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# Import the necessary libraries
from diffusers import StableDiffusionPipeline
import torch
from PIL import Image
import gradio as gr
# Load the Stable Diffusion model
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
# Use CPU as fallback if CUDA is not available
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipe.to(device)
# Function to generate an image
def generate_image(prompt):
image = pipe(prompt).images[0]
return image
# Define the Gradio interface
with gr.Blocks() as demo:
gr.HTML(
"""
<div style="text-align: center;">
<h1>🌄 Generate Stunning Images with Stable Diffusion</h1>
<h3>Type a prompt to create a beautiful image:</h3>
</div>
"""
)
with gr.Row():
with gr.Column():
prompt = gr.Textbox(label="Enter your prompt here", placeholder="e.g., beautiful and realistic mountain scenery 🌄", lines=1)
submit_button = gr.Button("Generate Image 🚀")
with gr.Column():
image_output = gr.Image(label="Generated Image", type="pil")
submit_button.click(fn=generate_image, inputs=prompt, outputs=image_output)
gr.HTML(
"""
<div style="text-align: center;">
<h4>Developed by Salman Maqbool ✨</h4>
</div>
"""
)
# Launch the Gradio app
demo.launch()
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