This directory contains a number of face vectorization implementations, each exposing a unified interface so that the algorithms can be used interchangeably in the faceanalysis app and in evaluation scripts.
The algorithm container will be called like so:
docker run -v /path/to/images:/data the_algorithm_container /data/image1.jpg ... /data/imageN.jpg
Each of the paths passed as arguments to the container is a raw image file.
The container must find all the faces in the image and create a face embedding
for each of the faces. If the environment variable PREALIGNED=true
is set in
the container, the face finding step can be skipped and the container should
assume that each image contains a single cropped face.
The container is expected output the following JSON structure to stdout:
{
"faceVectors": [
[
[0, 1, 2, 3], // face vector for the first person in the first image
// ...
[4, 5, 6, 7] // face vector for the last person in the first image
],
//
// ...
//
[
[3, 2, 1, 0], // face vector for the first person in the Nth image
// ...
[7, 6, 5, 4] // face vector for the last person in the Nth image
]
]
}