README.md

metadata

license: mit
title: cough-health-analyzer
sdk: gradio
emoji: 📊
colorFrom: green
colorTo: blue
thumbnail: >-
  https://cdn-uploads.huggingface.co/production/uploads/64981acf8126a020c2b83a2a/XMNXESRaeVAkZM5xR8Wbb.png
short_description: yipee

Cough Health Analyzer

A Gradio web application for analyzing cough audio to classify health status as 'healthy', 'COVID-19', or 'symptomatic'.

Features

• Upload Audio: Upload audio files containing coughs for analysis
• Record Audio: Record coughs directly in the browser for analysis
• Live Cough Detection: Stream audio in real-time to detect and analyze coughs
• API Access: Make API calls to the model for integration with other applications

Installation

1. Clone this repository:

git clone <repository-url>
cd <repository-directory>

2. Install the required dependencies:

pip install -r requirements-gradio.txt

3. Run the application:

python app.py

The application will be available at http://localhost:7860 by default.

Deploying to Hugging Face Spaces

To deploy this application to Hugging Face Spaces:

1. Create a new Space on Hugging Face
2. Choose "Gradio" as the SDK
3. Upload the following files to your Space:
   • app.py
   • cough_classification_model.pkl
   • requirements-gradio.txt (rename to requirements.txt)

The Space will automatically build and deploy your application.

Using the API

You can access the model via API calls. Here's an example using Python:

import requests
import json

# For file upload
files = {'audio': open('your_audio_file.wav', 'rb')}
response = requests.post('YOUR_GRADIO_URL/api/predict', files=files)
result = json.loads(response.content)
print(result)

Replace YOUR_GRADIO_URL with the URL of your deployed Gradio app.

Model Information

The model is a Random Forest classifier trained on audio features extracted from cough recordings. It classifies coughs into three categories:

• Healthy: Normal coughs from healthy individuals
• COVID-19: Coughs from individuals with COVID-19
• Symptomatic: Coughs from individuals with respiratory symptoms but not COVID-19

Live Audio Streaming and Cough Detection

The application includes a feature for streaming live audio and detecting coughs in real-time. When a cough is detected, it is automatically analyzed by the model.

This feature is useful for:

• Continuous health monitoring
• Automated cough counting and analysis
• Real-time health status updates

Limitations

• The model's accuracy depends on the quality of the audio recording
• Background noise can affect cough detection and classification
• The model should not be used as a substitute for professional medical diagnosis

License

[Specify your license here]