Upload 7 files

README.md

@@ -1,10 +1,10 @@
 ---
-title: TomTestModel2024043001Space
-emoji: 📈
-colorFrom: red
-colorTo: green
+title: P9OcrAiV2BridSpace
+emoji: 👁
+colorFrom: blue
+colorTo: red
 sdk: gradio
-sdk_version: 4.28.3
+sdk_version: 4.23.0
 app_file: app.py
 pinned: false
 ---

app.py

@@ -0,0 +1,36 @@
+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
+    # input_img = Image.fromarray(input_img)
+    output = pretrained_model.inference(image=input_img, prompt=task_prompt)["predictions"][0]
+    return output
+task_name = "preparedFinetuneData_Bird"
+# task_name = "cord-v2"
+task_prompt = f"<s_{task_name}>"
+
+image = Image.open("inv87.jpg")
+image.save("inv87.jpg")
+image = Image.open("inv17.jpg")
+image.save("inv17.jpg")
+
+PATH = 'epochs30_base_on_donut_base/'
+pretrained_model = DonutModel.from_pretrained("Goodarc/TomTestModel2024043001",
+    ignore_mismatched_sizes=True)
+pretrained_model.eval()
+
+demo = gr.Interface(
+    fn=demo_process,
+    inputs= gr.Image(type="pil"),
+    outputs="json",
+    title=f"Goodarc p9 for `{task_name}` task, epochs30",
+    description="""Goodarc p9 v2 訓練. 
+    """,
+    examples=[["inv87.jpg"], ["inv17.jpg"]],
+    cache_examples=False,
+)
+demo.launch()

requirements.txt

@@ -0,0 +1,6 @@
+torch
+donut-python
+gradio
+transformers==4.25.1
+timm==0.5.4
+pytorch-lightning==1.6.4