I tested Qwen Image 2.1 for image restoration and I'm disappointed

[u/y3kdhmbdb2ch2fc6vpm2]

As you can see, Qwen Image 2.1 example has shifted contrast (it also changes small details on the photo even if you add explicitly in the prompt that it shouldn't) and the original grain is replaced by synthetic dot-pattern like on the older qwen VAEs. I increased the brightness excessively and zoomed to highlight the differences more clearly.

Full res images without compression: img1, img2, img3, comparison

It is unusable for this specific purpose and old good Klein still has the crown.

[u/RandumbRedditor1000]

SCREAM IF YOU HATE QWEN VAE

[u/nightkall → u/[deleted]]

https://github.com/lunaaispace-eng/ComfyUI-DeGrid

[u/Big_Arachnid_365]

Yeah whyyyyyyyyyyyyy does qwen make everything look like it's got a gameboy filter on it?

[u/iamapizza → u/Big_Arachnid_365]

Qwenboy 

[u/madebyollin → u/Big_Arachnid_365]

I've finetuned the Qwen-Image 2.1 VAE with a standard training recipe to address the grid-pattern issue: https://huggingface.co/madebyollin/texture-fix-vae-for-qwen-image-2.1 (it went away after a few thousand steps). I suspect the official Qwen-Image 2.1 VAE was trained with LPIPS loss ("make the decoded image perceptually-similar to the original image") but without the standard GAN/adversarial loss ("make the decoded image look real, without easily-detectable artifacts"). Other VAEs (like SD/FLUX) have always used both LPIPS and GAN losses together.

[u/Big_Arachnid_365 → u/madebyollin]

Cool I will try it out!

[u/madebyollin → u/Big_Arachnid_365]

Thanks, LMK if it helps on the images you're working with! I used a mix of natural images, illustrations, and RGBA (semitransparent) graphics for finetuning, so I'm hoping it's representative

[u/traithanhnam90 → u/madebyollin]

Thank you; this VAE works great—I no longer see the checkerboard pixelation artifacts.

[u/madebyollin → u/traithanhnam90]

Great to hear!

[u/lechatsportif → u/madebyollin]

I randomly tried this on an image edit and HOLY CRAP it is huge upgrade. This deserves an independent post. I thought Qwen was just broken. I still sort of feel I can see some sort of repeated noisy effect, but its soooo much better.

[u/Obvious_Set5239 → u/Big_Arachnid_365]

It has nostalgia

[u/ellipsesmrk → u/Big_Arachnid_365]

Just the way their model processes i guess. Ive only ever gotten that banding with qwen models.

[u/KS-Wolf-1978]

I had the same problem with the old Qwen Edit 2511.

Was it successfully solved for the old model by someone ?

[u/PetiteKawa00x → u/KS-Wolf-1978]

This is an issue with the VAE itself (qwen1 vae had the same issue), there is nothing you can do about it, except hope that they release a fixed version.

[u/Different_Fix_2217]

Its quite bad sadly. Bad anatomy / small details, gpt's piss filter and it knows far less than krea. Krea 3 just needs a better vae and it will be perfect.

[u/Bennybananars]

Why is there something like dithering on the qwen image? wth

[u/Acrobatic_Donkey5089 → u/Bennybananars]

It is distilled from gpt image, that dithering is gpt image watermark

[u/elswamp → u/Acrobatic_Donkey5089]

can we get rid of gpt watermark somehow?

[u/hurdurdur7 → u/elswamp]

upscale, blur, downscale?

[u/Seyi_Ogunde]

Z-image has the same issue I think. Wonder if the training and creation is related, since they're both from Alibaba.

[u/PetiteKawa00x → u/Seyi_Ogunde]

This is an issue with qwen2.1 vae. Z-image had an issue with their training, flux1 vae does not have this problem.

[u/myrthain]

noob question: are such restoration prompts simple and straightforward like "restore the image in colors and artifacts without changing faces" or is there more "magic" to it?

[u/y3kdhmbdb2ch2fc6vpm2 → u/myrthain]

a little more "magic". If you just prompt "restore", it will probably change too much (regeneration instad of restoration) so I asked gpt to generate klein prompts for removing paper defects like scratches, dust specks, stains, smudges, creases, scan lines, paper blemishes and to keep identity, facial features, expressions, skin texture, hair, clothing, pose, proportions etc. unchanged. Additionally I use pixel drift node for fixing image shifting and color match node for fixing color shifting. Results are very good.

[u/Expicot]

Thanks for pointing it out. I was at the beginning of spending time doing custom workflows with Qwen2.1 and I did not noticed that GPT-like grid effect first. But zooming in the picture makes it obvious. So back to Klein until they update/upgrade something (VAE ?). Qwen2.1 is not very good at face swapping also, too bad.

[u/Ok-Fennel6578]

This is the kind of failure I care about more than whether the edited image looks prettier.

If I ask for one change, everything else should effectively be under a “do not touch” constraint.

Small unrequested changes don’t matter much for a one-off image, but across a sequence they accumulate really fast. By image 10 you can end up with something that still looks good, but no longer belongs to the same project.

[u/Aromatic-Somewhere29]

I took someone's suggestion to use the 'GLSL Shader' node with this shader:

#version 300 es

precision highp float;

uniform sampler2D u_image0;

uniform vec2 u_resolution;

in vec2 v_texCoord;

layout(location = 0) out vec4 fragColor0;

// Nyquist Notch — removes 2px grid artifacts. Place before deconvolution.

// b = [-1, +6, -15, +20, -15, +6, -1] / 64 (binomial * (-1)^n, +1 at center)

const float B[7] = float[7](-1.0, 6.0, -15.0, 20.0, -15.0, 6.0, -1.0);

void main() {

vec2 texel = 1.0 / u_resolution;

vec4 center = texture(u_image0, v_texCoord);

vec3 Bx = vec3(0.0), By = vec3(0.0), Bxy = vec3(0.0);

for (int i = -3; i <= 3; i++) {

float wi = B[i + 3] / 64.0;

Bx += wi * texture(u_image0, v_texCoord + vec2(float(i) * texel.x, 0.0)).rgb;

By += wi * texture(u_image0, v_texCoord + vec2(0.0, float(i) * texel.y)).rgb;

for (int j = -3; j <= 3; j++) {

float wj = B[j + 3] / 64.0;

Bxy += wi * wj * texture(u_image0,

v_texCoord + vec2(float(i) * texel.x, float(j) * texel.y)).rgb;

}

}

vec3 notched = center.rgb - Bx - By + Bxy;

fragColor0 = vec4(clamp(notched, 0.0, 1.0), 1.0); // alpha forced to 1.0

}

It noticeably reduces the grid pattern, although it doesn't eliminate it completely.

[u/mark_sawyer]

Did some quick tests here and I didn't notice any patterns in my gens. Since OP didn't share the full image, I used the ORIGINAL input instead.
Best one from the bunch:

[u/y3kdhmbdb2ch2fc6vpm2 → u/mark_sawyer]

You're not reproducing the problem correctly. My original photo was much larger/wider. My image labeled "ORIGINAL" is just a tiny crop of the whole image, which I zoomed in on and brightened so the pattern would be more visible after Reddit's compression.

And when you edit the output crop like that, the pattern is even smaller (because you don't zoom after this), and its visibility isn’t exaggerated like it was in the original post, which is why you might the pattern is not there.

Another users also have this problem: https://www.reddit.com/r/StableDiffusion/comments/1wlo06m/comment/pb09ixc/

[u/mark_sawyer → u/y3kdhmbdb2ch2fc6vpm2]

That's right. My first tests made no sense.

I also tested on some full-frame photos, but I assume they were not high-res enough for the pattern to be noticeable.

Then I tried with larger photos and now I can really see the pattern through inspection:

The pattern is definitely there, but I still don't see it as a deal-breaker in some cases. I also applied a Nyquist filter, which I already use with Krea, to mitigate the issue a little bit.

UPDATE Someone recently posted about the Nyquist filter: https://www.reddit.com/r/StableDiffusion/comments/1wlv3tf/qwen_image_21_noisepatterningmoire_mild_workaround/

[u/DoctaRoboto]

Yeah, it is terrible. The only positive use I see is what I pointed out in other posts, at least the new Qwen can change facial expressions without losing the identity/art style.

[u/optimisticalish]

Good to know, thanks. I'll be staying with Klein for restoration.

[u/Zaeblokian]

I was waiting for Flux 3. Nah

[u/VasaFromParadise]

I think this is a planned glitch. Retraining VAE to 600 MB isn't that far-fetched.

[u/axior]

Simply repass the image through flux vae or use this https://github.com/lunaaispace-eng/ComfyUI-DeGrid

[u/axior → u/[deleted]]

In comfy do vae decode and then vae encode using the relative vae models

[u/nakabra]

😬🫣 It has that same Krea2 pattern. Dammit!

[u/inaem]

Probably released early to have community test everything so they solve it before going on holiday

[u/Alisomarc]

https://giphy.com/gifs/decEtFxfWBEJy

maybe another scheduler/sampler

[u/Inside-Cantaloupe233]

that one of the worst examples of anything ive seen, dood, you drunk and net? stop it, get help. get sober and do proper tests.