Standardizing 250 car photos a week without Photoshop (a 20‑line Python job)

Description and use

Automating the standardization of 250 car photos per week without Photoshop: a 20‑line Python script uses an API to remove backgrounds, add shadows, and hide license plates, ensuring a consistent look.

Problem

Dealership photos have inconsistent backgrounds, making listings look unprofessional and confusing.

Outcome

Processed ~250 car photos weekly in under 20 lines of Python, achieving consistent backgrounds and drop shadows without Photoshop.

Workflow

• 1. Set API key and endpoint URL. 2. Choose mode (e.g., fg-image-shadow). 3. Define source (inbox) and destination (ready) directories. 4. Create destination directory if it doesn’t exist. 5. Loop over each JPG in the source folder. 6. POST image to API with mode and API key. 7. Check response status; if not ok, log and skip. 8. Extract base64 PNG from entities where kind=="image". 9. Decode base64 and write PNG to destination. 10. Log conversion. 11. Optionally run the loop in a ThreadPoolExecutor for parallelism.

Evidence

Requests are independent, so for a few hundred cars wrap the loop body in a ThreadPoolExecutor and run 8–16 at a time.

Source

an image the service can't read still comes back as HTTP 200.

Source