Returns True if this track is confirmed.

Get a logger with a custom format.

Returns True if this track is tentative (unconfirmed).

Compute pair-wise squared l2 distances between points in `a` and `b`.

3x3 convolution with padding

:param R (*, 3, 3) :param t (*, 3) return (*, 4, 4)

This function computes the perspective projection of a set of points Input: points (bs, N, 3): 3D points rotation (bs, 3, 3):

Convert 6D rotation representation to 3x3 rotation matrix. Based on Zhou et al., "On the Continuity of Rotation Representations in Neural Networks

Download the file specified by the URL to the cache_dir and return the path to the cached file. If the argument is not a URL, simply return it as

Download a file from Google Drive if it doesn't exist yet. :param url: the URL of the file to download :param path: the path to save t

For this mesh, pre-computes the UV coordinates for F x T x T points. Returns F x T x T x 2

Compute distance between features and targets. Parameters ---------- features : ndarray An NxM matrix of N featur

Download url and write it to dst_file_path. Credit: https://stackoverflow.com/questions/2028517/python-urllib2-progress-hook

Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks). This is the same as the DropConnect impl I created for Ef

Compute pair-wise squared l2 distances between points in `track_pose` and `detect_pose`.

Returns True if this track is dead and should be deleted.

Main function for running the PHALP tracker.

Main function for running the PHALP tracker.

Mark this track as missed (no association at the current time step).

Converts obj uv_map to NMR uv_map (F x T x T x 2), where tex_size (T) is the sample rate on each face.

Update the distance metric with new data. Parameters ---------- features : ndarray An NxM matrix of N features of

:param d_model: dimension of the model :param length: length of positions :return: length*d_model position matrix

encoder takes keys : pose_shape (bs, self.cfg.frame_length, 229) has_detection (bs, self.cfg.frame_length, 1)

Constructs a ResNet-50 model. Args: pretrained (bool): If True, returns a model pre-trained on ImageNet