Update app.py

app.py

@@ -1,10 +1,3 @@
-"""
-Donut
-Copyright (c) 2022-present NAVER Corp.
-MIT License
-
-https://github.com/clovaai/donut
-"""
 import gradio as gr
 import torch
 from PIL import Image
@@ -19,12 +12,12 @@ def demo_process(input_img):
 
 task_prompt = f"<s_cord-v2>"
 
-image = Image.open("./sample_image_cord_test_receipt_00004.png")
-image.save("cord_sample_receipt1.png")
-image = Image.open("./sample_image_cord_test_receipt_00012.png")
-image.save("cord_sample_receipt2.png")
+image = Image.open("./sample_1.jpg")
+image.save("cord_sample_1.png")
+image = Image.open("./sample_2.jpg")
+image.save("cord_sample_2.png")
 
-pretrained_model = DonutModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
+pretrained_model = DonutModel.from_pretrained("thinkersloop/donut-demo")
 pretrained_model.encoder.to(torch.bfloat16)
 pretrained_model.eval()
 
@@ -32,15 +25,9 @@ demo = gr.Interface(
     fn=demo_process,
     inputs= gr.inputs.Image(type="pil"),
     outputs="json",
-    title=f"Donut 🍩 demonstration for `cord-v2` task",
-    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_receipt1.png"], ["cord_sample_receipt2.png"]],
+    title=f"Transformers demo for `cord-v2` task",
+    description="""This model is trained with 30 driver's license images of CORD dataset. <br>""",
+    examples=[["cord_sample_1.png"], ["cord_sample_2.png"]],
     cache_examples=False,
 )