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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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## One-Step Respiratory Disease Classifier using Digital Stethoscope Sound - Readme
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This project provides a user-friendly Streamlit application to classify respiratory diseases using audio data from a digital stethoscope.
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**Features:**
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- Uploads a digital stethoscope audio file (WAV or MP3 format).
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- Extracts features from the audio using a pre-trained Audio Set Transfer (AST) model.
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- Predicts the most likely respiratory disease based on the extracted features using a deep learning model.
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- Displays informative messages and relevant images based on the prediction.
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**Requirements:**
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- Python 3.x
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- Streamlit (`pip install streamlit`)
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- TensorFlow (`pip install tensorflow`)
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- PyTorch (`pip install torch`)
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- torchaudio (`pip install torchaudio`)
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- transformers (`pip install transformers`)
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- Pillow (`pip install Pillow`)
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**Instructions:**
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1. Download the pre-trained AST model or Import it From the Hugging Face Website and disease classification model:
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- 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.
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- Download the disease classification model (`Model.h5`) and place it in the same directory as the AST model files.
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2. Update file paths in the code:
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- Unzip the Assets zip file
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- Modify the following paths to reflect your actual locations:
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- `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Model.h5'` (path to your disease classification model)
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- `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Assets\\Healthy.gif'` (path to the healthy image)
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- `'C:\\Users\\UserName\\Desktop\\RESPIRATORY-DISORDERS-.jpg'` (path to the generic respiratory issues image)
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- `'C:\\Users\\UserName\\Desktop\\RESPIRATORY DISEASE CLASSIFIER\\Assets\\COPD.png'` (path to the COPD info image )
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3. Run the application:
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- Open a terminal and navigate to the directory containing the script (`APP.py`).
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- Run the script using `streamlit run APP.py`.
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4. Use the application:
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- Upload an audio file from your digital stethoscope.
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- The application will display the predicted disease, relevant information, and images.
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- For COPD prediction, an additional information button can be clicked to display a detailed explanation.
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**Disclaimer:**
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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.
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