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AILabTools API - Remove Objects Advanced - API

Request

  • URL: https://www.ailabapi.com/api/image/editing/remove-objects-advanced
  • Method: POST
  • Content-Type: multipart/form-data

Image requirements

  • Image format: JPEG JPG PNG
  • Image size: No more than 5 MB.
  • Image resolution: Larger than 64x64px, smaller than 4096x4096px.

Mask image requirements:

  1. Single-channel grayscale image (0-255).
  2. Three-channel image, with equal RGB values.
  3. RGBA four-channel image, with equal RGB values and the A channel all set to 255.
  4. File format: 8-bit PNG encoding, do not embed "ICC Profile".

Headers

FieldRequiredTypeDescription
ailabapi-api-keyYESstringApplication API KEY. Get API KEY

Body

FieldRequiredTypeScopeDefaultDescription
imageYESfileOriginal image.
maskYESfileMask image.
stepsNOinteger[1, +]30Sampling steps determine the level of detail in the generated image. A higher value may result in better quality, but it will significantly increase the processing time.
strengthNOfloat[0.1, 1.0]0.8The smaller the value, the closer it is to the original image.
scaleNOfloat[1, 20]7The degree to which the text description influences the output.
seedNOinteger[-1, +]0Random seed, used as the basis for determining the initial state of the diffusion process. It must be a non-negative number (-1 represents a random seed). If the random seed is the same positive integer and all other parameters are identical, the generated image will most likely be consistent.

Response

Response Field Handling Flow
  1. Handle Public Response Fields

    Parse and validate the Public Response Fields, checking the status code or response message to ensure the request is successful and error-free.

  2. Handle Business Response Fields

    If the Public Response Fields are valid and error-free, proceed with processing the business logic in the Business Response Fields.

Public Response Fields

Viewing Public Response Fields and Error Codes

Business Response Fields

FieldTypeDescription
dataobjectThe content of the result data returned.
+binary_data_base64array of stringOutput the processed image as a Base64 array (single image).

Response Example

{
"request_id": "",
"log_id": "",
"error_code": 0,
"error_msg": "",
"error_detail": {
"status_code": 200,
"code": "",
"code_message": "",
"message": ""
},
"data": {
"binary_data_base64": []
}
}

Sample Code