Update app.py

app.py

@@ -1,33 +1,25 @@
+import gradio as gr
 from transformers import LayoutLMv3Processor, LayoutLMv3ForTokenClassification
 from PIL import Image
-import gradio as gr
 
-# Load processor and model
+# Load the processor and model
 processor = LayoutLMv3Processor.from_pretrained("microsoft/layoutlmv3-base")
 model = LayoutLMv3ForTokenClassification.from_pretrained("microsoft/layoutlmv3-base", num_labels=5)
 
-# Define function to process invoices
 def extract_invoice_data(image):
-    # Open image
+    # Open and preprocess the image
     image = Image.open(image).convert("RGB")
-
-    # Encode image
     encoding = processor(image, return_tensors="pt")
-    
-    # Perform inference
     outputs = model(**encoding)
     predictions = outputs.logits.argmax(-1).squeeze().tolist()
-    
-    # Return predictions (adjust to return structured data)
     return {"Predictions": predictions}
 
-# Create Gradio interface
+# Update Gradio interface
 interface = gr.Interface(
     fn=extract_invoice_data,
-    inputs=gr.inputs.Image(type="file"),
+    inputs=gr.Image(type="file"),
     outputs="json",
-    title="Invoice Data Extraction with LayoutLMv3"
+    title="Invoice Data Extraction"
 )
 
-# Launch Gradio app
 interface.launch()