Face-detection based transformations
You can detect faces in your images for automatic cropping or blurring those out. Face detection is available in group photos, including photos with small faces.
How it works
detect_faces operation returns the coordinates of faces found in an
input image. The output is similar to the
operation. The output is a JSON with the additional list of
holds the coordinates of faces that were detected.
Data for each of the found faces are put into separate lists that look like this:
[x, y, x_size, y_size]json
Further, lists within
y— coordinates of the upper-left corner of an area where a face was found.
y_size— dimensions of that area.
detect_faces is not divided from a file UUID by the
Hence, it can not be piped to other operations.
Run a face-check for the following image on our CDN:
detect_faces into the image URL, separating it with
the forward slash
/ from the UUID:
Get the following
faces list in the response JSON:
"faces": [ [45, 142, 207, 207], [460, 113, 238, 238], [892, 43, 265, 265] ]json
detect_faces uses an algorithm that better detects the fronts of faces rather
than facial profiles. Also, covering important face features with
different objects leads to a decline in detection accuracy.
Technically, the operation detects faces using Haar Cascades. That approach deals with machine learning processes that rely on classifiers holding cascades of features specific to faces, eyes, etc.