Felldude/QWEN_2.1_HDR_VAE

Qwen Image 2.1 HDR VAE

Fine-tuned Qwen Image 2.1 autoencoder for RGBA / HDR-oriented reconstruction.

The goal is stronger dynamic range, color volume, and detail energy for HDR-style workflows—not perfect fidelity to the source frame.

Eval

Relative to ground truth and compared with base Qwen 2.1 VAE (VAE A):

Metric	VAE A (Qwen 2.1 VAE)	VAE B (HDR)	vs GT
Lab color volume ratio	~0.81×	~1.34×	+34% color volume
Edge density ratio	~0.95×	~1.50×	+50% edge density
Gradient strength ratio	~0.97×	~1.16×	+16% gradient energy
Sharpness ratio	~0.96×	~1.99×	~2× sharpness
Saturation ratio	~0.99×	~1.20×	+20% saturation
SSIM	0.958	0.944	Slightly lower (expected)
PSNR	38.1 dB	32.0 dB	Lower (expected)

VAE B deliberately overshoots GT on Lab color volume, edge density, and gradient energy. VAE A stays closer to GT on SSIM/PSNR but compresses color volume and softens detail. That tradeoff is the point of this checkpoint.

Technical notes

• Base: Qwen Image 2.1 VAE (z_dim=64, 16× spatial compression)
• Input / output: RGBA, normalized to [-1, 1]
• Layout: [B, 4, 1, H, W] (single-frame temporal dim)
• Uses the VAE’s own latents_mean / latents_std (no FLUX/SD 0.18215 scaling)
• Trained / evaluated around 512–1024 resolution; spatial size should be divisible by 16

Intended use

• HDR-oriented encode/decode in Qwen Image pipelines
• Image editing / generation stacks that benefit from punchier latents
• Research on RGBA + high dynamic range autoencoders

Not intended for: archival reconstruction, metrics-maximizing ablations, or any setting where matching the input pixel-for-pixel matters more than look.

Limitations

• Will diverge from the source on sharpness, saturation, and color volume by design
• Alpha is supported; behavior on unusual alpha mattes is not heavily tuned
• Very large resolutions are memory-heavy (16× latent downscale)

License

See LICENSE (Qwen Research terms).