StyleGenAI / app.py
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Update app.py
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import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
from datetime import datetime
from PIL import Image
# Load the model
model_id = "stabilityai/stable-diffusion-2"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cpu")
# Keep image history
image_history = []
# Style templates
STYLE_TEMPLATES = {
"Photo": "highly detailed, realistic photo, natural lighting",
"Anime": "anime style, vibrant colors, line art, cel shading",
"Oil Painting": "oil painting style, brush strokes, classic fine art"
}
def enhance_prompt(prompt, style):
style_suffix = STYLE_TEMPLATES.get(style, "")
return f"{prompt}, {style_suffix}"
def generate_image(prompt, style, uploaded_image):
if not prompt.strip():
return None, image_history
final_prompt = enhance_prompt(prompt, style)
# Currently not using uploaded_image β€” could be used with img2img later
image = pipe(final_prompt).images[0]
# Add to history
timestamp = datetime.now().strftime("%H:%M:%S")
caption = f"{style} - {timestamp}"
image_history.append((image, caption))
return image, image_history[-5:]
def clear_history():
global image_history
image_history = []
return None, []
# Gradio UI
with gr.Blocks() as demo:
gr.Markdown("## 🎨 Realistic Text-to-Image Generator")
gr.Markdown("Powered by **Stable Diffusion 2** | Now with style presets, prompt enhancer, image history, and optional image upload!")
with gr.Row():
prompt = gr.Textbox(label="Enter your prompt", placeholder="e.g., A golden retriever in the snow")
style = gr.Dropdown(["Photo", "Anime", "Oil Painting"], label="Choose Style", value="Photo")
uploaded_image = gr.Image(label="Upload Optional Image (future use)", type="pil", tool=None)
with gr.Row():
generate_btn = gr.Button("🎨 Generate Image")
clear_btn = gr.Button("🧹 Clear History")
output_image = gr.Image(label="Generated Image", type="pil")
gallery = gr.Gallery(label="πŸ–ΌοΈ Image History (last 5)", columns=3, object_fit="contain")
generate_btn.click(generate_image, inputs=[prompt, style, uploaded_image], outputs=[output_image, gallery])
clear_btn.click(clear_history, outputs=[output_image, gallery])
demo.launch()