Update app.py

app.py

@@ -5,36 +5,34 @@ import gradio as gr
 import tempfile
 
 # Load the OCR model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2.0',
-                                         trust_remote_code=True,
-                                         token="<your_access_token>")
-model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2.0',
-                                 trust_remote_code=True,
-                                 low_cpu_mem_usage=True,
-                                 pad_token_id=tokenizer.eos_token_id).eval()
+tokenizer = AutoTokenizer.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True)
+model = AutoModel.from_pretrained('ucaslcl/GOT-OCR2_0', trust_remote_code=True, 
+                                  low_cpu_mem_usage=True, 
+                                  pad_token_id=tokenizer.eos_token_id).eval()
 
 # Check if GPU is available and use it, else use CPU
-# device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
-# model = model.to(device)  # Uncomment if you want to use GPU
+device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
+model = model.to(device)
 
 # Function to perform OCR on the image
 def perform_ocr(image):
+    # Save the image to a temporary file
     with tempfile.NamedTemporaryFile(suffix=".jpg", delete=False) as temp_file:
-        image.save(temp_file.name)
-        temp_image_path = temp_file.name
+        image.save(temp_file.name)  # Save the image
+        temp_image_path = temp_file.name  # Get the file path for the saved image
 
-        # Perform OCR using the model
-        result = model.chat(tokenizer, temp_image_path, ocr_type='ocr')
-        return result
+    # Perform OCR using the model
+    result = model.chat(tokenizer, temp_image_path, ocr_type='ocr')
+    return result
 
-# Create the Gradio interface
+# Create the Gradio interface using the new syntax
 interface = gr.Interface(
-    fn=perform_ocr,
-    inputs=gr.Image(type="pil"),
-    outputs=gr.Textbox(),
+    fn=perform_ocr, 
+    inputs=gr.Image(type="pil"),  # Updated to gr.Image
+    outputs=gr.Textbox(),         # Updated to gr.Textbox
     title="OCR Web App",
     description="Upload an image to extract text using the GOT-OCR2.0 model."
 )
 
 # Launch the app
-interface.launch()
+interface.launch()