import re import gradio as gr import torch from transformers import DonutProcessor, VisionEncoderDecoderModel processor = DonutProcessor.from_pretrained("binhnase04854/donut-invoice-docvqa") model = VisionEncoderDecoderModel.from_pretrained("binhnase04854/donut-invoice-docvqa") device = "cuda" if torch.cuda.is_available() else "cpu" model.to(device) def process_document(image, question): # prepare encoder inputs pixel_values = processor(image, return_tensors="pt").pixel_values # prepare decoder inputs task_prompt = "{user_input}" prompt = task_prompt.replace("{user_input}", question) decoder_input_ids = processor.tokenizer(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("<[^>]*>", "", 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 DocVQA (document visual question answering). To use it, simply upload your image and type a question and click 'submit', or click one of the examples to load them. Read more at the links below." article = "

Donut: OCR-free Document Understanding Transformer | Github Repo

" sample_1 = "sample_1.jpeg" sample_2 = "sample_2.jpg" demo = gr.Interface( fn=process_document, inputs=["image", "text"], outputs="json", title="Demo: Donut 🍩 for DocVQA", description=description, article=article, enable_queue=True, examples=[ [sample_1, "What is total price?"], [sample_1, "How much is Sale VAT?"], [sample_1, "The bill's printing date?"], [sample_2, "What is total price?"], ], cache_examples=False) demo.launch()