Use case · Activewear and outdoor

Generate activewear and outdoor photos from your product references

Supply front, back, seam and logo photos. Your assistant proposes Product page set, shows the credit estimate, and flags missing full-length views before generation.

Set up Uwear MCPCheck model credit rates
Model wearing a hooded fleece jacket, full-body front, generated with nano-banana-pro in Basic white photoshoot through the Uwear MCP

Uwear library example: hooded fleece jacket, generated with nano-banana-pro in Basic white photoshoot. This example shows styling, not garment performance.

Production signals

  • Source photos guide the brief
  • Cost approval before generation
  • Automatic QA, on or off

Mechanism

How does the assistant build the photo set?

Model wearing the same hooded fleece jacket, upper-body back camera edit generated with nano-banana-pro through the Uwear MCP
Upper-body back camera edit of the front example, generated with nano-banana-pro through the Uwear MCP. This library pair is not a full Product page set run.

Ask the Uwear MCP to propose Product page set with Basic white photoshoot. Review full-length leg references and flag unsuitable default crops before approving the brief.

Workflow

The production loop

  1. Prepare the source views

    Supply front and back flats, seam and logo details, waistband and cuff photos, pocket and hood references, and a brand-approved activity and styling reference.[1][2][5][8]

  2. Approve the proposed template

    Start with Product page set and Basic white photoshoot. Ask the assistant to flag missing views and show the credit estimate before generation.[8][9]

  3. Compare the results

    QA is automatic and toggleable: when on, an AI reviewer compares results with source photos and retries flagged results.[8]

Outcomes

What this unlocks

  • Check full-length framing

    Leggings need full-length leg references. Test the framing: the default upper-body crop cannot show the whole leg. An activity pose does not establish compression, waterproofing or performance.[1][2][3][8]

  • Check the destination brief

    Zalando’s sports guide asks for styling matched to the activity, compatible shoes, consistent drawstring lengths and visible construction. Its AI/model eligibility wording remains unresolved. Confirm eligibility before submitting generated model photos.[5][6]

Run it from your assistant

Run this photoshoot from your AI assistant with a Uwear template.

Connect the Uwear MCP server to ChatGPT, Claude, or Codex and ask for the Product page set template. It is a batch workflow that runs once per garment: front, upper-body, and back product-page shots on a white studio background, plus a 360-degree video, from one garment photo. Any Uwear account can load it by name, and the assistant shows a costed brief in credits before generation starts.

For a separate activity campaign, propose Instagram drop with Low-Angle Concrete Flash Studio. An outdoor setting is a brief choice; the direction does not prove terrain or technical performance.

Copy this prompt into your assistant

Use the Uwear MCP to propose a Product page set with Basic white photoshoot on Pure White, using nano-banana-pro, for my uploaded activewear. Review the front, back, logo, seam and fastening references. Flag missing full-length views and any unsuitable default crop. Show the costed brief in credits and wait for approval. Enable the AI reviewer for automatic QA to compare and retry, then return image and video URLs. Do not treat a generated activity pose as evidence of garment performance.

Set up the MCP server

What one run does, per garment

  1. Generate the front hero

    One full-body front photo of the garment on the template model, in the Basic white photoshoot art direction on the Pure White studio location.

  2. Edit to the upper-body crop

    A camera edit that reframes the front result to an upper-body front frame instead of generating a new image, so the crop comes from the same session as the hero.

  3. Edit to the back view

    A second camera edit of the front result to a full-body back frame, so the product page gets the back of the garment from the same session.

  4. Render the 360 turn

    A 5-second Kling 3 Pro video from the front photo: the model turns a slow, full 360 degrees in place, garment readable throughout.

Outputs per garment

  • Full-body front photo, 2K, 2:3
  • Upper-body front photo, 2K, 2:3
  • Full-body back photo, 2K, 2:3
  • 5-second 360-degree video

The setup the template pins

Template kind
Batch workflow: runs once per garment row
System key
demo_full_pdp_test_white_studio
Art direction
Basic white photoshoot is the starting system art direction. For a separate urban training campaign, propose Instagram drop with Low-Angle Concrete Flash Studio.
Location
Pure White (system studio location)
Model
The Uwear system model by default; the assistant can swap in one of your saved models when it proposes the brief
Image model
nano-banana-pro, 2K, 2:3
Video model
Kling 3 Pro, 5 seconds
QA
Optional. With the AI reviewer on, each result is checked against the source product photo and flagged results are retried
Approval
The assistant shows a costed brief in credits before anything generates

Frequently asked questions

Supply front and back flats, seam and logo details, waistband and cuff photos, pocket and hood references, and a brand-approved activity and styling reference.[1][2][5][8]

Propose Product page set with Basic white photoshoot for front, upper-body and back photos plus a 360 video per garment. Show the costed brief before approval. For leggings, test full-length framing and flag an unsuitable upper-body crop.[8][9]

Compare source views separately. Gymshark describes waistband and hip and calf logos; Arc’teryx labels hood and full-body views; lululemon specifies a 25-inch inseam. Use those details as inspection points. Automatic QA compares and retries; it does not guarantee geometry.[1][2][3][8]

Zalando’s sports guide asks for styling matched to the activity, compatible shoes, consistent drawstring lengths and visible construction. Its AI/model eligibility wording remains unresolved. Confirm eligibility before submitting generated model photos.[5][6]

QA is automatic and toggleable: when on, an AI reviewer compares results with source photos and retries flagged results. Use the Uwear MCP first. Credits cost $0.10 per credit; see /models for model rates. The REST API is the fallback for pure automation, with polling or callbacks. Studio is the manual path.[8]

No. An image of exercise is not evidence of compression, waterproofing or performance. Treat the activity and setting as brief choices. Test full-leg framing, mesh and logo placement against the supplied references.[1][2][5][8]

Sources and access dates

  1. [1]
  2. [2]
  3. [3]
  4. [5]
  5. [6]
  6. [8]
  7. [9]

Next step

Map this workflow into your catalog operation.

Start with the Uwear MCP. Use the asynchronous REST API for pure automation and Studio for manual work.

Set up Uwear MCPCheck model credit rates