Running a store by yourself, the visual work is not one task. It is a chain, and the chain has a specific place where it jams.
For me it was never generation. Generation is fast. The jam is upstream, in preparing inputs, and downstream, in deciding what is good enough.
The chain
| Stage | Time share for me | Can it be automated? |
|---|---|---|
| Shooting or sourcing the source photo | Large | No |
| Preparing inputs, cropping, cleaning, aligning | Large | Partly |
| Generating | Small | Yes |
| Selecting from the outputs | Large | No |
| Exporting to every required size | Small | Yes |
| Publishing | Small | Partly |
Generation is the smallest slice. Optimising it feels productive and moves the total very little.
Fix the input stage first
Most of my early rework traced back to inconsistent inputs rather than anything the model did.
Shoot against one background. Not a nice background, just the same one every time. Consistent input is worth more than good input.
Shoot at one camera height. Mixed perspectives inside a batch cannot be reconciled later.
Crop to a fixed ratio before generating. Doing it after means the composition was decided by the model rather than by you.
Name files so the SKU is recoverable from the filename. Sounds trivial until you have four hundred outputs and no idea which is which.
Those four take an afternoon to set up and remove most downstream problems.
Decide what good enough means, once
Selection was my real bottleneck. Looking at outputs and deciding case by case is slow and inconsistent, because the standard drifts as you get tired.
What helped was writing down a pass condition and checking against it instead of judging.
My pass condition, for reference:
- The item is recognisable as the item
- Colour matches the reference photo
- Nothing in frame that is not included
- Text, if any, is legible at thumbnail size
Four checks, answered yes or no. Selection went from minutes per image to seconds.
Batch by stage, not by SKU
The instinct is to take one SKU all the way through, then start the next. It is the slower way.
Working stage by stage across the whole batch is faster, because each stage has its own setup cost that you would otherwise pay once per SKU. Prepare all inputs, then generate all, then select all, then export all.
It also makes drift visible, because you are looking at many outputs from the same stage side by side rather than one at a time.
What I gave up trying to automate
Selection. Every attempt to automate it produced a worse standard than the four checks above.
Sourcing the original photo. There is no way around having a real photograph of the real item.
Deciding which SKUs are worth the effort at all. That is a commercial judgement, not a production one.
Where the tool choice actually matters
Two things, and neither is output quality.
Concurrency, because it decides whether a batch finishes inside a working session or spills into the next day. Entry tiers commonly allow two.
Whether style constraints can be stored as configuration rather than restated per request. TangyuanAI's pricing page lists 5 brand kits on its entry tier (pricing page, checked 6 August 2026), which is the mechanism that keeps a batch consistent without you re-describing the style every time.
Checklist
- One background, one camera height, one pre-crop ratio
- SKU recoverable from the filename
- A written pass condition, checked rather than judged
- Batch by stage, not by SKU
- Concurrency cap checked against your batch size
- Style constraints stored as configuration
Sources
Tier data comes from the TangyuanAI pricing page, https://tangyuanai.vip/en/pricing , checked 6 August 2026. The workflow and the pass condition come from my own production notes. Output depends on the uploaded material and the brief.
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