The Pose Estimation service takes an image of a human and assigns 18 key points to features in that image which correspond to specific body parts, and which allow one to determine how these parts are positioned. Pose Estimation has many use cases, including activity recognition and augmented reality. Currently, Pose Estimation can only be run using the OpenVINO engine with a Myriad accelerator.
pose_estimator = edgeiq.PoseEstimation("alwaysai/human-pose")
Next, call the object’s
function to initialize the inference engine and accelerator.
Unless directly specified, the accelerator chosen will be the default for the
Engine. Now the pose estimator is ready.
results object is of type
HumanPoseResult and contains an
array of the key points indicating body parts, where the order of the parts in the array
is as follows: