Troubleshooting
AI virtual try-on troubleshooting guide
Diagnose distorted hands, changed faces, incorrect colors, blurred details, and unrealistic garment edges.
Quick answer
Most weak results come from an unclear person photo, an ambiguous garment reference, heavy occlusion, or asking the image to change too many things at once. Fix the input connected to the visible problem first.
Match the problem to the input
If the face changes, improve the person photo. If the outfit shape or pattern changes, improve the garment reference. If hands merge with sleeves, choose a pose with less overlap.
Reduce visual ambiguity
Remove collages, extra people, mirrors, clutter, and screenshots with interface text. Use one clear person and one clear outfit before adding optional styling instructions.
- Changed face: sharper front-facing portrait
- Wrong garment: cleaner and larger clothing image
- Broken hands or sleeves: less overlap and a simpler pose
Regenerate with one controlled change
Change one input at a time so you can identify what helped. Repeatedly generating from the same ambiguous images may produce different artifacts without solving the cause.
Use a symptom-first diagnosis
Do not change every setting at once. Identify the first visible failure: identity, anatomy, garment fidelity, color, background, or overall realism. Then replace the input most directly connected to that failure.
Separate input problems from model limits
Blur, occlusion, tiny references, and confusing prompts are input problems you can fix. Exact fabric physics, perfect logos, concealed garment construction, and precise body measurements are limitations a better prompt cannot guarantee.
Know when to stop regenerating
If three attempts from the same inputs fail in the same area, stop and change the source material. Repeated generation is useful for normal variation, but it is inefficient when the model consistently lacks visible information.
Record a minimal reproducible case
For a persistent failure, save the exact person photo, garment image, short instruction, and result. Remove optional instructions and test the simplest version. This makes it easier to see whether the problem follows the pose, garment type, or prompt—and gives support a clear example if you need help.
Apply different standards to creative and factual work
A fantasy outfit concept can remain useful even when embroidery changes slightly. A boutique catalog image cannot. Decide the acceptance threshold before reviewing the output: identity and overall mood for creative work, or strict color, construction, pattern, and accessory verification for product-facing work.
Troubleshooting order
- Name the single most important visible error
- Check whether the relevant detail exists in the input
- Remove unnecessary prompt instructions
- Replace only the person or garment image first
- Compare at full resolution
- Stop after repeated identical failure and change the source
Common failures, causes, and fixes
| Failure | Common cause | First fix to try |
|---|---|---|
| Face changed | Small, filtered, angled, or shadowed face | Use a clearer front-facing person photo |
| Hands or sleeves are malformed | Hands overlap waist, sleeves, or garment edge | Use a pose with visible separation |
| Wrong color | Colored light, reflection, or compressed garment image | Use a neutral-lit reference |
| Pattern becomes blurry | Pattern is too small or partially hidden | Use a sharper, larger front view |
| Background changes | Prompt asks for a new mood or scene | Remove scene instructions and preserve the original composition |
Common questions
Why did the outfit color change?
Colored lighting, compression, reflections, or an ambiguous reference can cause the generated image to reinterpret color.
Why did my body shape change?
Generated try-on images may reinterpret contours to accommodate the target clothing. They are not measurements or exact fit simulations.
Is a different result on every generation normal?
Yes. Generative output varies, but recurring failures usually point to ambiguous input or a capability limit.
Will a longer prompt fix anatomy?
Usually not. A less obstructed pose and clearer source photo are more useful.
Why does a layered outfit lose pieces?
Overlapping garments hide construction and require the system to infer which layer sits above another. Use a clearer complete reference or simplify the outfit.
Ready to try a look?
Choose an outfit, upload one clear photo, and create your own Dressora virtual try-on.