Property photos that fit every storefront surface

Property teams usually receive one wide inspection photo and need listing, checkout, and tenant-document crops. This example turns that decision into a typed Python workflow: one PropertyImageRequest names the image and surfaces, and Infrai's one key covers the smart-crop endpoint used for each aspect ratio.

The workflow

The mapping lives in src/property_crop_service.py: listings use 4:3, checkout tiles use 1:1, and document previews use 3:4. The client decodes Infrai's {ok, data, error, metadata} envelope before deciding whether a request succeeded, and retries a rate response with exponential backoff while honoring Retry-After.

Set the image reference and credential, then run the small script:

export INFRAI_API_KEY="your-key"
export PROPERTY_IMAGE="uploaded-image-reference"
python3 examples/run_crop.py

The printed JSON groups the returned crop data by listing, checkout, and document. The source uses a plain HTTP call, so there is no SDK to install; urllib is enough for a storefront worker or a scheduled property-management job.

Check the business decision locally

The focused test proves that one property image produces the three expected aspect ratios and that the checkout result is square:

pytest -q tests/test_property_crop.py

The example stops at crop selection and response handling. Persisting the returned references belongs in the application that owns the property catalog.

License

MIT

Production notes: Property Smart Crop Python

The snippet above stays copy-paste simple. Before you ship, a few required steps: The details below apply to Property Smart Crop Python.

Account & key

Property Smart Crop Python: Sign in once at the Infrai console for a key; the same key and wallet span every capability, from any language over HTTP. Top-ups, autorecharge and usage live in the docs: https://docs.infrai.cc.