update

app.py

@@ -38,7 +38,7 @@ ip_model = NestedAdapterInference(
 )
 
 # Generation defaults
-negative_prompt = "monochrome, lowres, bad anatomy, worst quality, low quality"
+negative_prompt = "bad anatomy, monochrome, lowres, worst quality, low quality"
 num_inference_steps = 30
 guidance_scale = 5.0
 
@@ -77,7 +77,7 @@ def generate_images(img1, img2, img3, prompt, w, num_samples, seed):
 # Gradio UI
 # ----------------------
 with gr.Blocks() as demo:
-    gr.Markdown("## Personalized Image Generation Demo")
+    gr.Markdown("## Nested Attention: Semantic-aware Attention Values for Concept Personalization")
     gr.Markdown(
         "Upload up to 3 reference images. "
         "Faces will be auto-aligned before personalization. Include the placeholder token (e.g., \\<person\\>) in your prompt, "
@@ -95,6 +95,18 @@ with gr.Blocks() as demo:
             num_samples_input = gr.Slider(minimum=1, maximum=6, step=1, value=4, label="Number of Images to Generate")
             seed_input = gr.Slider(minimum=-1, maximum=100000, step=1, value=-1, label="Random Seed (use -1 for random and up to 100000)")
             generate_button = gr.Button("Generate Images")
+
+            # Add examples
+            gr.Examples(
+                examples=[
+                    ["example_images/01.jpg", None, None, "a pop figure of a <person>, she stands on a white background", 2.0, 4, 1],
+                    ["example_images/01.jpg", None, None, "a watercolor painting of a <person>, closeup", 1.0, 4, 42],
+                    ["example_images/01.jpg", None, None, "a high quality photo of a <person> as a firefighter", 3.0, 4, 10],
+                ],
+                inputs=[img1, img2, img3, prompt_input, w_input, num_samples_input, seed_input],
+                label="Example Prompts"
+            )
+
         with gr.Column(scale=1):
             output_gallery = gr.Gallery(label="Generated Images", columns=3)