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

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

def remove_non_alphabet_chars(s):
    return re.sub('[^a-zA-Z]', '', s)


urls = [
    'https://fki.tic.heia-fr.ch/static/img/a01-122-02.jpg',
    'https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcSoolxi9yWGAT5SLZShv8vVd0bz47UWRzQC19fDTeE8GmGv_Rn-PCF1pP1rrUx8kOjA4gg&usqp=CAU',
    'https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRNYtTuSBpZPV_nkBYPMFwVVD9asZOPgHww4epu9EqWgDmXW--sE2o8og40ZfDGo87j5w&usqp=CAU',
    ]

for idx, url in enumerate(urls):
  image = Image.open(requests.get(url, stream=True).raw)
  image.save(f"image_{idx}.png")

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

    generated_ids = model.generate(pixel_values)

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

    generated_text = remove_non_alphabet_chars(generated_text)

    return generated_text

title = "Interactive demo: TrOCR - Handwriting Text Recognition"
description = "Short Demo for the handwriting recognition component of the Receipt OCR tool. Upload an image of handwriting which you want the model to read. I recommend screenshotting words on here: https://www.calligrapher.ai/"
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2109.10282'>TrOCR: Transformer-based Optical Character Recognition with Pre-trained Models</a> | <a href='https://github.com/microsoft/unilm/tree/master/trocr'>Github Repo</a></p>"
examples =[["image_0.png"], ["image_1.png"], ["image_2.png"]]

iface = gr.Interface(fn=process_image, 
                     inputs=gr.Image(type="pil"), 
                     outputs=gr.Textbox(),
                     title=title,
                     description=description,
                     article=article,
                     examples=examples)

iface.launch(debug=True, share=True)