Update

app.py

@@ -11,26 +11,29 @@ from PIL import Image
 
 from donut import DonutModel
 
+
 def demo_process(input_img):
     global pretrained_model, task_prompt, task_name
     # input_img = Image.fromarray(input_img)
-    output = pretrained_model.inference(image=input_img, prompt=task_prompt)["predictions"][0]
+    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_00004.png")
-# image.save("cord_sample_receipt1.png")
-# image = Image.open("./sample_image_cord_test_receipt_00012.png")
-# image.save("cord_sample_receipt2.png")
+task_prompt = f"<s_cord-v2>"
 
-pretrained_model = DonutModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
-# pretrained_model: DonutModel = DonutModel.from_pretrained("result", local_files_only=True)
+pretrained_model = DonutModel.from_pretrained(
+    "naver-clova-ix/donut-base-finetuned-cord-v2"
+)
+# pretrained_model: DonutModel = DonutModel.from_pretrained(
+#     "result", local_files_only=True
+# )
 pretrained_model.eval()
 
 demo = gr.Interface(
     fn=demo_process,
-    inputs= gr.inputs.Image(type="pil"),
+    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>
@@ -40,7 +43,10 @@ More CORD receipt images are available at https://huggingface.co/datasets/naver-
 More details are available at:
 - Paper: https://arxiv.org/abs/2111.15664
 - GitHub: https://github.com/clovaai/donut""",
-    examples=[["sample_image_cord_test_receipt_00004.png"], ["sample_image_cord_test_receipt_00012.png"]],
+    examples=[
+        ["sample_image_cord_test_receipt_00004.png"],
+        ["sample_image_cord_test_receipt_00012.png"],
+    ],
     cache_examples=False,
 )
 

receipts_app.py

@@ -20,15 +20,9 @@ def demo_process(input_img):
 # task_prompt = f"<s_cord-v2>"
 task_prompt = f"<s_receipts>"
 
-# 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")
+device = 'cpu' # 'cuda' if torch.cuda.is_available() else 'cpu'
 
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
-
-pretrained_model = DonutModel.from_pretrained("naver-clova-ix/donut-base-finetuned-cord-v2")
-# pretrained_model: DonutModel = DonutModel.from_pretrained("result", local_files_only=True)
+pretrained_model: DonutModel = DonutModel.from_pretrained("result", local_files_only=True)
 pretrained_model.to(device)
 pretrained_model.eval()