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This project is a Flask web application that integrates with TensorFlow a CNN model to be able to give predictions of two classes: "Normal" and "Tuberculosis". The user can upload their photo to be able to process it and also have a contrast enhancement filter applied with CLAHE.

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jdcarvajalc/pulmonary-tuberculosis-screening

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Machine learning model for screening cases of pulmonary tuberculosis using chest X-rays

Spanish version

Requirements

To run this project, you need the following requirements:

  • Python 3.8 or higher
  • TensorFlow 2.7 or higher
  • Flask 2.0 or higher

Installation

To install the requirements, you can run the following command in the terminal:

pip install -r requirements.txt

Execution

To run the application, you can run the following command in the terminal:

python main.py

The application will run on port 5000. To access it, you can open a web browser and enter the following address:

http://localhost:5000

Usage

To use the application, follow these steps:

  1. Click the "Upload Image" button.
  2. Select the image you want to process.
  3. Click the "Process Image" button.

The application will process the image and show you the model's prediction. It will also show you the original image and the processed image.

About

This project is a Flask web application that integrates with TensorFlow a CNN model to be able to give predictions of two classes: "Normal" and "Tuberculosis". The user can upload their photo to be able to process it and also have a contrast enhancement filter applied with CLAHE.

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