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# ----------------------------------------------------------------------------
# - Open3D: www.open3d.org -
# ----------------------------------------------------------------------------
# Copyright (c) 2018-2024 www.open3d.org
# SPDX-License-Identifier: MIT
# ----------------------------------------------------------------------------
import open3d as o3d
import numpy as np
import re
import os
def load_fountain_dataset():
rgbd_images = []
fountain_rgbd_dataset = o3d.data.SampleFountainRGBDImages()
for i in range(len(fountain_rgbd_dataset.depth_paths)):
depth = o3d.io.read_image(fountain_rgbd_dataset.depth_paths[i])
color = o3d.io.read_image(fountain_rgbd_dataset.color_paths[i])
rgbd_image = o3d.geometry.RGBDImage.create_from_color_and_depth(
color, depth, convert_rgb_to_intensity=False)
rgbd_images.append(rgbd_image)
camera_trajectory = o3d.io.read_pinhole_camera_trajectory(
fountain_rgbd_dataset.keyframe_poses_log_path)
mesh = o3d.io.read_triangle_mesh(fountain_rgbd_dataset.reconstruction_path)
return mesh, rgbd_images, camera_trajectory
def test_color_map():
"""
Hard-coded values are from the 0.12 release. We expect the values to match
exactly when OMP_NUM_THREADS=1. If more threads are used, there could be
some small numerical differences.
"""
o3d.utility.set_verbosity_level(o3d.utility.VerbosityLevel.Debug)
# Load dataset
mesh, rgbd_images, camera_trajectory = load_fountain_dataset()
# Computes averaged color without optimization, for debugging
mesh, camera_trajectory = o3d.pipelines.color_map.run_rigid_optimizer(
mesh, rgbd_images, camera_trajectory,
o3d.pipelines.color_map.RigidOptimizerOption(maximum_iteration=0))
vertex_mean = np.mean(np.asarray(mesh.vertex_colors), axis=0)
extrinsic_mean = np.array(
[c.extrinsic for c in camera_trajectory.parameters]).mean(axis=0)
np.testing.assert_allclose(vertex_mean,
np.array([0.40322907, 0.37276872, 0.54375919]),
rtol=1e-5)
np.testing.assert_allclose(
extrinsic_mean,
np.array([[0.77003829, -0.10813595, 0.06467495, -0.56212008],
[0.19100387, 0.86225833, -0.14664845, -0.81434887],
[-0.05557141, 0.16504166, 0.82036438, 0.27867426],
[0., 0., 0., 1.]]),
rtol=1e-5)
# Rigid Optimization
mesh, camera_trajectory = o3d.pipelines.color_map.run_rigid_optimizer(
mesh, rgbd_images, camera_trajectory,
o3d.pipelines.color_map.RigidOptimizerOption(maximum_iteration=10))
vertex_mean = np.mean(np.asarray(mesh.vertex_colors), axis=0)
extrinsic_mean = np.array(
[c.extrinsic for c in camera_trajectory.parameters]).mean(axis=0)
np.testing.assert_allclose(vertex_mean,
np.array([0.40294861, 0.37250299, 0.54338467]),
rtol=1e-5)
np.testing.assert_allclose(
extrinsic_mean,
np.array([[0.7699379, -0.10768808, 0.06543989, -0.56320637],
[0.19119488, 0.8619734, -0.14717332, -0.8137762],
[-0.05608781, 0.16546427, 0.81995183, 0.27725451],
[0., 0., 0., 1.]]),
rtol=1e-5)
# Non-rigid Optimization
mesh, camera_trajectory = o3d.pipelines.color_map.run_non_rigid_optimizer(
mesh, rgbd_images, camera_trajectory,
o3d.pipelines.color_map.NonRigidOptimizerOption(maximum_iteration=10))
vertex_mean = np.mean(np.asarray(mesh.vertex_colors), axis=0)
extrinsic_mean = np.array(
[c.extrinsic for c in camera_trajectory.parameters]).mean(axis=0)
np.testing.assert_allclose(vertex_mean,
np.array([0.4028204, 0.37237733, 0.54322786]),
rtol=1e-5)
np.testing.assert_allclose(
extrinsic_mean,
np.array([[0.76967962, -0.10824218, 0.0674025, -0.56381652],
[0.19129921, 0.86245618, -0.14634957, -0.81500831],
[-0.05765316, 0.16483281, 0.82054672, 0.27526268],
[0., 0., 0., 1.]]),
rtol=1e-5)
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