File size: 1,417 Bytes
a6dd040 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 |
"""
https://github.com/google/dynibar/blob/main/ibrnet/data_loaders/llff_data_utils.py
"""
import numpy as np
import cv2
def render_stabilization_path(poses, k_size=45):
"""Rendering stablizaed camera path."""
# hwf = poses[0, :, 4:5]
num_frames = poses.shape[0]
output_poses = []
input_poses = []
for i in range(num_frames):
input_poses.append(
np.concatenate(
[poses[i, :3, 0:1], poses[i, :3, 1:2], poses[i, :3, 3:4]], axis=-1
)
)
input_poses = np.array(input_poses)
gaussian_kernel = cv2.getGaussianKernel(ksize=k_size, sigma=-1)
output_r1 = cv2.filter2D(input_poses[:, :, 0], -1, gaussian_kernel)
output_r2 = cv2.filter2D(input_poses[:, :, 1], -1, gaussian_kernel)
output_r1 = output_r1 / np.linalg.norm(output_r1, axis=-1, keepdims=True)
output_r2 = output_r2 / np.linalg.norm(output_r2, axis=-1, keepdims=True)
output_t = cv2.filter2D(input_poses[:, :, 2], -1, gaussian_kernel)
for i in range(num_frames):
output_r3 = np.cross(output_r1[i], output_r2[i])
render_pose = np.concatenate(
[
output_r1[i, :, None],
output_r2[i, :, None],
output_r3[:, None],
output_t[i, :, None],
],
axis=-1,
)
output_poses.append(render_pose[:3, :])
return output_poses
|