Main objective of this program is to classify Pneumonia with deep learning methods. Through this model i hope it can help health workers to automate process classifying Pneumonia throug chest ray image
My main method to make this is using a deep learning approach. I use Convolution Neural Nets to create the classifier and apply transfer learning with pre-trained models. I used Vgg-19 as the backbone fine-tune it with my own dataset (which I got from this Kaggle link). For the architecture, I used Pytorch as the base framework.
For installation options, currently I don't provide the docker image yet. But you can run this simply by clone or fork this repository.
- Clone this repository in your local with this command
git clone https://github.com/Clayrisee/PneumoniaNet.git - Install the requirement modules
pip install -r requirements.txt - If the module already satisfied, you can run the main.py
To use main.py, the model is in .pth format. My .pth saved model is in this folder.
-
See details arguments
python main.py -h -
Perform inference
python main.py -i <your_image_path> -v <y/n to visualize result>
| Input Image | Output |
|---|---|
 |
Pneumonia |
 |
Pneumonia |
 |
Normal |
I Also build another version of this project using ResNet50 backbone, you can visit this Repository