Get track id for each person instance on the current frame. Args: results (list[dict]): The bbox & pose results of the current frame

Visualize the detection results on the image. Args: model (nn.Module): The loaded detector. img (str | np.ndarray): Image filenam

Get pose estimation results of the message. Args: tag (str, optional): If given, only the results with the tag wi

Initialize the weights in backbone. Args: pretrained (str, optional): Path to pre-trained weights. Defaults to No

Load checkpoint from a file or URI. Args: model (Module): Module to load checkpoint. filename (str): Accept local filepath, URL,

Keypoint evaluation. Report mean per joint position error (MPJPE) and mean per joint position error after rigid alignment (MPJPE-PA)

Initialize model weights.

Save parameters every eval_epoch

Create a superset of inputs needed to run backbone. Args: input_shape (tuple): input batch dimensions. Default: (1, 3, 64, 64

Build posenet.

Evaluate coco keypoint results. The pose prediction results will be saved in ``${res_folder}/result_keypoints.json``. Note:

Calls either forward_train or forward_test depending on whether return_loss=True. Note this setting will change the expected inputs. W

Calls either forward_train or forward_test depending on whether return_loss=True. Note this setting will change the expected inputs. W

Calculate the pose accuracy of PCK for each individual keypoint and the averaged accuracy across all keypoints for coordinates. Note:

Performs Linear Blend Skinning with the given shape and pose parameters Parameters ---------- betas : torch.tensor BxNB The tenso

Performs Linear Blend Skinning with the given shape and pose parameters Parameters ---------- betas : torch.tensor BxNB

Load an image file, from disk or url. Args: filename (str): file name on the disk or url link. readFlag (int): readFlag for imdec

SMPL model constructor Parameters ---------- model_path: str The path to the folder or to the file where the mode

SMPL model constructor Parameters ---------- model_path: str The path to the folder or to the fi

Create a superset of inputs needed to run test or train batches. Args: input_shape (tuple): input batch dimensions nu

Recursively convert Tensor in inputs from src_type to dst_type. Args: inputs: Inputs that to be casted. src_type (torch.dtype): S

Evaluate PCKh for MPII dataset. Adapted from https://github.com/leoxiaobin/deep-high-resolution-net.pytorch Copyright (c) Microsoft, u

Use `get_logger` method in mmcv to get the root logger. The logger will be initialized if it has not been initialized. By default a StreamHan

Greedily select boxes with high confidence and overlap <= thr. Args: dets: [[x1, y1, x2, y2, score]]. thr: Retain overlap < thr.

Convert the model into training mode.

Visualize the pose tracking results on the image. Args: model (nn.Module): The loaded detector. img (str | np.ndarray): Image fil

Transform x to the integral multiple of the base.

Flip the flipped heatmaps back to the original form. Note: - batch_size: N - num_keypoints: K - heatmap height: H

Calculate accuracy for hand type. Args: output (list[Tensor]): a list of outputs from multiple heads. target (list[Te

transform_mat_neutral_pose is function to warp pre-defined posed to zero-pose

Draw bboxes with labels (optional) on an image. This is a wrapper of mmcv.imshow_bboxes. Args: img (str or ndarray): The image to be

Draw keypoints and links on an image. Args: img (str or Tensor): The image to draw poses on. If an image array is giv

Inference 3D pose from 2D pose sequences using a pose lifter model. Args: model (nn.Module): The loaded pose lifter model pose_re

Check if is one of the norms.

Convert rotations given as rotation matrices to axis/angle. Args: matrix: Rotation matrices as tensor of shape (..., 3, 3). Ret

Scatter function. Args: inputs (Tensor): Input Tensor. kwargs (dict): Args for ``mmcv.parallel.scatte