|
""" |
|
Donut |
|
Copyright (c) 2022-present NAVER Corp. |
|
MIT License |
|
https://github.com/clovaai/donut |
|
""" |
|
import gradio as gr |
|
import torch |
|
from PIL import Image |
|
|
|
from donut import DonutModel |
|
|
|
def demo_process(input_img): |
|
global pretrained_model, task_prompt, task_name |
|
|
|
output = pretrained_model.inference(image=input_img, prompt=task_prompt)["predictions"][0] |
|
return output |
|
|
|
task_prompt = f"<s_cord-v2>" |
|
|
|
image = Image.open("./sample_image_cord_test_receipt_00012.png") |
|
image.save("cord_sample_receipt2.png") |
|
|
|
pretrained_model = DonutModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2") |
|
pretrained_model.encoder.to(torch.bfloat16) |
|
pretrained_model.eval() |
|
|
|
demo = gr.Interface( |
|
fn=demo_process, |
|
inputs= gr.inputs.Image(type="pil"), |
|
outputs="json", |
|
title=f"Donut 🍩 demonstration for `cord-v2` task as 🤗 Inference Endpoint", |
|
description="""This model is trained with 800 Indonesian receipt images of CORD dataset. <br> |
|
Demonstrations for other types of documents/tasks are available at https://github.com/clovaai/donut <br> |
|
More CORD receipt images are available at https://huggingface.co/datasets/naver-clova-ix/cord-v2 |
|
More details are available at: |
|
- Paper: https://arxiv.org/abs/2111.15664 |
|
- GitHub: https://github.com/clovaai/donut""", |
|
examples=[["cord_sample_receipt2.png"]], |
|
cache_examples=False, |
|
) |
|
demo.launch(server_name="0.0.0.0") |
