[FLUX] Detail Daemon img2img workflow (for beginner)

This beginner-friendly Flux img2img workflow is for using Detail Daemon with Flux; it takes a source image, includes Flux text encoding, and provides image preview and saving steps.

The graph combines DetailDaemonGraphSigmasNode and DetailDaemonSamplerNode with BasicScheduler and BasicGuider.

It includes image loading, VAE encoding and decoding, Flux text encoding, sampling, image comparison, previewing, and saving.

Use LoadImage for the source image; the graph includes CLIPTextEncodeFlux and DualCLIPLoader for text encoding.

PreviewImage and SaveImage are included for previewing and saving image results.

The listed base model is Flux.1 D, and the publisher is A01demort.

No license is listed for this workflow.

Named model files are clip_l.safetensors, FLUX_VAE_diffusion_pytorch_model.safetensors, flux1-dev-Q8_0.gguf, and t5xxl_fp16.safetensors.

Named processing components include BasicGuider, BasicScheduler, CLIPTextEncodeFlux, DetailDaemonGraphSigmasNode, DetailDaemonSamplerNode, DualCLIPLoader, KSamplerSelect, SamplerCustomAdvanced, and UnetLoaderGGUF.

Other named components include Image Comparer (rgthree), Label (rgthree), LoadImage, PreviewImage, RandomNoise, SaveImage, VAEDecode, VAEEncode, and VAELoader.

The workflow is described as having a clean node layout, clear labels, and an essentials-only structure for beginners.

Before using it, verify that your setup includes the named components and model files.

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