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import re | |
import gradio as gr | |
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) | |
description = "Gradio Demo for Donut, an instance of `VisionEncoderDecoderModel` fine-tuned on CORD (document parsing). To use it, simply upload your image and click 'submit', or click one of the examples to load them. Read more at the links below." | |
article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2111.15664' target='_blank'>Donut: OCR-free Document Understanding Transformer</a> | <a href='https://github.com/clovaai/donut' target='_blank'>Github Repo</a></p>" | |
demo = gr.Interface( | |
fn=process_document, | |
inputs="image", | |
outputs="json", | |
title="Demo: Donut 🍩 for Document Parsing", | |
description=description, | |
article=article, | |
enable_queue=True, | |
examples=[["example.png"], ["example_1.png"],["example_2.png"], ["example_3.png"],["example_4.png"]], | |
cache_examples=False) | |
demo.launch() |