modified: .gitignore

.gitignore

@@ -3,3 +3,4 @@ __pycache__/
 *.pyc
 heatmap/
 src/gradio_utils/gradio_outputs/
+src/gradio_utils/gradio_prompts/

app.py

@@ -519,6 +519,19 @@ def on_change(init_image, changed: gr.EventData):
 
 
 def create_demo(model_name: str, device: str = "cuda" if torch.cuda.is_available() else "cpu"):
+
+    description = r"""
+        <h3>Tips 🔔:</h3>
+        <ol>
+        <li>The app starts with default settings. To begin: <strong>(1) Click Reset Button.</strong> (2)Try the example image (at the bottom of the page) / Upload your own / Generate one with a target prompt.</li>
+        <li> Adaptive Attention (attn_guidance):  The option<i> Top activated attn-maps</i> is effective only when this editing technique is selected. </li>
+        <li> If you like this project, please ⭐ us on <a href='https://github.com/ZhouZJ-DL/Multi-turn_Consistent_Image_Editing' target='_blank'>GitHub</a> or cite our <a href='https://arxiv.org/abs/2505.04320' target='_blank'>paper</a>. Thanks for your support! </li>
+        </ol>
+    """
+    css = '''
+    .gradio-container {width: 85% !important}
+    '''
+
     is_schnell = model_name == "flux-schnell"
     
     # Pre-defined examples
@@ -528,9 +541,10 @@ def create_demo(model_name: str, device: str = "cuda" if torch.cuda.is_available
 
     with gr.Blocks() as demo:
         gr.Markdown(f"# Multi-turn Consistent Image Editing (FLUX.1-dev)")
-        
+        gr.Markdown(description)
         with gr.Row():
             with gr.Column():
+                reset_btn = gr.Button("Reset")
                 source_prompt = gr.Textbox(label="Source Prompt", value="(Optional) Describe the content of the uploaded image.")
                 target_prompt = gr.Textbox(label="Target Prompt", value="(Required) Describe the desired content of the edited image.")
                 with gr.Row():
@@ -555,7 +569,6 @@ def create_demo(model_name: str, device: str = "cuda" if torch.cuda.is_available
                     attn_guidance_start_block = gr.Slider(0, 18, 11, step=1, label="Top activated attn-maps", interactive=not is_schnell)
                     inject_step = gr.Slider(0, 15, 1, step=1, label="Number of inject steps")
                 output_image = gr.Image(label="Generated/Edited Image")
-                reset_btn = gr.Button("Reset")
                 example_image = gr.Image(label="example Image", visible=False, width=200)
 
         gallery.select(on_select, gallery, [init_image, source_prompt])