Patient Monitoring System

Description

This is a patient monitoring system that uses deep learning techniques, such as ConvLSTM and LRCN, for video processing. The system has been deployed on a website using Streamlit, making it easy for medical staff to upload patient videos and receive result videos directly on the platform.

Styling Methods

The styling of the web application has been done using CSS and HTML. The CSS file is located in the static folder, while the HTML file is located in the templates folder.

To make changes to the styling, simply open the style.css file and edit the appropriate CSS rules. To make changes to the structure of the web application, open the index.html file and make the necessary changes to the HTML markup.

How to Use

1. Open the website.
2. Upload the patient video.
3. Wait for the video to be processed.
4. View the result video on the website.

Dependencies

This project requires the following dependencies:

• Python 3.7 or later
• TensorFlow
• Keras
• Streamlit

Installation

To install the dependencies, run the following command:

pip install -r requirements.txt

Usage

To run the web application, run the following command:

streamlit run app.py

Contributors

This project was developed by Kush Kapoor. If you would like to contribute to the project, please fork the repository and submit a pull request with your changes.