Update app.py

app.py

@@ -35,7 +35,10 @@ pipe = StableDiffusionControlLoraV3Pipeline.from_pretrained(
     unet=unet
 )
 
+# Performance optimizations
 pipe.scheduler = UniPCMultistepScheduler.from_config(pipe.scheduler.config)
+pipe.enable_attention_slicing()
+pipe.enable_vae_slicing()
 
 pipe.load_lora_weights(
     "models",
@@ -66,7 +69,7 @@ def get_canny_image(image, low_threshold=100, high_threshold=200):
     canny_image = np.stack([canny_image] * 3, axis=-1)
     return Image.fromarray(canny_image)
 
-@spaces.GPU(duration=300)
+@spaces.GPU(duration=180)  # Reduced to 3 minutes
 def generate_image(input_image, prompt, negative_prompt, guidance_scale, steps, low_threshold, high_threshold, seed, progress=gr.Progress()):
     if input_image is None:
         raise gr.Error("Please provide an input image!")
@@ -88,8 +91,8 @@ def generate_image(input_image, prompt, negative_prompt, guidance_scale, steps,
             image = pipe(
                 prompt=prompt,
                 negative_prompt=negative_prompt,
-                num_inference_steps=int(steps),  # Convert to int
-                guidance_scale=float(guidance_scale),  # Convert to float
+                num_inference_steps=int(steps),
+                guidance_scale=float(guidance_scale),
                 image=canny_image,
                 extra_condition_scale=1.0,
                 generator=generator
@@ -107,14 +110,14 @@ def random_image_click():
         return Image.open(image_path)
     return None
 
-# Example data
+# Example data with reduced steps
 examples = [
     [
         "conditions/example1.jpg",
         "a futuristic cyberpunk city",
         "blurry, bad quality",
         7.5,
-        50,
+        25,  # Reduced steps
         100,
         200,
         42
@@ -124,7 +127,7 @@ examples = [
         "a serene mountain landscape",
         "dark, gloomy",
         7.0,
-        40,
+        25,  # Reduced steps
         120,
         180,
         123
@@ -136,7 +139,8 @@ with gr.Blocks() as demo:
     gr.Markdown(
         """
         # Control LoRA v3 Demo
-        ⚠️ Warning: This is a demo of Control LoRA v3. Please be aware that generation can take several minutes. 
+        ⚠️ Warning: This is a demo of Control LoRA v3. Generation might take a few minutes.
+        For better results with ZeroGPU, it's recommended to use 20-30 steps.
         The model uses edge detection to guide the image generation process.
         """
     )
@@ -159,7 +163,7 @@ with gr.Blocks() as demo:
                 low_threshold = gr.Slider(minimum=1, maximum=255, value=100, label="Canny Low Threshold")
                 high_threshold = gr.Slider(minimum=1, maximum=255, value=200, label="Canny High Threshold")
             guidance_scale = gr.Slider(minimum=1, maximum=20, value=7.5, label="Guidance Scale")
-            steps = gr.Slider(minimum=1, maximum=100, value=50, label="Steps")
+            steps = gr.Slider(minimum=1, maximum=50, value=25, label="Steps")  # Reduced max steps
             seed = gr.Textbox(label="Seed (empty for random)", placeholder="Enter a number for reproducible results")
             generate = gr.Button("Generate")