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| import streamlit as st | |
| from diffusers import AutoPipelineForText2Image | |
| import torch | |
| from io import BytesIO | |
| st.set_page_config(page_title="Dreamscape Visualizer (Turbo)") | |
| st.title("🌌 Dreamscape Visualizer") | |
| def load_pipeline(): | |
| pipe = AutoPipelineForText2Image.from_pretrained( | |
| "stabilityai/sdxl-turbo", | |
| torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32, | |
| variant="fp16" if torch.cuda.is_available() else None | |
| ) | |
| pipe.to("cuda" if torch.cuda.is_available() else "cpu") | |
| return pipe | |
| pipe = load_pipeline() | |
| style_modifiers = { | |
| "Fantasy": "fantasy dream, ethereal, colorful", | |
| "Nightmare": "dark horror dream, creepy surreal", | |
| "Lucid": "hyperreal dream, bright, vivid", | |
| "Sci-Fi": "futuristic city, neon dream", | |
| "Mythical": "mythical world, god-like, celestial" | |
| } | |
| prompt = st.text_area("Describe your dream:") | |
| style = st.selectbox("Choose a dream style:", list(style_modifiers.keys())) | |
| if st.button("Generate Dream Image"): | |
| if not prompt.strip(): | |
| st.warning("Please describe your dream first!") | |
| else: | |
| with st.spinner("Dreaming up your world..."): | |
| final_prompt = f"{prompt}, {style_modifiers[style]}" | |
| result = pipe(prompt=final_prompt, guidance_scale=0.0, num_inference_steps=2) | |
| image = result.images[0] | |
| st.image(image, caption="✨ Your Dream Visualized", use_column_width=True) | |
| # Convert image to bytes for download | |
| buf = BytesIO() | |
| image.save(buf, format="PNG") | |
| byte_im = buf.getvalue() | |
| st.download_button( | |
| label="📥 Download Dream Image", | |
| data=byte_im, | |
| file_name="dreamscape.png", | |
| mime="image/png" | |
| ) | |