Covid19-Detection-Using-Chest-X-Ray
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Covid-19 detection in chest x-ray images using Convolution Neural Network.
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