Update app.py

app.py

@@ -1,17 +1,15 @@
 import torch
-from diffusers import StableDiffusionPipeline
-import gradio as gr
+from diffusers import StableDiffusionPipeline, DPMSolverMultistepScheduler
 
-# Load model on CPU (use torch_dtype=torch.float32 for CPU compatibility)
-pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32).to("cpu")
+# Load the model with torch.float32 for CPU
+pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float32)
+pipe.scheduler = DPMSolverMultistepScheduler.from_config(pipe.scheduler.config)  # Faster scheduler
+pipe = pipe.to("cpu")
 
-# Function to generate image
+# Optimized function for faster image generation
 def generate_image(prompt):
-    image = pipe(prompt).images[0]
-    return image
+    image = pipe(prompt, num_inference_steps=15, guidance_scale=7.0).images[0]  # Reduced steps
+    image.save("output.png")
+    print("Image saved!")
 
-# Gradio interface
-iface = gr.Interface(fn=generate_image, inputs="text", outputs="image", title="Stable Diffusion Image Generator")
-
-# Launch app
-iface.launch()
+generate_image("a photo of an astronaut riding a horse on Mars")