Parameter
key
requiredExample
YOUR_API_KEY_HERE
Description
Your VinAudit API key
docs / api / images / background
The Vehicle Background Removal API uses AI to remove, replace, or generate backgrounds for vehicle images. It supports image URL, Base64, and file upload inputs, with options for white, transparent, custom, or generative backgrounds. With an API-enabled VinAudit account and valid API key, applications can send requests and receive processed vehicle image output. It helps standardize image presentation across listings, reports, and marketing workflows.
Note: Output will also include ‘window correction,’ which will remove any objects in the background that appear through a window, such as a building, trees, other vehicles, etc.
The original vehicle image provided by the user before any background manipulation.
Optionally replaces the vehicle's license plate with a custom or blank plate for privacy or branding purposes.
Replaces the original image background with a clean white background—ideal for listings and reports.
Allows users to upload or link a custom background image to replace the original one.
Automatically generates a realistic background based on a text prompt, powered by AI.
Use the same endpoint for GET and POST requests. Use GET for simple URL requests and POST for uploads, base64 input, custom backgrounds, and other request-body options.
Parameter
key
requiredExample
YOUR_API_KEY_HERE
Description
Your VinAudit API key
Parameter
image_url
optionalExample
https://images.vinaudit.com/samples/image1.jpg
Description
Publicly accessible URL of the source image in .jpg, .png, or .webp format.
Provide one of image_url, image_base64, or image_file.
Parameter
image_base64
optionalExample
iVBORw0KGgoAAA
Description
Base64 encoded source image.
Provide one source image using image_url, image_base64, or image_file.
Parameter
image_file
optionalExample
files={'image_file': open('/path/to/image.jpg','rb')}
Description
Image file upload via multipart form.
Provide one source image using image_url, image_base64, or image_file.
Parameter
background
optionalExample
white_background
Description
Background mode: white_background, transparent_background, custom_background, or generative_background.
Parameter
background_url
optionalExample
https://images.vinaudit.com/samples/background1.jpg
Description
Public URL for a custom background image. If both background_url and background_file are sent, background_url takes priority.
Parameter
background_file
optionalExample
files={'background_file': open('/path/to/bg.jpg','rb')}
Description
Custom background file via multipart form upload. Use if not providing background_url.
Parameter
layout
optionalExample
center
Description
Output layout: center, crop, or none. Default is none. With generative_background, must be none.
Parameter
effect
optionalExample
shadow
Description
Shadow effect: shadow or none. Default is shadow. With generative_background, must be none.
Parameter
background_prompt
optionalExample
a studio image of car inside room
Description
Text prompt to guide generative_background. Ignored for other background modes.
Parameter
background_negative_prompt
optionalExample
blur, low quality
Description
Words to avoid for generative_background. Ignored for other background modes.
Parameter
plate_replacement
optionalExample
image
Description
Replace plate overlay, image to enable, none to disable. Default is none.
Parameter
plate_base64
optionalExample
iVBORw0KGgoAAA…
Description
Base64 of the replacement plate image, required if plate_replacement=image.
Parameter
output_url
Example
http://bg2.imgset.info/i2/example.jpg
Description
Direct URL of the processed vehicle image
Parameter
error
Example
blank, invalid_input, unauthorized_request, no_data, request_failed
Description
One of: invalid_input, unauthorized_request, no_data, request_failed, or (blank) if no error.
Parameter
error_description
Example
blank or request-specific message
Description
Human-readable error message providing additional context about the error. The message format and wording may vary as new error cases are introduced, and should not be relied on for programmatic handling.
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