import gradio as gr
import pydicom
import pandas as pd
from pathlib import Path
from io import BytesIO

def convert_dicom_to_tsv(dicom_file):
  dicom_file = pathlib.Path(__loader__).parent / "."
    # Read the DICOM file
    pydicom = dicom_data.dcmread(dicom_file)
    
    # Extract data elements from the DICOM file
    data_elements = {de.tag: (de.description(), de.value) for de in dicom_data}
    
    # Convert to DataFrame
    df = pd.DataFrame(list(data_elements.values()), columns=["Description", "Value"])
    
    # Convert DataFrame to TSV format and store in a buffer
    buffer = BytesIO()
    df.to_csv(buffer, sep='\t', index=False, encoding='utf-8')
    buffer.seek(0)
    
    return buffer

# Create a Gradio interface
app = gr.Interface(
        dicom_file = gr.File(type="df")
    b1 = gr.Button("Recognize Speech")
    b1.click(fn=convert_dicom_to_tsv, inputs=pydicom, outputs=file)
)
    

if __name__ == "__main__":
    app.launch(share=True)