Instructions to use Felldude/SDXL-HDR-VAE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use Felldude/SDXL-HDR-VAE with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("Felldude/SDXL-HDR-VAE", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
HDR VAE v3
HDR VAE v3 is the most capable release in the HDR VAE series to date, delivering substantial improvements in perceived image quality while maintaining strong reconstruction fidelity.
Compared to the standard SDXL VAE, HDR VAE v3 focuses on preserving detail, expanding color reproduction, and increasing visual impact. The result is sharper images, richer colors, improved edge retention, and a noticeably larger effective color gamut.
These gains are visible in standard workflows and become even more pronounced when working in high bit-depth pipelines.
Highlights
β¨ Sharper details and textures
π¨ Expanded color volume and color diversity
π Richer saturation without excessive clipping
π Improved edge preservation
π Better retention of fine image structure
β‘ Slightly increased dynamic range and contrast
At a Glance
| Category | Winner |
|---|---|
| Reconstruction Accuracy | SDXL Base VAE |
| Sharpness | HDR VAE v3 |
| Edge Preservation | HDR VAE v3 |
| Color Gamut | HDR VAE v3 |
| Color Diversity | HDR VAE v3 |
| Saturation | HDR VAE v3 |
| Visual Impact | HDR VAE v3 |
| Scientific Fidelity | SDXL Base VAE |
The base SDXL VAE remains slightly stronger for pure reconstruction metrics, while HDR VAE v3 produces significantly more visually compelling outputs.
Evaluation Results
Reconstruction Fidelity
HDR VAE v3 remains very close to the original SDXL VAE in structural accuracy.
| Model | SSIM |
|---|---|
| SDXL Base VAE | 0.8555 |
| HDR VAE v3 | 0.8481 |
A small SSIM reduction is expected for enhancement-oriented VAEs. In exchange, HDR VAE v3 delivers substantial gains in perceived image quality.
Detail Preservation
One of the largest improvements in HDR VAE v3 is the retention of fine detail.
Sharpness (Laplacian Variance)
| Model | Value |
|---|---|
| Ground Truth | 172.68 |
| SDXL Base VAE | 102.12 |
| HDR VAE v3 | 165.55 |
HDR VAE v3 remains remarkably close to the source image while avoiding the softening commonly seen with the default SDXL VAE.
Edge Density
| Model | Difference from Ground Truth |
|---|---|
| SDXL Base VAE | -24.8% |
| HDR VAE v3 | -7.3% |
The improvement in edge retention helps preserve texture, architectural detail, hair, fabric, and other fine structures.
Color Performance
Color reproduction is where HDR VAE v3 shows its largest gains.
LAB Color Volume
| Model | Value |
|---|---|
| Ground Truth | 1.387M |
| SDXL Base VAE | 1.297M |
| HDR VAE v3 | 1.822M |
This represents roughly a 38% increase in color volume over the source image.
Saturation
| Model | Value |
|---|---|
| Ground Truth | 118.96 |
| SDXL Base VAE | 118.27 |
| HDR VAE v3 | 139.81 |
Colors appear more vibrant, richer, and more expressive while maintaining overall image coherence.
Color Diversity
| Metric | SDXL Base VAE | HDR VAE v3 |
|---|---|---|
| Quantized Colors | -10.1% | +16.6% |
| Unique Colors | +1.4K | +17.0K |
HDR VAE v3 consistently produces a wider variety of distinguishable colors throughout the image.
Dynamic Range & Contrast
HDR VAE v3 introduces modest but measurable improvements in image depth and contrast.
| Metric | Ground Truth | SDXL Base VAE | HDR VAE v3 |
|---|---|---|---|
| Brightness | 68.645 | 68.928 | 69.740 |
| Contrast | 56.36 | 55.56 | 56.62 |
| Dynamic Range | 244.3 | 243.0 | 246.3 |
These changes contribute to a stronger HDR-like appearance without dramatically altering image balance.
Recommended Usage
Choose SDXL Base VAE if you need
- Maximum reconstruction fidelity
- Scientific or medical imaging
- Archival preservation workflows
- Exact reference matching
- Conservative image processing
Choose HDR VAE v3 if you need
- A better default VAE for image generation
- Stronger photorealism
- Sharper textures and facial details
- Richer color reproduction
- Improved environmental and architectural renders
- More visually striking outputs
- Enhanced presentation quality
Conclusion
HDR VAE v3 intentionally trades a small amount of reconstruction accuracy for substantial gains in perceived image quality.
While the SDXL Base VAE remains the better choice for strict numerical fidelity, HDR VAE v3 delivers superior sharpness, edge retention, color reproduction, and overall visual impact, making it the recommended choice for most generative image workflows.
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Model tree for Felldude/SDXL-HDR-VAE
Base model
stabilityai/sdxl-vae