Skip to main content

Portrait Depth Estimation

Portrait Depth Estimation API

To compute your images depth estimation, our API is available at


Our API focuses on portrait depth estimation, so that any image pixel that is not part of a person will be ignored (ie, the depth estimation will be 0 for those pixels).

Result image will be a JPEG where each pixel value is the depth estimation for that pixel, the white color represents the closest pixel and the black color represents the farthest pixel.

The request must be an http POST and its body must be a multipart/form-data that has one image file:

  • image_file is the original image to process.
    • The original image should be a PNG, JPEG or WEBP file, with a maximum resolution of 25 megapixels and a max file size of 30 Mb.

In case of success:

  • the response body will contain an image containing the depth estimation of your input image.
  • response mime type will be image/jpeg.
  • the response headers will include a x-remaining-credits property to tell you how many credits you have left.

In case of an error:

  • the response mime-type is application/json, the error type is indicated by the response status code and details are in the json body, ie
{ "error": "No api key provided" }


Requests are authenticated with an API key. If you do not have one, you can get one here.

If your key has leaked, you can revoke it and request a new one in your account page.


1 successful depth estimation API call = 1 credit.

Once logged in, you can claim 100 free Clipdrop APIs credits that you can use for development and debugging purposes. Once the 100 images have been consumed, further calls will be rejected.

If you need more credits, you can purchase more credits via the following link.

Quota / Rate limiting

By default, each API key has a limit of 60 requests per minute for the depth estimation API. Please let us know if you'd like higher values.


curl -X POST \
-H 'x-api-key: YOUR_API_KEY' \
-F image_file=@portrait.jpg \
-o result.jpg


The result image, e.g. 
Example result of an upscaled image

Examples of input and outputs


Example of an input image for depth estimation


Example of a depth estimation map


Any question ? Contact us at or join the Slack community.