resize qr code and add examples

app.py

@@ -62,15 +62,26 @@ def main():
         [Image.open(os.path.join(args.example_image_path, image_path))]
         for image_path in os.listdir(args.example_image_path)
     ]
-
-    description = """
-    Welcome to the Document Image Enhancement (DIE) model demo on Hugging Face!
-
-    This application showcases a specialized AI model by the Artificial Intelligence group at the Alfréd Rényi Institute of Mathematics, aimed at enhancing and restoring archival document images. This model removes domain-specific noise, preserving clarity and improving OCR accuracy, particularly for aged and historical documents.
-
-    Contact: [email protected]
-
-    """
+    
+    description = "Welcome to the Document Image Enhancement (DIE) model demo on Hugging Face!\n\n" \
+                  "" \
+                  "This interactive application showcases a specialized AI model developed by " \
+                  "the [Artificial Intelligence group](https://ai.renyi.hu) at the [Alfréd Rényi Institute of Mathematics](https://renyi.hu).\n\n" \
+                  "" \
+                  "Our DIE model is designed to enhance and restore archival and aged document images " \
+                  "by removing various types of degradation, thereby making historical documents more legible " \
+                  "and suitable for Optical Character Recognition (OCR) processing.\n\n" \
+                  "" \
+                  "The model effectively tackles 20-30 types of domain-specific noise found in historical records, " \
+                  "such as scribbles, bleed-through text, faded or worn text, blurriness, textured noise, " \
+                  "and unwanted background elements. " \
+                  "By applying deep learning techniques, specifically a U-Net-based architecture, " \
+                  "the model accurately cleans and clarifies text while preserving original details. " \
+                  "This improved clarity dramatically boosts OCR accuracy, making it an ideal " \
+                  "pre-processing tool in digitization workflows.\n\n" \
+                  "" \
+                  "If you’re interested in learning more about the model’s capabilities or potential applications, " \
+                  "please contact us at: [email protected].\n" 
 
     # Partial function for inference with model and device arguments
     partial_die_inference = partial(die_inference, die_model=die_model, device=args.device)
@@ -85,7 +96,7 @@ def main():
                 gr.Markdown(description)
             with gr.Column():
                 # Display QR code as an image in Gradio
-                gr.Image(value=Image.open("logo/qr-code.png"), label="QR Code")
+                gr.Image(value=Image.open("logo/qr-code.png").resize((200, 200)), label="QR Code")
 
         with gr.Row():
             with gr.Column():
@@ -95,7 +106,14 @@ def main():
 
             with gr.Column():
                 output_image = gr.Image(type="pil", label="Enhanced Document Image")
-
+        
+        # Display example images
+        gr.Examples(
+            examples=example_image_list,
+            inputs=[input_image],
+            label="Example Images",
+        )
+        
         # Button trigger for inference
         run_button.click(partial_die_inference, [input_image, num_iterations], output_image)