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app.py

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+import re
+from PIL import Image
+import gradio as gr
+
+import torch
+from transformers import DonutProcessor, VisionEncoderDecoderModel
+
+processor = DonutProcessor.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
+model = VisionEncoderDecoderModel.from_pretrained("naver-clova-ix/donut-base-finetuned-docvqa")
+
+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_docvqa><s_question>{user_input}</s_question><s_answer>"
+    question = "When is the coffee break?"
+    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(r"<.*?>", "", sequence, count=1).strip()  # remove first task start token
+    
+    return processor.token2json(sequence)
+
+image = Image.open("./example_1.png")
+image.save("example_1.png")
+
+demo = gr.Interface(
+    fn=process_document,
+    inputs= gr.inputs.Image(type="pil"),
+    outputs="json",
+    title=f"Interactive demo: Donut 🍩 for DocVQA",
+    description="""This model is fine-tuned on the DocVQA dataset. <br>
+Documentation: https://huggingface.co/docs/transformers/main/en/model_doc/donut
+Notebooks: https://github.com/NielsRogge/Transformers-Tutorials/tree/master/Donut
+
+More details are available at:
+- Paper: https://arxiv.org/abs/2111.15664
+- Original repository: https://github.com/clovaai/donut""",
+    examples=[["example_1.png"]],
+    cache_examples=False,
+)
+demo.launch()