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| import gradio as gr | |
| import json | |
| from transformers import pipeline | |
| from pytesseract import pytesseract | |
| # Load the model | |
| nlp = pipeline( | |
| "document-question-answering", | |
| model="impira/layoutlm-document-qa", | |
| ) | |
| # Function to perform the question answering | |
| def perform_question_answering(image, question): | |
| answer = nlp(image, question) | |
| # Format the answer as JSON | |
| answer_json = json.dumps(answer, indent=4) | |
| return answer_json | |
| # Create the Gradio interface | |
| inputs = [ | |
| gr.inputs.Image(type="pil", label="Upload Image"), | |
| gr.inputs.Textbox(label="Question") | |
| ] | |
| outputs = gr.outputs.Textbox(label="Answer") | |
| iface = gr.Interface(fn=perform_question_answering, inputs=inputs, outputs="text") | |
| # Launch the Gradio interface | |
| iface.launch() | |