Workflow RAW Detailer
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Model description

🔧 NEURO HARMONY
Purpose: This workflow is designed to generate ultra-detailed RAW-style images using the RAW_Photography LoRA, ControlNet depth guidance, and multiple stages of high-resolution upscaling.
🧠Core Components:
1. Model and LoRA
UNET:
flux_dev.safetensors(fp8)CLIP:
clip_l.safetensors + t5xxl_fp16.safetensorsLoRA:
RAW_Photography.safetensors(enabled at 100%) Model page here: /model/1639720LoRA is integrated via the
Power Lora Loader (rgthree)node.
2. Prompting and Detailing
BilboXPhotoPrompt is used to generate rich photo-style prompts.
A separate prompt detailer enhances:
high-frequency surface texture,
edge and contour definition,
natural gradients,
depth and occlusion cues,
realistic material response,
and framing clarity.
FluxGuidanceis applied withguidance: 3.5to boost semantic conditioning.
3. Depth Guidance with ControlNet
Preprocessor:
MiDaS-DepthMapPreprocessorat 1280px resolutionControlNet:
flux-depth-controlnet-v3.safetensorsUsed via
ControlNetApplyAdvancedwith settings:Strength: 0.6
Start: 0.0
End: 0.618
This ensures stable structure and perspective.
4. Detail Enhancement via DetailDaemon
Three progressive sampling stages, each wrapped with a DetailDaemonSamplerNode using:
detail_amount: 0.62start/end: 1bias: 0.62smooth: true
Sampling is handled through SamplerCustomAdvanced and BasicScheduler nodes using karras/beta scheduling and controlled denoising.
5. Hi-Res Upscaling
After each sampling pass, image resolution is progressively increased with:
002_lightweightSR_DIV2K_s64w8_SwinIR-S_x2.pth001_classicalSR_DIV2K_s48w8_SwinIR-M_x4.pth1xSkinContrast-SuperUltraCompact.pth— for final skin cleanup
All upscaling is performed with precision to preserve microtexture and avoid artifacts.
📸 Finalization and Output
Results are compared using the
Image Comparer (rgthree)in "Slide" mode.Images are saved with
SaveImagefor both intermediate and final outputs.
✅ Summary:
Flux_RAW_HIRes_V2 is a highly optimized multi-stage workflow tailored for photorealism and ultra-fine detail. It combines:
a RAW photography LoRA,
progressive DetailDaemon refinement,
ControlNet depth stabilization,
SwinIR upscaling layers,
and enhanced semantic conditioning.
Ideal for portraits where skin detail, structure, and texture fidelity matter most.






















