run.py

import gradio as gr
from deploy import ocr_btn
import pandas as pd


with gr.Blocks() as demo:
    image_input = gr.inputs.Image(label="Upload Image")
    webcam_input = gr.inputs.Image(label="Webcam", source="webcam")
    card_type_input = gr.inputs.Dropdown(["passport", "id_card"], label="Card Type", default="id_card")

    # column_names = ["name", "dob", "gender", "country", "doc_num"]
    # input_table = gr.inputs.Table(columns=column_names)
    data = {
    "Name": ["John", "Emma", "Michael"],
    "Age": [25, 30, 35],
    "Country": ["USA", "Canada", "UK"]
    }
    df = pd.DataFrame(data)

    table_input = gr.inputs.Table(headers=list(df.columns), row_count=len(df), default_data=df.values.tolist())


    # Define the output components
    json_output = gr.outputs.JSON(label="JSON Output")
    string_output = gr.outputs.Textbox(label="OCR Extracted Text")

    # Create the Gradio interface
    interface = gr.Interface(fn=ocr_btn, inputs=[card_type_input,image_input,webcam_input], outputs=[json_output, string_output])
    interface.launch(share=True)

if __name__ == "__main__":
    demo.launch()