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# Copyright 2024 ByteDance and/or its affiliates.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import numpy as np
from scipy.spatial.transform import Rotation
def angle_3p(a, b, c):
"""
Calculate the angle between three points in a 2D space.
Args:
a (list or array-like): The coordinates of the first point.
b (list or array-like): The coordinates of the second point.
c (list or array-like): The coordinates of the third point.
Returns:
float: The angle in degrees (0, 180) between the vectors
from point a to point b and point b to point c.
"""
a = np.array(a)
b = np.array(b)
c = np.array(c)
ab = b - a
bc = c - b
dot_product = np.dot(ab, bc)
norm_ab = np.linalg.norm(ab)
norm_bc = np.linalg.norm(bc)
cos_theta = np.clip(dot_product / (norm_ab * norm_bc + 1e-4), -1, 1)
theta_radians = np.arccos(cos_theta)
theta_degrees = np.degrees(theta_radians)
return theta_degrees
def random_transform(
points, max_translation=1.0, apply_augmentation=False, centralize=True
) -> np.ndarray:
"""
Randomly transform a set of 3D points.
Args:
points (numpy.ndarray): The points to be transformed, shape=(N, 3)
max_translation (float): The maximum translation value. Default is 1.0.
apply_augmentation (bool): Whether to apply random rotation/translation on ref_pos
Returns:
numpy.ndarray: The transformed points.
"""
if centralize:
points = points - points.mean(axis=0)
if not apply_augmentation:
return points
translation = np.random.uniform(-max_translation, max_translation, size=3)
R = Rotation.random().as_matrix()
transformed_points = np.dot(points + translation, R.T)
return transformed_points
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