Update app.py

app.py

@@ -70,13 +70,13 @@ def initialize_models():
 @spaces.GPU(processing_timeout=180)
 def process_image(
     input_image,
-    prompt="clean, high-resolution, 8k",
+    prompt="clean, texture, high-resolution, 8k",
     negative_prompt="blurry, dotted, noise, raster lines, unclear, lowres, over-smoothed",
-    guidance_scale=1.0,
+    guidance_scale=2.5,
     conditioning_scale=1.0,
-    num_inference_steps=20,
-    seed=42,
-    upscale_factor=2,
+    num_inference_steps=6,
+    seed=None,
+    upscale_factor=4,
     color_fix_method="adain"
 ):
     global pipeline, generator, accelerator
@@ -190,13 +190,13 @@ demo = gr.Interface(
     fn=process_image,
     inputs=[
         gr.Image(label="Input Image"),
-        gr.Textbox(label="Prompt", value="clean, high-resolution, 8k"),
+        gr.Textbox(label="Prompt", value="clean, texture, high-resolution, 8k"),
         gr.Textbox(label="Negative Prompt", value="blurry, dotted, noise, raster lines, unclear, lowres, over-smoothed"),
-        gr.Slider(minimum=1.0, maximum=20.0, value=1.0, label="Guidance Scale"),
+        gr.Slider(minimum=1.0, maximum=20.0, value=2.5, label="Guidance Scale"),
         gr.Slider(minimum=0.1, maximum=2.0, value=1.0, label="Conditioning Scale"),
-        gr.Slider(minimum=1, maximum=50, value=20, step=1, label="Number of Steps"),
-        gr.Number(label="Seed", value=42),
-        gr.Slider(minimum=1, maximum=4, value=2, step=1, label="Upscale Factor"),
+        gr.Slider(minimum=1, maximum=50, value=6, step=1, label="Number of Steps"),
+        gr.Number(label="Seed", value=None),
+        gr.Slider(minimum=1, maximum=4, value=4, step=1, label="Upscale Factor"),
         gr.Radio(["none", "wavelet", "adain"], label="Color Fix Method", value="adain"),
     ],
     outputs=gr.Image(label="Generated Image"),