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Pneumonia Detection

This project uses PyTorch to develop a deep learning model to detect pneumonia in chest X-ray images.

Requirements

To install the required packages, run the following command:

pip3 install -r requirements.txt

Dataset

The dataset used for this project is the Chest X-ray Pneumonia Detection Challenge dataset from Kaggle. You can download the dataset from here

Training the Model

To train the model, run the following command:

python3 train.py

This will train the model on the Chest X-ray Pneumonia Detection Challenge dataset.

Evaluating the Model

To evaluate the model, run the following command:

python3 evaluate.py

This will evaluate the model on a held-out test set of images.

Deploying the Model

To deploy the model, you can use the torch.jit.trace() function to trace the model and save it to a file. You can then load this file and use it to make predictions on new images. Usage

To use the model to make a prediction on a new image, run the following command:

python3 predict.py model_path image_path

This will print the probability of pneumonia in the image.

License

This project is licensed under the MIT License.

Contact

If you have any questions or suggestions, please feel free to contact me at [email protected].

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