SLD
SLD stands for Self-correcting LLM-controlled Diffusion Models, the official PyTorch implementation of the CVPR 2024 paper from UC Berkeley. This framework enhances generative models by integrating large language models as detectors to ensure precise text-to-image alignment. Its core capability is self-correction, which identifies and fixes failures during the generation process automatically. The system supports both image generation from text and fine-grained image editing using a unified approach. A key advantage is its universal compatibility; it works with any existing image generator, including models like DALL-E 3 and Stable Diffusion variants, without requiring extra training or new data. The software includes scripts for processing images based on JSON instructions, allowing users to specify prompts, input directories, and output configurations. It relies on Python 3.9 and specific versions of dependencies like transformers and diffusers, optimized for Linux environments with high-memory GPUs. Users