Product · Single image · 3 credits

Marketplace-compliant white-background photos, in minutes

Pure white backdrop, correct margins, no shadow drift. Pass Amazon, Walmart, and Shopify image review on first submit.

Standardize a product photo See pricing

Mixed shots in. Catalog-clean out.

Every result below was generated from the photo next to it. No cherry-picking.

Input

Pixfino output

Marketplace policy compliance

Each output is checked against current Amazon, Walmart, and Shopify image guidelines before delivery.

Phone photo to PDP-ready

Sellers don't need a studio. Phone snapshot in, marketplace-ready out.

Shadow as a parameter

Some marketplaces ban contact shadows on the main image; the preset handles per-image policy variants.

Who this is for

Marketplace sellers

Job

Pass Amazon/Walmart image review on first try

Friction

Each marketplace's image policy is different and strict.

Brand aggregators

Job

Standardise photo quality across an acquired-brand portfolio

Friction

Each acquired brand ships photos to a different standard.

3PL listing services

Job

Service per-SKU listing prep at scale

Friction

Manual photo cleanup is the throughput ceiling.

Retailer-DAM distributors

Job

Hit retailer image specs without designer help

Friction

Each retailer's DAM has its own intake spec.

How it works

1. 1

   Upload the product photo

   Phone or studio shot. The renderer isolates the product and replaces the backdrop with pure white.

   Replaces: Photoshop pen-tool isolation per SKU.

2. 2

   Pick shadow style

   None (Amazon main image), contact (PDP secondary), or drop (lifestyle accent).

   Replaces: Photographer-set shadow placement.

3. 3

   Generate

   One render, ~20 seconds. Output is RGB 255/255/255 backdrop with correct product margins.

   Replaces: Manual cleanup pass per SKU.

4. 4

   Bulk-upload to marketplace

   Pass image-quality review on first submit; failed uploads drop to near-zero.

   Replaces: Bounce-and-resubmit cycles.

Pixfino vs traditional production

	Traditional studio	Stock + retouch	Pixfino
Lead time	1-3 days	Same-day	Under 1 minute
Per-photo cost	$15-$50	$8-$15	3 credits
Iterations	Re-shoot or re-edit	Slow	Unlimited
Compliance	Designer-checked	Generic	Built to current spec
Scale ceiling	100-200/day	Slow	Thousands per hour
Revisions	Charged per pass	Re-purchase	Free re-runs

Questions and answers

Will it pass Amazon image review?

Output is built against Amazon's published main-image guidelines. Always confirm against the latest policy version.

Will the product silhouette stay clean?

Yes — the renderer detects edges precisely and avoids the halo artefacts manual masking sometimes produces.

Can I batch this across my catalog?

Yes. POST a list of product photos via the API; one credit cost per image.

What about shadows for hero PDP shots?

Shadow style is a parameter — none, contact, or drop — so you can match per-marketplace policy.

Does this handle reflective products?

Yes — chrome, glass, and polished surfaces are isolated cleanly.

What resolution do I get?

1024px on the longest edge; 2x via the API for retailer DAM intake.

Related templates

360° Product Spin Video

Product · 22 credits

Flat Lay Composition

Product · 3 credits

Lifestyle Context Shot

Product · 3 credits

Lifestyle Motion Video

Product · 40 credits

Measured quality

Full QC report →

White-Background Standardizer

oaktree/image-edit · $0.04/image

high pass-rate baseline

The easiest of the shoe presets and our highest pass rate — included as an honest contrast so the harder presets read in context, not as a wall of identical 99%s.

Background compliance

target ≥ 95% PDP pass

98.7% pass

n=99 · 95% CI 98.47–98.98 · BiRefNet_lite (transformers 4.52.4) + numpy 2.4.6 · pipeline v3.1 · set shoes-v3 · measured 2026-06-16

Color fidelity (ΔE 2000)

target ≤ 2.0 ΔE (imperceptible)

1.75 ΔE pass

n=99 · 95% CI 1.15–2.36 · BiRefNet_lite (transformers 4.52.4) + colour-science 0.4.7 · pipeline v3.1 · set shoes-v3 · measured 2026-06-16

Frame occupancy

target ≥ 85% of frame (Amazon spec)

91.8% pass

n=99 · 95% CI 91.64–92.10 · BiRefNet_lite (transformers 4.52.4) + numpy 2.4.6 · pipeline v3.1 · set shoes-v3 · measured 2026-06-16

Silhouette preservation

target ≥ 0.90 shape IoU

0.933 IoU pass

n=99 · 95% CI 0.90–0.96 · BiRefNet_lite (transformers 4.52.4) + numpy 2.4.6 · pipeline v3.1 · set shoes-v3 · measured 2026-06-16

Perceptual drift (LPIPS)

target threshold pending calibration

0.130

n=99 · 95% CI 0.10–0.16 · piq.LPIPS (mask-aligned crop) 0.8.0 · pipeline v3.1 · set shoes-v3 · measured 2026-06-16

Auto-QC first-pass rate

target ≥ 85% first pass

97.9% pass

n=99 · 95% CI 92.93–99.45 · pixfino-qc-gate n/a · pipeline v3.1 · set shoes-v3 · measured 2026-06-16