CONTENT CREATION

Generate marketplace size variants from a single Dropbox product photo

On each Dropbox drop, removes the background and fans out a fixed set of marketplace-spec variants (thumbnail, square listing.

CategoryContent Creation
Enginesim
Difficultyintermediate
Triggerevent
Steps5
Setup~15 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew product photo in DropboxDropboxDropbox
  • ActionRemove background via ReplicateReplicateReplicate
  • ActionCenter cutout on square canvas
  • LogicFan out to thumbnail / listing / zoom sizes
  • OutputUpload each variant to R2CloudflareCloudflare R2

What it does

Takes one product photo and produces the exact size and aspect-ratio variants your sales channels demand. After Replicate strips the background, the pipeline resizes the cutout into a thumbnail, a 1:1 listing image, and a high-resolution zoom view, uploading each to R2 under predictable, channel-named keys.

When to use it

Use it when different marketplaces enforce different image dimensions and you are tired of manually exporting three or four crops per SKU. Drop the master shot once; get every required size back, named so a feed builder can pick them up by convention.

How it works

  1. 1A new file in the Dropbox folder triggers the run.
  2. 2The image is downloaded and sent to Replicate for background removal.
  3. 3The transparent cutout is centered on a square canvas to satisfy marketplace 1:1 rules.
  4. 4A fan-out step renders the thumbnail, square listing, and zoom resolutions from that canvas.
  5. 5Each variant uploads to R2 at a deterministic key like `sku/<name>/<size>.png`, ready for the catalog feed.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect DropboxFiles and folders.
  2. 2
    Connect ReplicateImage, video, and model inference.
  3. 3
    Connect Cloudflare R2Object storage, S3-compatible.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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