nicetoolbox.detectors.method_detectors.mmpose.mmpose_framework_3d

MMPose 3D frameworks and specific algorithm definitions.

Classes

MMPose3D	MMPose3D handles native 3D pose lifters (e.g.
MotionBERT	Handler for MotionBERT models trained on Human3.6M (17 Keypoints).

class nicetoolbox.detectors.method_detectors.mmpose.mmpose_framework_3d.MMPose3D(io: SequenceIO, data: SequenceData, sequence_context: SequenceRuntimeConfig, algorithm_instance: str)

MMPose3D handles native 3D pose lifters (e.g. MotionBERT). Post-inference applies optional temporal filtering and confidence masking on stored 2D/3D arrays; 3D stays in the lifter’s root-relative frame (no PnP or camera alignment).

Initialize base method detector with references.

post_inference()

Post-inference processing for 3D pose estimation.

class nicetoolbox.detectors.method_detectors.mmpose.mmpose_framework_3d.MotionBERT(io: SequenceIO, data: SequenceData, sequence_context: SequenceRuntimeConfig, algorithm_instance: str)

Handler for MotionBERT models trained on Human3.6M (17 Keypoints).

Initialize base method detector with references.

compute_viz_folder(_visualize: bool) → str | None

Return None so base __init__ does not mkdir the visualization folder.

The subprocess creates the per-camera frame folders itself; the main process assembles the mp4s in visualization() after inference.

get_per_component_keypoint_mapping(keypoints_indices)

This method extracts the keypoint indices and descriptions for each pose estimation component.

It has to be implemented by the derived classes associated to the available pose estimation algorithms. (See HRNetw48 and Vitpose classes below)

Available algorithms are: hrnetw48, vitpose

Parameters:

keypoints_indices (_type_) – _description_

visualization(_)

Generates a visualization video for each camera from the processed image frames.

This method takes the processed image frames for each camera and compiles them into a video file. It uses the frames_to_video() function from utils.video.py. The success of the video creation is tracked, and the method logs the outcome of the visualization process for each camera. :param data: An instance of a class that stores all data related

information, including the frame rate (fps) for the video and the starting frame number (video_start).

Note

• The method assumes that the processed image frames are named in a

specific format (%09d.jpg), where each frame’s name is a zero-padded five-digit number representing its sequence in the video.