Update app.py

app.py

@@ -1,36 +1,36 @@
-import torch
-import gradio as gr
-from diffusers import StableDiffusionPipeline
-from PIL import Image
-
-# Set up the device (use 'cpu' since we are running on CPU)
-device = "cpu"  # Force CPU usage
-
-# Load the pre-trained Stable Diffusion model from Hugging Face
-pipe = StableDiffusionPipeline.from_pretrained("CompVis/stable-diffusion-v1-4-original")
-pipe = pipe.to(device)
-
-# Function for generating an image based on input image and prompt
-def generate_image(photo, prompt):
-    # Resize input image to 512x512 (required by Stable Diffusion)
-    photo = photo.resize((512, 512))
-
-    # Generate the image using Stable Diffusion model
-    generated_image = pipe(prompt=prompt, init_image=photo, strength=0.75, guidance_scale=7.5)["sample"][0]
-    
-    # Return the generated image
-    return generated_image
-
-# Create Gradio interface
-interface = gr.Interface(
-    fn=generate_image,  # The function to generate images
-    inputs=[
-        gr.Image(type="pil", label="Upload your photo"),  # Input image (your photo)
-        gr.Textbox(lines=2, placeholder="Enter prompt here", label="Enter text prompt")  # Input text prompt
-    ],
-    outputs=gr.Image(type="pil", label="Generated Image"),  # Output generated image
-    live=True  # Automatically update the output as the user changes the prompt or uploads a photo
-)
-
-# Launch the Gradio interface
-interface.launch()
+import torch
+import gradio as gr
+from diffusers import StableDiffusionPipeline
+from PIL import Image
+
+# Set up the device (use 'cpu' since we are running on CPU)
+device = "cpu"  # Force CPU usage
+
+# Load the pre-trained Stable Diffusion model from Hugging Face
+pipe = StableDiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-2-1")
+pipe = pipe.to(device)
+
+# Function for generating an image based on input image and prompt
+def generate_image(photo, prompt):
+    # Resize input image to 512x512 (required by Stable Diffusion)
+    photo = photo.resize((512, 512))
+
+    # Generate the image using Stable Diffusion model
+    generated_image = pipe(prompt=prompt, init_image=photo, strength=0.75, guidance_scale=7.5)["sample"][0]
+    
+    # Return the generated image
+    return generated_image
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=generate_image,  # The function to generate images
+    inputs=[
+        gr.Image(type="pil", label="Upload your photo"),  # Input image (your photo)
+        gr.Textbox(lines=2, placeholder="Enter prompt here", label="Enter text prompt")  # Input text prompt
+    ],
+    outputs=gr.Image(type="pil", label="Generated Image"),  # Output generated image
+    live=True  # Automatically update the output as the user changes the prompt or uploads a photo
+)
+
+# Launch the Gradio interface
+interface.launch()