Ajk4

# Based on https://gist.github.com/crmccreary/1593090

import numpy as np
import math

def isclose(x, y, rtol=1.e-5, atol=1.e-8):
    return abs(x-y) <= atol + rtol * abs(y)

def euler_angles_from_rotation_matrix(R):
    yaw = 0.0

Ajk4

import numpy as np

def pointcloud_to_depth_map(pointcloud: np.ndarray, theta_res=150, phi_res=32, max_depth=50, phi_min_degrees=60,
                            phi_max_degrees=100) -> np.ndarray:
    """
        All params are set so they match default carla lidar settings
    """
    assert pointcloud.shape[1] == 3, 'Must have (N, 3) shape'
    assert len(pointcloud.shape) == 2, 'Must have (N, 3) shape'

Ajk4

from scipy import io
import numpy as np
from keras.utils import np_utils
from sklearn.model_selection import train_test_split
from PIL import Image
from sklearn.metrics import confusion_matrix
import tensorflow as tf
from threading import Thread

from keras.models import Sequential

Ajk4

export type UiAction = {
  type: 'SET_INVITE_OTHER_USERS_MODAL_OPENED',
  modalOpened: boolean
} | {
  type: 'SET_IMAGES_FILTER_QUERY',
  filterQuery: string
}

export const setInviteOtherUsersModalOpened = (modalOpened: boolean): UiAction => ({
  type: 'SET_INVITE_OTHER_USERS_MODAL_OPENED',