Update app_turbo.py

app_turbo.py

@@ -126,6 +126,7 @@ def process(
     input_image: Image.Image,
     user_prompt: str,
     use_KDS: bool,
+    bandwidth: float,
     num_particles: int,
     positive_prompt: str,
     negative_prompt: str,
@@ -177,8 +178,8 @@ def process(
                     height=height, width=width,
                     guidance_scale=cfg_scale,  conditioning_scale=1,
                     start_point='lr', start_steps=999,ram_encoder_hidden_states=ram_encoder_hidden_states,
-                    latent_tiled_size=latent_tiled_size, latent_tiled_overlap=latent_tiled_overlap, use_KDS=use_KDS,
-                    num_particles=num_particles
+                    latent_tiled_size=latent_tiled_size, latent_tiled_overlap=latent_tiled_overlap, 
+                    use_KDS=use_KDS, bandwidth=bandwidth, num_particles=num_particles
                 ).images[0]
 
             if True:  # alpha<1.0:
@@ -210,8 +211,9 @@ with block:
     with gr.Row():
         with gr.Column():
             input_image = gr.Image(type="pil")
-            num_particles = gr.Slider(label="Num of Partickes", minimum=1, maximum=16, step=1, value=4)
-            use_KDS = gr.Checkbox(label="Use Kernel Density Steering")
+            num_particles = gr.Slider(label="Num of Partickes", minimum=1, maximum=16, step=1, value=10)
+            bandwidth = gr.Slider(label="Bandwidth", minimum=0.1, maximum=0.8, step=0.1, value=0.1)
+            use_KDS = gr.Checkbox(label="Use Kernel Density Steering")  
             run_button = gr.Button("Run")
             with gr.Accordion("Options", open=True):
                 user_prompt = gr.Textbox(label="User Prompt", value="")
@@ -220,8 +222,8 @@ with block:
                     label="Negative Prompt",
                     value="dotted, noise, blur, lowres, oversmooth, longbody, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality"
                 )
-                cfg_scale = gr.Slider(label="Classifier Free Guidance Scale (Set to 1.0 in sd-turbo)", minimum=1, maximum=1, value=1, step=0)
-                num_inference_steps = gr.Slider(label="Inference Steps", minimum=2, maximum=8, value=2, step=1)
+                cfg_scale = gr.Slider(label="Classifier Free Guidance Scale (Set to 1.0 in sd-turbo)", minimum=1, maximum=10, value=7.5, step=0)
+                num_inference_steps = gr.Slider(label="Inference Steps", minimum=2, maximum=100, value=50, step=1)
                 seed = gr.Slider(label="Seed", minimum=-1, maximum=2147483647, step=1, value=231)
                 sample_times = gr.Slider(label="Sample Times", minimum=1, maximum=10, step=1, value=1)
                 latent_tiled_size = gr.Slider(label="Diffusion Tile Size", minimum=128, maximum=480, value=320, step=1)
@@ -229,11 +231,82 @@ with block:
                 scale_factor = gr.Number(label="SR Scale", value=4)
         with gr.Column():
             result_gallery = gr.Gallery(label="Output", show_label=False, elem_id="gallery")
-
+            examples = gr.Examples(
+                examples=[
+                    [
+                        "preset/datasets/test_datasets/woman.png", 
+                        "",
+                        False,
+                        0.1,
+                        4,
+                        "clean, high-resolution, 8k, best quality, masterpiece",
+                        "dotted, noise, blur, lowres, oversmooth, longbody, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
+                        50,
+                        4,
+                        7.5,
+                        123,
+                        320,
+                        4,
+                        1,
+                    ],
+                    [
+                        "preset/datasets/test_datasets/woman.png", 
+                        "",
+                        True,
+                        0.1,
+                        4,
+                        "clean, high-resolution, 8k, best quality, masterpiece",
+                        "dotted, noise, blur, lowres, oversmooth, longbody, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
+                        50,
+                        4,
+                        7.5,
+                        123,
+                        320,
+                        4,
+                        1,
+                    ],
+                    [
+                        "preset/datasets/test_datasets/woman.png", 
+                        "",
+                        True,
+                        0.1,
+                        16,
+                        "clean, high-resolution, 8k, best quality, masterpiece",
+                        "dotted, noise, blur, lowres, oversmooth, longbody, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality",
+                        50,
+                        4,
+                        7.5,
+                        123,
+                        320,
+                        4,
+                        1,
+                    ],                    
+                ],
+                inputs=[
+                    input_image,
+                    user_prompt,
+                    use_KDS,
+                    bandwidth,
+                    num_particles,
+                    positive_prompt,
+                    negative_prompt,
+                    num_inference_steps,
+                    scale_factor,
+                    cfg_scale,
+                    seed,
+                    latent_tiled_size,
+                    latent_tiled_overlap,
+                    sample_times,
+                ],
+                outputs=[result_gallery],
+                fn=process,
+                cache_examples=True,
+            )
     inputs = [
         input_image,
         user_prompt,
         use_KDS,
+        bandwidth,
         num_particles,
         positive_prompt,
         negative_prompt,