Gather the Pre-denoising section

gradio_demo.py

@@ -290,15 +290,14 @@ with gr.Blocks(title="SUPIR") as interface:
         with gr.Column():
             with gr.Row(equal_height=True):
                 with gr.Column():
-                    gr.Markdown("<center>Input</center>")
-                    input_image = gr.Image(type="numpy", elem_id="image-input", height=400, width=400)
-                with gr.Column():
-                    gr.Markdown("<center>Pre-denoising Output</center>")
-                    denoise_image = gr.Image(type="numpy", elem_id="image-s1", height=400, width=400)
+                    input_image = gr.Image(label="Input", show_label=True, type="numpy", height=600, elem_id="image-input")
             prompt = gr.Textbox(label="Image description", value="", placeholder="A person, walking, in a town, Summer, photorealistic", lines=3)
 
-            with gr.Accordion("Pre-denoising options", open=False):
+            with gr.Accordion("Pre-denoising", open=False):
                 gamma_correction = gr.Slider(label="Gamma Correction", minimum=0.1, maximum=2.0, value=1.0, step=0.1)
+                denoise_button = gr.Button(value="Pre-denoise")
+                denoise_image = gr.Image(label="Denoised image", show_label=True, type="numpy", height=600, elem_id="image-s1")
+                denoise_information = gr.HTML(value="If present, the denoised image will be used for the restoration instead of the input image.")
 
             with gr.Accordion("LLaVA options", open=False, visible=False):
                 temperature = gr.Slider(label="Temperature", info = "lower=Always similar, higher=More creative", minimum=0., maximum=1.0, value=0.2, step=0.1)
@@ -306,7 +305,7 @@ with gr.Blocks(title="SUPIR") as interface:
                 qs = gr.Textbox(label="Question", info="Ask LLaVa what description you want", value="Describe the image and its style in a very detailed manner. The image is a realistic photography, not an art painting.", lines=3)
 
             with gr.Accordion("Restoring options", open=False):
-                upscale = gr.Slider(label="Upscale factor", info="Resolution x1, x2, x3, x4, x5, x6, x7 or x8", minimum=1, maximum=8, value=2, step=1)
+                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="Default Positive Prompt",
                                       info="Describe what the image represents",
                                       value='Cinematic, High Contrast, highly detailed, taken using a Canon EOS R '
@@ -361,12 +360,9 @@ with gr.Blocks(title="SUPIR") as interface:
                     
 
         with gr.Column():
-            gr.Markdown("<center>Restoring Output</center>")
-            result_slider = ImageSlider(label='Output', show_label=False, elem_id="slider1")
-            result_gallery = gr.Gallery(label='Output', show_label=False, elem_id="gallery1")
+            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.Row():
-                with gr.Column():
-                    denoise_button = gr.Button(value="Pre-denoise")
                 with gr.Column(visible=False):
                     llave_button = gr.Button(value="Generate description by LlaVa (disabled)")
                 with gr.Column():