Modify camera intrinsics to follow a different convention. Coordinates of the center of the top-left pixels are by default: - (0.5, 0.5)

Compute RMSE of ATE Args: gt: ground-truth poses pred: predicted poses

return PixelwiseTaskWithDPT for given net params

Given an image and its intrinsics, we want to replicate a rectangular crop with an homography, so that the principal point of the n

Return Euler angles from rotation matrix for specified axis sequence. axes : One of 24 axis sequences as string or encoded tuple Note that m

Return homogeneous rotation matrix from Euler angles and axis sequence. ai, aj, ak : Euler's roll, pitch and yaw angles axes : One of 24 axis

returns 3 values: 1 - reciprocal_in_P2: a boolean array of size P2.shape[0], a "True" value indicates a match 2 - nn2_in_P1: a int array

First order approximation of a rotation: I + skew(rotvec) cfo, 2015/08/13

Calculate nearest point to all focal axes in poses.

Generate random crops of size=resolution, for an input image upscaled to (imsize + randint(0 , aug_crop))

extract 3D_model (glb file) from a reconstructed scene

extract 3D_model (glb file) from a reconstructed scene

maximize trace(Rz(theta) * C)

X right, Y up, Z backward to the observer. :param H, W: :param fx, fy: :param W2C: (4, 4) matrix :param frustum_length:

X right, Y up, Z backward to the observer. :param H, W: :param fx, fy: :param W2C: (4, 4) matrix :param frustum_length:

Convert images in a folder to a video. Args: - image_folder (str): The path to the folder containing the images. - output_video_path

Construct inner and outer measures on (t1, y1) for t0.

Insert extra poses at the start and end of the path.

Compute the cumulative sum of w, assuming all weight vectors sum to 1. The output's size on the last dimension is one greater than that of the inpu

Runs multidimensional B-spline interpolation on the input points.

Invert the CDF defined by (t, w) at the points specified by u in [0, 1).

Invert the CDF defined by (t, w) at the points specified by u in [0, 1).

Loads, normalizes, inverts, and scales confidence values to obtain learning rate modifiers. Args: confidence_path (str): Path to