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import gradio as gr
import warnings
import os
import pix2struct, layoutlm, donut
warnings.filterwarnings('ignore')
def process_image_and_generate_output(image, model_selection, question):
result = ''
if image is None:
return "Please select an image", None
if model_selection == "LayoutLM":
result = layoutlm.get_result(image, question)
return result
if model_selection == 'Pix2Struct':
result = pix2struct.get_result(image, question)
return result
if model_selection == 'Donut':
result = donut.get_result(image, question)
return result
return result
sample_images = [
[os.path.join(os.path.dirname(__file__), "images/1.png"), "LayoutLM", "What is the NIC Code?"],
[os.path.join(os.path.dirname(__file__), "images/1.png"), "Pix2Struct", "What is the NIC Code?"],
[os.path.join(os.path.dirname(__file__), "images/1.png"), "Donut", "What is the NIC Code?"]
]
# Create a dropdown to select sample image
image_input = gr.Image(label="Upload Image", type='filepath')
# Create a dropdown to choose the model
model_selection_input = gr.Radio(["LayoutLM", "Pix2Struct", "Donut"],
label="Choose Model")
question_input = gr.Text(label="Question")
iface = gr.Interface(fn=process_image_and_generate_output,
inputs=[image_input, model_selection_input, question_input],
outputs=gr.Text(label="Result"),
allow_flagging='never',
examples=sample_images,
title="DocVQA Sanctum")
iface.launch()
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