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import re
import streamlit as st
from transformers import DonutProcessor, VisionEncoderDecoderModel
from datasets import load_dataset
import torch
import os
from PIL import Image
import PyPDF2
from pypdf.errors import PdfReadError
from pypdf import PdfReader
import pypdfium2 as pdfium
processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
device ="cpu"
model.to(device)
#create uploader
document = st.file_uploader(label="Upload the document you want to explore",type=["png",'jpg', "jpeg","pdf"])
question = st.text_input(str("Insert here you question?"))
if document == None:
st.write("Please upload the document in the box above")
else:
try:
PdfReader(document)
pdf = pdfium.PdfDocument(document)
page = pdf.get_page(0)
pil_image = page.render(scale = 300/72).to_pil()
#st.image(pil_image, caption="Document uploaded", use_column_width=True)
task_prompt = "<s_docvqa><s_question>{user_input}</s_question><s_answer>"
#question = "What's the total amount?"
prompt = task_prompt.replace("{user_input}", question)
decoder_input_ids = processor.tokenizer(prompt, add_special_tokens=False, return_tensors="pt").input_ids
pixel_values = processor(pil_image, return_tensors="pt").pixel_values
outputs = model.generate(
pixel_values.to(device),
decoder_input_ids=decoder_input_ids.to(device),
max_length=model.decoder.config.max_position_embeddings,
pad_token_id=processor.tokenizer.pad_token_id,
eos_token_id=processor.tokenizer.eos_token_id,
use_cache=True,
bad_words_ids=[[processor.tokenizer.unk_token_id]],
return_dict_in_generate=True,
)
sequence = processor.batch_decode(outputs.sequences)[0]
sequence = sequence.replace(processor.tokenizer.eos_token, "").replace(processor.tokenizer.pad_token, "")
sequence = re.sub(r"<.*?>", "", sequence, count=1).strip() # remove first task start token
st.image(pil_image,"Document uploaded")
st.write(processor.token2json(sequence))
print(processor.token2json(sequence))
except PdfReadError:
#image = Image.open(document)
#st.image(document, caption="Document uploaded", use_column_width=False)
# prepare decoder inputs
document = Image.open(document)
task_prompt = "<s_docvqa><s_question>{user_input}</s_question><s_answer>"
#question = "What's the total amount?"
prompt = task_prompt.replace("{user_input}", question)
decoder_input_ids = processor.tokenizer(prompt, add_special_tokens=False, return_tensors="pt").input_ids
pixel_values = processor(document, return_tensors="pt").pixel_values
outputs = model.generate(
pixel_values.to(device),
decoder_input_ids=decoder_input_ids.to(device),
max_length=model.decoder.config.max_position_embeddings,
pad_token_id=processor.tokenizer.pad_token_id,
eos_token_id=processor.tokenizer.eos_token_id,
use_cache=True,
bad_words_ids=[[processor.tokenizer.unk_token_id]],
return_dict_in_generate=True,
)
sequence = processor.batch_decode(outputs.sequences)[0]
sequence = sequence.replace(processor.tokenizer.eos_token, "").replace(processor.tokenizer.pad_token, "")
sequence = re.sub(r"<.*?>", "", sequence, count=1).strip() # remove first task start token
st.image(document,"Document uploaded")
st.write(processor.token2json(sequence))
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