README.md

---
title: VoXMED
emoji: 🐢
colorFrom: red
colorTo: yellow
sdk: streamlit
sdk_version: 1.37.1
app_file: app.py
pinned: false
---

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

## One-Step Respiratory Disease Classifier using Digital Stethoscope Sound - Readme

This project provides a user-friendly Streamlit application to classify respiratory diseases using audio data from a digital stethoscope. 

**Features:**

- Uploads a digital stethoscope audio file (WAV or MP3 format).
- Extracts features from the audio using a pre-trained Audio Set Transfer (AST) model.
- Predicts the most likely respiratory disease based on the extracted features using a deep learning model.
- Displays informative messages and relevant images based on the prediction.

**Requirements:**

- Python 3.x
- Streamlit (`pip install streamlit`)
- TensorFlow (`pip install tensorflow`)
- PyTorch (`pip install torch`)
- torchaudio (`pip install torchaudio`)
- transformers (`pip install transformers`)
- Pillow (`pip install Pillow`)

**Instructions:**

1. Download the pre-trained AST model or Import it From the Hugging Face Website and disease classification model:
    - Download the AST model files (e.g., `pytorch_model.bin`) from [https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593](https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593) (replace with the actual download URL). Place them in a directory.
    - Download the disease classification model (`Model.h5`) and place it in the same directory as the AST model files.
2. Update file paths in the code:
    - Unzip the Assets zip file
    - Modify the following paths to reflect your actual locations:
        - `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Model.h5'` (path to your disease classification model)
        - `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Assets\\Healthy.gif'` (path to the healthy image)
        - `'C:\\Users\\UserName\\Desktop\\RESPIRATORY-DISORDERS-.jpg'` (path to the generic respiratory issues image)
        - `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Assets\\COPD.png'` (path to the COPD info image )
3. Run the application:
    - Open a terminal and navigate to the directory containing the script (`APP.py`).
    - Run the script using `streamlit run APP.py`.
4. Use the application:
    - Upload an audio file from your digital stethoscope.
    - The application will display the predicted disease, relevant information, and images.
    - For COPD prediction, an additional information button can be clicked to display a detailed explanation.

**Disclaimer:**

This application is for informational purposes only and should not be used for medical diagnosis. Always consult a qualified healthcare professional for any health concerns.