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Covid-19 detection in chest x-ray images using Convolution Neural Network.

License: MIT License

JavaScript 0.68% Python 1.02% CSS 0.42% HTML 0.87% Jupyter Notebook 97.00%

covid19-detection-using-chest-x-ray's Introduction

Covid19-Detection-Using-Chest-X-Ray

Using Convolutional Neural Network, I have implemented a classifier which detects whether the person is infected by Covid-19 or not.

Dataset

Positive Cases : https://github.com/ieee8023/covid-chestxray-dataset
Normal Cases : https://www.kaggle.com/paultimothymooney/chest-xray-pneumonia

Kaggle Notebook Link (Support Please 👍👍👍)

Link : https://www.kaggle.com/fusicfenta/covid-19-detection-using-chest-x-ray (If you liked this notebook then don't forget to give upvote on kaggle.)

Network Architecture

Model: "sequential_1"

Layer (type)                 Output Shape              Param #   
=================================================================
conv2d_1 (Conv2D)            (None, 222, 222, 32)      896      
conv2d_2 (Conv2D)            (None, 220, 220, 64)      18496     
max_pooling2d_1 (MaxPooling2 (None, 110, 110, 64)      0         
dropout_1 (Dropout)          (None, 110, 110, 64)      0         
conv2d_3 (Conv2D)            (None, 108, 108, 64)      36928     
max_pooling2d_2 (MaxPooling2 (None, 54, 54, 64)        0         
dropout_2 (Dropout)          (None, 54, 54, 64)        0         
conv2d_4 (Conv2D)            (None, 52, 52, 128)       73856     
max_pooling2d_3 (MaxPooling2 (None, 26, 26, 128)       0         
dropout_3 (Dropout)          (None, 26, 26, 128)       0         
conv2d_5 (Conv2D)            (None, 24, 24, 128)       147584    
max_pooling2d_4 (MaxPooling2 (None, 12, 12, 128)       0         
dropout_4 (Dropout)          (None, 12, 12, 128)       0       
flatten_1 (Flatten)          (None, 18432)             0         
dense_1 (Dense)              (None, 64)                1179712   
dropout_5 (Dropout)          (None, 64)                0         
dense_2 (Dense)              (None, 1)                 65        
=================================================================
Total params: 1,457,537
Trainable params: 1,457,537
Non-trainable params: 0

Accuracy

Confusion Matrix (0 for Positive and 1 for Negative cases)

Prediction of Covid-19 Positive Case

Prediction of Covid-19 Negative Case

Run

Steps to Execute the Project

1) Open CMD in directory where "app.py" is stored (Basically, Open CMD to this folder)

2) enter : python app.py

3) Open Specified URL which is given to you in CMD in running process

4) Upload Any Chest XRay Image and click "Predict"

5) To stop serving, press CTRL+C

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