This repository provides a collection of custom nodes for ComfyUI and SD WebUI (reForge) that implement various guidance techniques for diffusion models. It includes implementations of Perturbed-Attention Guidance (PAG), Smoothed Energy Guidance (SEG), Sliding Window Guidance (SWG), PLADIS, Normalized Attention Guidance (NAG), Token Perturbation Guidance (TPG), Frequency-Decoupled Guidance (FDG), Momentum Guidance (MG), and Sliding Mode Control CFG (SMC-CFG). The architecture consists of modular node files, shared utility functions, and backend compatibility layers. Key entry points are the ComfyUI extension registration in __init__.py and the reForge integration scripts in the scripts directory. The system modifies the denoising process of diffusion models by injecting guidance computations at specific U-Net blocks, enhancing image quality and control.
ComfyUI-VoxCPM is a ComfyUI custom node package that provides expressive text-to-speech (TTS) using the VoxCPM model family (v1.x and v2). It supports zero-shot TTS, voice cloning (prompt or reference audio), voice design via text descriptions, LoRA inference, and LoRA fine-tuning. The architecture is a ComfyUI extension with heavy JavaScript frontend, HTTP API routes, and vendored model inference code. The core functionality is implemented in the `src/voxcpm/` directory, which contains model architectures (MiniCPM4, AudioVAE, local DiT, etc.), a standalone CLI, and training utilities. External dependencies include ComfyUI, PyTorch, Hugging Face Hub, and several optional libraries (argbind, datasets, modelscope, etc.). The codebase demonstrates good software engineering practices with clean abstractions, reusable components, and graceful degradation for optional features. However, it is tightly coupled to ComfyUI's ecosystem and vendors upstream model code, which may drift from upstream. The repository also includes a standalone `hf_progress` library for HuggingFace transfer progress tracking, which is a well-isolated, reusable component.
This repository provides custom nodes for ComfyUI to enable Deforum-based animation generation. It implements frame-by-frame processing of stable diffusion models with parameter scheduling, allowing users to create animated sequences by evolving prompts, seeds, strength, and other parameters over time. The architecture centers around ComfyUI's node system, with specialized nodes for parameter scheduling, prompt engineering, sampling, latent caching, ControlNet integration, image processing, logic control, video I/O, audio synchronization, and advanced noise generation. A critical execution hijack mechanism modifies ComfyUI's internal processing to handle list operations for frame sequences. The system relies on external libraries like Deforum Studio, ControlNet, RAFT, depth models, and FILM for computer vision techniques.