaria causing pathogens are present in it or not. Also, a attempt was made to detect the COVID-19 positive patients using Chest X-Ray images.

Link to Code

sanidhyamangal / smart_doc_flask

A Flask based App for smart_doc

sanidhyamangal / covid-19_dataset

A repo containing trained models using mobile net and imagenet for covid-19 Xray images.

covid-19

This repo constitues of two different types of CNN following transerfer learning architecture, implemented in Tensorflow. The only difference between both the iterations of the models is, in one the base model of imagenet is freezed and is not allowed to be trained, but in other cases the model is allowed to be trained after 100th layer.

This is a repo which contains X-Ray images of COVID-19 Datset from ieee8023/covid-chestxray-dataset. The provided repo is an updated source of data from the cohen, it is structured in such a way that it can be directly feeded into any of the provided neural network using tensorflow's ImageGenerator and flow from directory feature.

Requirememts

tensorflow >= 2.0.0

How to run the project

For trainable base model:

python main.py

For non trainable base model:

python main_non.py

Visualizing the training results

tensorboard --logdir="."

Credit for the dataset goes to:

@article{cohen2020covid title={COVID-19…

View on GitHub

How I built it (what's the stack? did I run into issues or discover something new along the way?)

To build the above project I used following techstack

• Python
• TensorFlow
• Flask
• Docker
• MS Azure

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