Add application file

app.py

@@ -1,27 +1,27 @@
 import gradio as gr
-from diffusers import StableDiffusionPipeline, EulerAncestralDiscreteScheduler, DDIMScheduler, PNDMScheduler
+from diffusers import StableDiffusionPipeline, DDIMScheduler
 import torch
 from PIL import ImageEnhance, Image
 import numpy as np
+import spaces  # For using ZeroGPU decorator
 
+# Load Stable Diffusion pipeline with efficient defaults
 model_id = "CompVis/stable-diffusion-v1-4"
-default_scheduler = EulerAncestralDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
+default_scheduler = DDIMScheduler.from_pretrained(model_id, subfolder="scheduler")
 
-# Set device based on availability
 device = "cuda" if torch.cuda.is_available() else "cpu"
 torch_dtype = torch.float16 if device == "cuda" else torch.float32
-
-# Load pipeline with appropriate torch dtype
 pipe = StableDiffusionPipeline.from_pretrained(model_id, scheduler=default_scheduler, torch_dtype=torch_dtype).to(device)
 
-# Scheduler options
+# Scheduler options (setting DDIM as the default for speed)
 schedulers = {
-    "Artistic & Imaginative (Euler Ancestral) - Recommended for creative scenes, moderate speed": EulerAncestralDiscreteScheduler,
-    "Photo-Realistic (PNDM) - Best for realistic details, moderate speed": PNDMScheduler,
     "High-Definition & Fast (DDIM) - Good quality with fastest speed": DDIMScheduler,
+    "Photo-Realistic (PNDM) - Best for realistic details, moderate speed": PNDMScheduler,
+    "Artistic & Imaginative (Euler Ancestral) - Good for creative scenes, moderate speed": EulerAncestralDiscreteScheduler,
 }
 
-# Main image generation function with dynamic scheduling and size option
+# Main image generation function with 60-second GPU duration limit
+@spaces.GPU(duration=60)
 def generate_image(prompt, use_categories, genre, style, theme, lighting, scheduler_choice, quality, size):
     # Check if additional categories should be added to the prompt
     if use_categories:
@@ -38,7 +38,7 @@ def generate_image(prompt, use_categories, genre, style, theme, lighting, schedu
     pipe.scheduler = scheduler
 
     # Set output size based on selection
-    image_size = (512, 512) if size == "Profile Picture" else (1024, 768)
+    image_size = (512, 512) if size == "Profile Picture" else (512, 512)  # Using smaller size for faster generation
 
     # Generate image with specified quality and size
     with torch.no_grad():
@@ -54,16 +54,15 @@ def adjust_brightness_contrast(image, brightness, contrast):
     image = ImageEnhance.Contrast(image).enhance(contrast)
     return np.array(image)
 
-# Warning function to show a message if the user selects a high value for quality
+# Warning function for high-quality settings
 def show_warning(quality):
-    if quality > 80:
-        return "⚠️ High Quality: This setting may slow down generation and might not provide additional visual improvement. Consider using 50-80 steps for best results."
+    if quality > 40:  # Lower threshold for warning
+        return "⚠️ High Quality: This may slow down generation. Consider using values below 40 for faster results."
     return ""
 
-# Build Gradio Interface
+# Build Gradio Interface with adjusted defaults
 with gr.Blocks() as demo:
     gr.Markdown("# ✨ AI-Powered Wallpaper/Profile Picture Generator\n🖼️ A tool to generate and fine-tune AI-created wallpapers and profile pictures with adjustable styles and effects.")
-    gr.Markdown("⚠️ **Live effects and advanced prompt engineering coming soon! Disclaimer**: Results may not always be accurate or perfectly aligned with your prompt. Experiment with prompt adjustments and settings to get the best results.")
     
     # Image Generation Section
     with gr.Tab("Image Generator"):
@@ -83,18 +82,19 @@ with gr.Blocks() as demo:
                     theme = gr.Dropdown(["Landscape", "Portrait", "Abstract Patterns", "Architecture"], label="Theme")
                     lighting = gr.Dropdown(["Warm", "Cool", "Cinematic", "Soft", "Neon"], label="Lighting")
 
-                quality = gr.Slider(20, 150, value=80, step=10, label="Image Quality", info="Higher values yield more detail but take longer to generate.")
+                # Reduced quality for faster generation
+                quality = gr.Slider(20, 80, value=30, step=10, label="Image Quality", info="Lower values for faster generation.")
                 warning_message = gr.Markdown("")
                 
-                # Scheduler selection with default option
+                # Scheduler selection with default option as DDIM for speed
                 scheduler_choice = gr.Dropdown(
                     [
-                    "Artistic & Imaginative (Euler Ancestral) - Recommended for creative scenes, moderate speed",
+                    "High-Definition & Fast (DDIM) - Good quality with fastest speed",
                     "Photo-Realistic (PNDM) - Best for realistic details, moderate speed",
-                    "High-Definition & Fast (DDIM) - Good quality with fastest speed"
+                    "Artistic & Imaginative (Euler Ancestral) - Good for creative scenes, moderate speed"
                     ],
                     label="Artistic Style & Speed",
-                    value="Artistic & Imaginative (Euler Ancestral) - Recommended for creative scenes, moderate speed"
+                    value="High-Definition & Fast (DDIM) - Good quality with fastest speed"
                 )
                 
                 size = gr.Dropdown(["Profile Picture", "Wallpaper"], label="Image Size", value="Profile Picture")