Text-to-Image
Diffusers
Safetensors
English
flux
flux2
vae
hdr
ultrahd
cinematic
high-detail
image-enhancement
texture-recovery
sharpness-enhancement
color-enhancement
microcontrast
raw
generative-ai
stable-diffusion
diffusion
latent-space
photorealistic
neural-compression
reconstruction
fp16
inference
image-generation
visual-quality
machine-learning
ai-art
flux-compatible
Instructions to use Felldude/FLUX.2-HDR-VAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Felldude/FLUX.2-HDR-VAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Felldude/FLUX.2-HDR-VAE", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
Update README.md
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README.md
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---
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license:
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---
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| 1 |
+
```yaml
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| 2 |
---
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| 3 |
+
license: other
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| 4 |
+
language:
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| 5 |
+
- en
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| 6 |
+
library_name: diffusers
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| 7 |
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pipeline_tag: text-to-image
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| 8 |
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tags:
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| 9 |
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- flux
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| 10 |
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- flux2
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| 11 |
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- vae
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| 12 |
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- hdr
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| 13 |
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- ultrahd
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| 14 |
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- cinematic
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| 15 |
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- high-detail
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| 16 |
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- image-enhancement
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| 17 |
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- texture-recovery
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| 18 |
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- sharpness-enhancement
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| 19 |
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- color-enhancement
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| 20 |
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- microcontrast
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| 21 |
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- raw
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| 22 |
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- generative-ai
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| 23 |
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- stable-diffusion
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| 24 |
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- diffusion
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| 25 |
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- latent-space
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| 26 |
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- photorealistic
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| 27 |
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- neural-compression
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| 28 |
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- reconstruction
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| 29 |
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- fp16
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| 30 |
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- inference
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| 31 |
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- image-generation
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| 32 |
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- visual-quality
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| 33 |
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- machine-learning
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| 34 |
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- ai-art
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| 35 |
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- flux-compatible
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| 36 |
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base_model:
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| 37 |
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- FLUX.2
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| 38 |
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- FLUX.2 Klein
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| 39 |
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- Ernie
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| 40 |
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model_type: Variational Autoencoder (VAE)
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| 41 |
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datasets:
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| 42 |
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- internal-evaluation-suite
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| 43 |
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metrics:
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| 44 |
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- lpips
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| 45 |
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- gradient-energy
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| 46 |
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- unique-colors
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| 47 |
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- brightness-bias
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| 48 |
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- contrast-gain
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| 49 |
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- rgb-channel-shift
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| 50 |
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inference: true
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| 51 |
---
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| 52 |
+
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| 53 |
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# FLUX.2 UltraHD RAW VAE
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| 54 |
+
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| 55 |
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## Overview
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| 56 |
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| 57 |
+
FLUX.2 UltraHD RAW VAE is a high-fidelity enhancement-focused Variational Autoencoder engineered for the FLUX.2 ecosystem. Unlike reconstruction-pure VAEs optimized exclusively for perceptual similarity, UltraHD RAW VAE is tuned for cinematic rendering, HDR enhancement, sharper edge response, texture recovery, and richer gradient reproduction.
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| 58 |
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| 59 |
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The model is fully compatible with all FLUX.2 variants including:
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| 60 |
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| 61 |
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- FLUX.2
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| 62 |
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- FLUX.2 Klein
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| 63 |
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- FLUX.2 Ernie
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| 64 |
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| 65 |
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---
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| 66 |
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| 67 |
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# Scientific Assessment
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| 68 |
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| 69 |
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## Design Objective
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| 70 |
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| 71 |
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The primary design goal of UltraHD RAW VAE is not strict latent reconstruction accuracy, but perceptual enhancement quality.
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| 72 |
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| 73 |
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Key optimization targets include:
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| 74 |
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| 75 |
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- Increased texture fidelity
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| 76 |
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- Enhanced microcontrast
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| 77 |
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- Expanded color richness
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| 78 |
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- Sharper edge gradients
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| 79 |
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- Improved HDR-style rendering
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| 80 |
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- Stable luminance preservation
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| 81 |
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- Dynamic range consistency
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| 82 |
+
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| 83 |
+
---
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| 84 |
+
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| 85 |
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# Quick Assessment
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| 86 |
+
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| 87 |
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## Observed Visual Characteristics
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| 88 |
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|
| 89 |
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### Color Enhancement
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| 90 |
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| 91 |
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UltraHD RAW VAE increases effective color richness through:
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| 92 |
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| 93 |
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- Higher unique color utilization
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| 94 |
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- Expanded HDR gradient smoothness
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| 95 |
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- Slight saturation enhancement
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| 96 |
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- Preserved luminance integrity
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| 97 |
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- Preserved dynamic range behavior
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| 98 |
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| 99 |
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### Detail Recovery
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| 100 |
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| 101 |
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The VAE demonstrates:
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| 102 |
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| 103 |
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- Stronger edge energy
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| 104 |
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- Sharper fine detail reconstruction
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| 105 |
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- Increased perceived texture depth
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| 106 |
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- Enhanced microcontrast behavior
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| 107 |
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| 108 |
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---
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| 109 |
+
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| 110 |
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# Training Notes
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| 111 |
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|
| 112 |
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Although the visual enhancement effect may appear subtler compared to previous enhancement VAEs, the underlying optimization process was substantially more difficult.
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| 113 |
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| 114 |
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More than double-digit failed training attempts were required to achieve:
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| 115 |
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| 116 |
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- Stable HDR enhancement
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| 117 |
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- Low LPIPS divergence
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| 118 |
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- Contrast preservation
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| 119 |
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- Brightness neutrality
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| 120 |
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- Balanced channel behavior
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| 121 |
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| 122 |
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Achieving an LPIPS value near the already extremely low FLUX.2 baseline proved exceptionally challenging.
|
| 123 |
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|
| 124 |
+
---
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| 125 |
+
|
| 126 |
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# Direct Metric Comparison
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| 127 |
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|
| 128 |
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## Evaluation Setup
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| 129 |
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| 130 |
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- 150-image benchmark comparison
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| 131 |
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- Tested directly against Base FLUX.2 VAE
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| 132 |
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- Metrics computed across identical latent reconstruction conditions
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| 133 |
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| 134 |
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---
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| 135 |
+
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| 136 |
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# LPIPS (Perceptual Similarity)
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| 137 |
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| 138 |
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| Model | LPIPS |
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| 139 |
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|---|---|
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| 140 |
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| FLUX Base | 0.0073 |
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| 141 |
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| UltraHD RAW VAE | 0.0303 |
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| 142 |
+
|
| 143 |
+
### Difference
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| 144 |
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| 145 |
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- 4.1× higher than FLUX Base
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| 146 |
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| 147 |
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### Interpretation
|
| 148 |
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| 149 |
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The model intentionally trades strict reconstruction fidelity for perceptual enhancement quality.
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| 150 |
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| 151 |
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Despite the increase, both values remain significantly below typical human perceptual thresholds.
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| 152 |
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|
| 153 |
+
---
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| 154 |
+
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| 155 |
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# Gradient Energy
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| 156 |
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|
| 157 |
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| Model | Gradient Energy |
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| 158 |
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|---|---|
|
| 159 |
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| FLUX Base | 405.5 |
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| 160 |
+
| UltraHD RAW VAE | 633.5 |
|
| 161 |
+
|
| 162 |
+
### Difference
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| 163 |
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| 164 |
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- +56% increase
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| 165 |
+
|
| 166 |
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### Interpretation
|
| 167 |
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|
| 168 |
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Substantially sharper detail rendering and stronger edge definition.
|
| 169 |
+
|
| 170 |
+
---
|
| 171 |
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| 172 |
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# Unique Colors
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| 173 |
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|
| 174 |
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| Model | Unique Colors |
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| 175 |
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|---|---|
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| 176 |
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| FLUX Base | 37,369 |
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| 177 |
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| UltraHD RAW VAE | 39,184 |
|
| 178 |
+
|
| 179 |
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### Difference
|
| 180 |
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| 181 |
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- +4.9% increase
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| 182 |
+
|
| 183 |
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### Interpretation
|
| 184 |
+
|
| 185 |
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Improved color richness and smoother HDR tonal transitions.
|
| 186 |
+
|
| 187 |
+
---
|
| 188 |
+
|
| 189 |
+
# Brightness Bias
|
| 190 |
+
|
| 191 |
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| Model | Brightness Bias |
|
| 192 |
+
|---|---|
|
| 193 |
+
| FLUX Base | 0.0047 |
|
| 194 |
+
| UltraHD RAW VAE | 0.0030 |
|
| 195 |
+
|
| 196 |
+
### Interpretation
|
| 197 |
+
|
| 198 |
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Excellent luminance preservation with slightly improved brightness neutrality.
|
| 199 |
+
|
| 200 |
+
---
|
| 201 |
+
|
| 202 |
+
# Contrast Gain
|
| 203 |
+
|
| 204 |
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| Model | Contrast Gain |
|
| 205 |
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|---|---|
|
| 206 |
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| FLUX Base | 0.984 |
|
| 207 |
+
| UltraHD RAW VAE | 0.983 |
|
| 208 |
+
|
| 209 |
+
### Interpretation
|
| 210 |
+
|
| 211 |
+
Near-identical dynamic range and HDR tone retention.
|
| 212 |
+
|
| 213 |
+
---
|
| 214 |
+
|
| 215 |
+
# RGB Channel Shift Analysis
|
| 216 |
+
|
| 217 |
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## Red Shift
|
| 218 |
+
|
| 219 |
+
| Model | Red Shift |
|
| 220 |
+
|---|---|
|
| 221 |
+
| FLUX Base | +0.0048 |
|
| 222 |
+
| UltraHD RAW VAE | +0.0188 |
|
| 223 |
+
|
| 224 |
+
Interpretation:
|
| 225 |
+
|
| 226 |
+
- Slightly warmer red response
|
| 227 |
+
- Improved cinematic warmth
|
| 228 |
+
|
| 229 |
+
---
|
| 230 |
+
|
| 231 |
+
## Green Shift
|
| 232 |
+
|
| 233 |
+
| Model | Green Shift |
|
| 234 |
+
|---|---|
|
| 235 |
+
| FLUX Base | -0.0037 |
|
| 236 |
+
| UltraHD RAW VAE | -0.0104 |
|
| 237 |
+
|
| 238 |
+
Interpretation:
|
| 239 |
+
|
| 240 |
+
- Minor reduction in green balance
|
| 241 |
+
- Helps reduce sterile tonal appearance
|
| 242 |
+
|
| 243 |
+
---
|
| 244 |
+
|
| 245 |
+
## Blue Shift
|
| 246 |
+
|
| 247 |
+
| Model | Blue Shift |
|
| 248 |
+
|---|---|
|
| 249 |
+
| FLUX Base | +0.0181 |
|
| 250 |
+
| UltraHD RAW VAE | +0.0434 |
|
| 251 |
+
|
| 252 |
+
Interpretation:
|
| 253 |
+
|
| 254 |
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- Stronger blue/cyan HDR emphasis
|
| 255 |
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- Enhanced atmospheric rendering
|
| 256 |
+
|
| 257 |
+
---
|
| 258 |
+
|
| 259 |
+
# Summary
|
| 260 |
+
|
| 261 |
+
FLUX.2 UltraHD RAW VAE is an enhancement-oriented VAE optimized for:
|
| 262 |
+
|
| 263 |
+
- HDR rendering
|
| 264 |
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- Texture recovery
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| 265 |
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- Cinematic sharpness
|
| 266 |
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- Richer gradients
|
| 267 |
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- Enhanced microcontrast
|
| 268 |
+
- Improved perceptual detail
|
| 269 |
+
|
| 270 |
+
Compared to the base FLUX VAE, UltraHD RAW VAE produces:
|
| 271 |
+
|
| 272 |
+
- Significantly stronger edge detail
|
| 273 |
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- Improved color richness
|
| 274 |
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- Better texture clarity
|
| 275 |
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- Enhanced HDR-style rendering
|
| 276 |
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- Stable brightness preservation
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| 277 |
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- Preserved contrast behavior
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| 278 |
+
|
| 279 |
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The model is best suited for users prioritizing perceptual image quality and cinematic rendering over strict pixel-perfect reconstruction fidelity.
|
| 280 |
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|
| 281 |
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---
|
| 282 |
+
|
| 283 |
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# Recommended Usage
|
| 284 |
+
|
| 285 |
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Recommended for:
|
| 286 |
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|
| 287 |
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- Photorealistic generations
|
| 288 |
+
- Cinematic compositions
|
| 289 |
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- HDR workflows
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| 290 |
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- Texture-heavy scenes
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| 291 |
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- High-detail portrait rendering
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| 292 |
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- Atmospheric lighting
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| 293 |
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- Stylized realism
|
| 294 |
+
|
| 295 |
+
Less suitable for:
|
| 296 |
+
|
| 297 |
+
- Pixel-faithful reconstruction tasks
|
| 298 |
+
- Scientific image preservation
|
| 299 |
+
- Reconstruction benchmarking applications
|
| 300 |
+
|
| 301 |
+
---
|
| 302 |
+
|
| 303 |
+
# Compatibility
|
| 304 |
+
|
| 305 |
+
Compatible with:
|
| 306 |
+
|
| 307 |
+
- FLUX.2
|
| 308 |
+
- FLUX.2 Klein
|
| 309 |
+
- Ernie
|
| 310 |
+
|
| 311 |
+
Precision support:
|
| 312 |
+
|
| 313 |
+
- FP16
|
| 314 |
+
- BF16
|
| 315 |
+
- FP32
|
| 316 |
+
|
| 317 |
+
---
|
| 318 |
+
|
| 319 |
+
# Disclaimer
|
| 320 |
+
|
| 321 |
+
This VAE intentionally modifies reconstruction characteristics to improve perceptual aesthetics. Metric increases in LPIPS are expected and are part of the enhancement-oriented design philosophy.
|
| 322 |
+
```
|