优化命名

app.py

@@ -102,8 +102,8 @@ def generate(
     width: int,
     height: int,
     scheduler: str,
-    upscaler_strength:float,
-    upscale_by:float,
+    opt_strength:float,
+    opt_scale:float,
     seed: int,
     randomize_seed: bool,
     guidance_scale: float,
@@ -123,7 +123,7 @@ def generate(
         progress(progress_value, desc=f"Image generating, {step + 1}/{num_inference_steps} steps")
         return callback_kwargs
     
-    optimizing_steps = int(num_inference_steps * upscaler_strength)
+    optimizing_steps = int(num_inference_steps * opt_strength)
     def callback2(pipe, step, timestep, callback_kwargs):
         progress_value = 0.6 + ((step+1.0)/optimizing_steps)*(0.4/1.0)
         progress(progress_value, desc=f"Image optimizing, {step + 1}/{optimizing_steps} steps")
@@ -164,14 +164,14 @@ def generate(
                 output_type="latent",
                 callback_on_step_end=callback1
             ).images
-        upscaled_latents = utils.upscale(latents, "nearest-exact", upscale_by)
+        upscaled_latents = utils.upscale(latents, "nearest-exact", opt_scale)
         images = upscaler_pipe(
                 prompt=prompt,
                 negative_prompt=negative_prompt,
                 image=upscaled_latents,
                 guidance_scale=guidance_scale,
                 num_inference_steps=num_inference_steps,
-                strength=upscaler_strength,
+                strength=opt_strength,
                 generator=generator,
                 output_type="pil",
                 callback_on_step_end=callback2
@@ -254,15 +254,15 @@ with gr.Blocks(css=custom_css).queue() as demo:
                     value=1216, 
                 )
             with gr.Row():
-                upscaler_strength = gr.Slider(
-                    label="Upscaler strength",
+                optimization_strength = gr.Slider(
+                    label="Optimization strength",
                     minimum=0,
                     maximum=1,
                     step=0.05,
                     value=0.55,  
                 )
-                upscale_by = gr.Slider(
-                    label="Upscale",
+                optimization_scale = gr.Slider(
+                    label="Optimization scale ratio",
                     minimum=1,
                     maximum=1.5,
                     step=0.1,
@@ -314,7 +314,7 @@ with gr.Blocks(css=custom_css).queue() as demo:
             prompt, negative_prompt,
             width, height, 
             scheduler,
-            upscaler_strength,upscale_by,
+            optimization_strength,optimization_scale,
             seed,randomize_seed,
             guidance_scale,num_inference_steps
             ],