Group

gradio_demo.py

@@ -285,17 +285,18 @@ with gr.Blocks(title="SUPIR") as interface:
     """)
     gr.HTML(title_html)
 
-    input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
-    prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
-    upscale = gr.Radio([1, 2, 3, 4, 5, 6, 7, 8], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
-    a_prompt = gr.Textbox(label="Image description",
-                          info="The prompt that describes what the image represents",
-                          value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
-                                'camera, hyper detailed photo - realistic maximum detail, 32k, Color '
-                                'Grading, ultra HD, extreme meticulous detailing, skin pore detailing, '
-                                'hyper sharpness, perfect without deformations.',
-                          lines=3)
-    a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
+    with gr.Group():
+        input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
+        prompt = gr.Textbox(label="Image description for LlaVa", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3, visible=False)
+        upscale = gr.Radio([1, 2, 3, 4, 5, 6, 7, 8], label="Upscale factor", info="Resolution x1 to x8", value=2, interactive=True)
+        a_prompt = gr.Textbox(label="Image description",
+                              info="Help the AI to understand what the image represents",
+                              value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
+                                    'camera, hyper detailed photo - realistic maximum detail, 32k, Color '
+                                    'Grading, ultra HD, extreme meticulous detailing, skin pore detailing, '
+                                    'hyper sharpness, perfect without deformations.',
+                              lines=3)
+        a_prompt_hint = gr.HTML("You can use a <a href='"'https://huggingface.co/spaces/MaziyarPanahi/llava-llama-3-8b'"'>LlaVa space</a> to auto-generate the description of your image.")
 
     with gr.Accordion("Pre-denoising (optional)", open=False):
         gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)
@@ -352,17 +353,18 @@ with gr.Blocks(title="SUPIR") as interface:
         with gr.Group():
             param_setting = gr.Radio(["Quality", "Fidelity"], interactive=True, label="Presetting", value="Quality")
             restart_button = gr.Button(value="Apply presetting")
-            
 
-    llave_button = gr.Button(value="Generate description by LlaVa (disabled)", visible=False)
-    diffusion_button = gr.Button(value="🚀 Upscale/Restore", variant = "primary", elem_id="process_button")
-    restore_information = gr.HTML(value="Restart the process to get another result.", visible=False)
-    result_slider = ImageSlider(label='Output', show_label=True, elem_id="slider1")
-    result_gallery = gr.Gallery(label='Output', show_label=True, elem_id="gallery1")
+    with gr.Group():
+        llave_button = gr.Button(value="Generate description by LlaVa (disabled)", visible=False)
+
+        diffusion_button = gr.Button(value="🚀 Upscale/Restore", variant = "primary", elem_id="process_button")
+
+        restore_information = gr.HTML(value="Restart the process to get another result.", visible=False)
+        result_slider = ImageSlider(label='Output', show_label=True, elem_id="slider1")
+        result_gallery = gr.Gallery(label='Output', show_label=True, elem_id="gallery1")
 
     with gr.Accordion("Feedback", open=True, visible=False):
-        fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1,
-                             interactive=True)
+        fb_score = gr.Slider(label="Feedback Score", minimum=1, maximum=5, value=3, step=1, interactive=True)
         fb_text = gr.Textbox(label="Feedback Text", value="", placeholder='Please enter your feedback here.')
         submit_button = gr.Button(value="Submit Feedback")
     with gr.Row():