The Most Comprehensive Flux ControlNet Guide: Learn Everything About Flux ControlNet in 30 Minutes
ControlNet is a neural network structure that adds additional constraints to image generation in diffusion models. Since its release in early 2023, it has become an essential part of the diffusion model ecosystem (SD, Flux). It allows you to reference elements like lines, depth, and poses from input images to generate images that match these features.
Flux is currently the most popular diffusion model for image generation, heavily supported by the open-source community. In just over two months, multiple organizations have released dozens of different ControlNet models. While the variety is not yet as rich as SD1.5 and SDXL, some models show impressive results and can be useful in many scenarios.
Initially, using ControlNet was a bit tricky, requiring separate installation of the nodes released by the model developers. However, ComfyUI quickly adapted, and in newer versions, most models can be applied directly without the need for additional plugins.
Today, I’ll give you a complete overview of Flux ControlNet—from downloading the models and installing pre-processors to demonstrating and comparing different Flux ControlNet models in ComfyUI. I’ll also test whether they can be used with GGUF models and Schnell models.
Models:
ControlNet-Union-Pro: https://huggingface.co/Shakker-Labs/F...
openpose_controlnet: https://huggingface.co/raulc0399/flux...
ControlNet-Upscaler: https://huggingface.co/jasperai/Flux....
Workflow:
https://drive.google.com/drive/folder...
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