Rdemo / app.py
bentobytes's picture
Update app.py
1391eac
import re
import gradio as gr
import os
import json
import torch
from transformers import DonutProcessor, VisionEncoderDecoderModel
processor = DonutProcessor.from_pretrained("debu-das/donut_receipt_v2.29")
model = VisionEncoderDecoderModel.from_pretrained("debu-das/donut_receipt_v2.29")
device = "cuda" if torch.cuda.is_available() else "cpu"
model.to(device)
def process_document(image):
# prepare encoder inputs
pixel_values = processor(image, return_tensors="pt").pixel_values
# prepare decoder inputs
task_prompt = "<s_cord-v2>"
decoder_input_ids = processor.tokenizer(task_prompt, add_special_tokens=False, return_tensors="pt").input_ids
# generate answer
outputs = model.generate(
pixel_values.to(device),
decoder_input_ids=decoder_input_ids.to(device),
max_length=model.decoder.config.max_position_embeddings,
early_stopping=True,
pad_token_id=processor.tokenizer.pad_token_id,
eos_token_id=processor.tokenizer.eos_token_id,
use_cache=True,
num_beams=1,
bad_words_ids=[[processor.tokenizer.unk_token_id]],
return_dict_in_generate=True,
)
# postprocess
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
return processor.token2json(sequence)
demo = gr.Interface(
fn=process_document,
inputs="image",
outputs="json",
title="Demo: bentobytes for Receipt Parsing",
# description=description,
# article=article,
enable_queue=True,
examples=[["example.png"], ["example_1.png"],["example_2.png"], ["example_3.png"],["example_4.png"],["example_5.png"]],
cache_examples=False)
credentials_json = os.environ.get("CREDENTIALS")
if credentials_json is None:
print("Error: Please set the CREDENTIALS")
else:
credentials = json.loads(credentials_json)
if __name__ == "__main__":
demo.launch(auth=credentials)