stable-diffusion-image-generation

# Stable Diffusion Image Generation Comprehensive guide to generating images with Stable Diffusion using the HuggingFace Diffusers library. ## When to use Stable Diffusion **Use Stable Diffusion when:** - Generating images from text descriptions - Performing image-to-image translation (style transfer, enhancement) - Inpainting (filling in masked regions) - Outpainting (extending images beyond boundaries) - Creating variations of existing images - Building custom image generation workflows **Key features:** - **Text-to-Image**: Generate images from natural language prompts - **Image-to-Image**: Transform existing images with text guidance - **Inpainting**: Fill masked regions with context-aware content - **ControlNet**: Add spatial conditioning (edges, poses, depth) - **LoRA Support**: Efficient fine-tuning and style adaptation - **Multiple Models**: SD 1.5, SDXL, SD 3.0, Flux support **Use alternatives instead:** - **DALL-E 3**: For API-based generation without GPU - **Midjourney**: For artistic, stylized outputs - **Imagen**: For Google Cloud integration - **Leonardo.ai**: For web-based creative workflows ## Quick start ### Installation ```bash pip install diffusers transformers accelerate torch pip install xformers # Optional: memory-efficient attention ``` ### Basic text-to-image ```python from diffusers import DiffusionPipeline import torch # Load pipeline (auto-detects model type) pipe = DiffusionPipeline.from_pretrained( "stable-diffusion-v1-5/stable-dif...