app.py

import gradio as gr
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
import requests
from PIL import Image

processor = TrOCRProcessor.from_pretrained("microsoft/trocr-base-printed")
model = VisionEncoderDecoderModel.from_pretrained("microsoft/trocr-base-printed")

def process_image(image):
    # prepare image
    pixel_values = processor(image, return_tensors="pt").pixel_values

    # generate (no beam search)
    generated_ids = model.generate(pixel_values)

    # decode
    generated_text = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]

    return generated_text

title = "Demo: TrOCR"

#css = """.output_image, .input_image {height: 600px !important}"""

iface = gr.Interface(
            fn=process_image, 
            inputs=gr.inputs.Image(type="pil"), 
            outputs=gr.outputs.Textbox(),
            title=title,
        )
iface.launch(debug=True)