AI Lookbook Image QC
Without the Eye Strain? Let Opus 5.5 Handle It

You've made your AI lookbook, and now you're zooming into every single image: is the logo spelled right, is the pant length right, is the coat the right length?
Ten images is doable. A hundred, and your eyes are ready to give up.

So at StyleRoom, we handed this QC job to AI.
Spoiler: it's way pickier than we expected!

01 · CheckAI lookbook image QC: what people have been checking by hand

Until now, a person would pull up the original garment photo on the side and go through every image by eye.
AI-generated images all look convincing at a glance, so the mistakes only show up when you zoom in.

We handed this exact checklist to Claude, and here's what we asked.

"When I do AI lookbook image QC, I usually look at this, this, and this. I've put the original images and the generated AI lookbook images in the folder, so check them for me as strictly as you can and tell me what's wrong. If you need to know anything to do the QC, just ask me."

For the first few rounds I used Claude Opus 5.5. The results were so impressive that I ran the same test with Sonnet 5.5 too, and got results that weren't far off.

02 · HowHow Claude does QC: scan, zoom, compare side by side

It shrinks the image down and looks at the whole thing first. This is where it catches the big problems, like the model turning into a different person or the garment design changing completely.

It crops only the suspicious areas at full resolution and lines them up side by side with the same area in the original garment photo. Think logos, cuffs, pant hems, and toes.

Along with pass or fail, it writes down where and why things differ, and whether to regenerate the image or fix just that part.

03 · CasesWhat Claude actually caught

Floor-sweeping jeans that stopped at the ankle

The original is a pair of wide flare jeans that open up below the knee and pool on the floor, almost covering the feet.
The generated result was a straight wide leg that ended at the ankle. The high rise, stitching, and buttons were all correct, but the length and silhouette were off.

Same cap, different color

The shape and the PG logo are unchanged, but the color shifted just slightly. The original is a washed taupe cap, while the generated result came out dark gray.
Looking at one image on its own, you'd miss it. Claude also pointed out that the embroidered lettering on the brim had disappeared.

The tiny flower logo on the left chest

This is the Pg flower logo on the left chest of a brown knit. In the original, it's a white flower with a smiley face drawn in brown lines. In the generated result, the center of the flower was filled in yellow.
The PG lettering and petal shapes were slightly off too, and instead of a knitted texture, it came out looking like a smooth print.

Logo shapes, down to a single digit

It caught the small script logo on the chest of a knit vest being drawn in a different shape from the original, and even 'EST.1989' turning into 'EST.1988'.

In each pair: original on the left, generated result on the right

5 Style Shot background composites: Claude's QC report

Here's the QC report for Style Shots where a model was composited into a reference background.
We only checked whether the model landed in the reference space in the same pose, without anything looking physically off.
Claude compared each image as a whole, then zoomed into the toes, hands, and contact points at full resolution.

01BeachFail · Critical

The composite itself failed. This is beyond what a partial fix can repair.

Why it failed

• There's no head, and the upper body is see-through. You can see the sand and palm trunks behind him right through the T-shirt.

Zoomed-in evidence

02Window wallFail

It looks like a front-facing model was pasted in front of the wall. The pose, feet, and lighting all differ from the reference.

Why it failed

• Different pose. In the reference, she stretches one arm overhead against the wall and leans at an angle. In the result, he has a hand on the back of his head and stands straight, facing forward.
• Feet floating in midair. The reference is framed so the floor isn't visible, but the result includes the shoes. They float in front of the wall with no floor beneath them and no shadow underfoot.
• Lighting mismatch. In the reference, warm side light comes in from the window on the right. The model is lit evenly from the front, so he looks cut out and pasted in.

Zoomed-in evidence

03Concrete railingFail

The lean against the railing turned into a stiff, at-attention stance, and the feet aren't standing on anything.

Why it failed

• Different pose. In the reference, she leans with her hands on the railing and her legs crossed. In the result, he stands facing forward at attention with both arms down, touching the railing nowhere.
• Feet floating in midair. The shoes float in front of the concrete wall. The floor tiles are only on the right, so the feet hang over the line between wall and floor without standing on either.

Zoomed-in evidence

04Street sidewalkFail · Subtle

It looks the most natural, but the spatial depth doesn't add up. This is the kind that's easy to miss at a glance.

Why it failed

• Hand on an unreachable wall. Follow the line where the building wall meets the sidewalk, and at the model's distance the wall is off-frame to the right. The spot his hand touches is a few meters behind him, so in reality his arm couldn't reach it. The shadows around the hand look natural, which makes it even easier to be fooled.
• Different pose. In the reference, she reaches her arm out into the air and stands with her legs apart. In the result, he leans on the wall with his legs crossed.

What worked

• The feet are planted properly on the sidewalk, and the shadows and sunlight direction mostly line up.
• The hand holding the coffee and the overall scale look natural.

Zoomed-in evidence

05Basement storage roomConditional pass · On hold

There are two things left to check.

What worked

• The pose is nearly identical, from the angle of her shoulder against the pillar's edge to the tilted head, the hand on her waist, and the lowered arm.
• She sits in the same spot between the pillar and the shelves, at a similar size.
• The front foot is planted properly on the floor, and the shadow under the skirt looks natural.

Needs a check

• Background changed. A ceiling light that wasn't in the reference appeared in the upper right, and the overall tone of the space shifted from bright and cool to dark and warm. The structure of the space, like the shelves and the cracks in the floor, is unchanged.

04 · ResultThe AI lookbook QC test at a glance

We deliberately used a very strict standard, so not even the smallest difference slipped through.
And most of the issues could be solved by generating one more time or fixing just that part.

05 · HumanThe final call stays with a human

When something is unclear, Claude doesn't force a conclusion.

When the original is low-resolution. It said it couldn't be sure and marked it 'on hold.' The sharper the original, the more accurate the QC.

When the text is really small. For tiny text like sock or shoe tags, it simply flags that the text is smudged and leaves the final call to your team.

Instead of a person checking all hundred images, you only need to check the spots Claude picks out.

06 · EnterpriseAutomated QC is coming to
our high-volume Enterprise workflow

StyleRoom is building this automated QC feature into the workflow for Enterprise users who create lots of looks at once.

Auto mode. Shots that pass QC are approved automatically and move on to the next step.
Manual review. Your team reviews the QC results and approves shots themselves.

Every shot gets a status like 'Passed QC' or 'Needs manual fix,' and problem areas are marked with numbered boxes right on the image.
And if you already run local agents from Claude, GPT, and others, you'll get access to even more powerful automation.

07 · FAQAI lookbook image QC: frequently asked questions

Can AI really handle AI lookbook image QC?

Yes. In this test, the AI agent Claude compared generated images against the original garment photos, model, and background, and flagged problems with logo lettering, pant length, fabric, pose, and background compositing.

What kinds of problems does it catch?

Logo and lettering spelling, color and fabric, length and silhouette, pose, and background compositing issues, right down to floating feet or a hand resting on a wall it could never reach.

Can it check tiny text or low-resolution images?

Yes. But when it can't say for sure, it marks the image as 'on hold' and leaves the final call to your team.

When can I use automated QC?

We're building it into our Enterprise workflow for high-volume production as an automated QC feature. You can reach us through the Enterprise page.