sergeyprokudin

import numpy as np
from sklearn.neighbors import NearestNeighbors


def chamfer_distance(x, y, metric='l2', direction='bi'):
    """Chamfer distance between two point clouds

    Parameters
    ----------
    x: numpy array [n_points_x, n_dims]

mkocabas

import numpy as np
import torch

def compute_similarity_transform(S1, S2):
    '''
    Computes a similarity transform (sR, t) that takes
    a set of 3D points S1 (3 x N) closest to a set of 3D points S2,
    where R is an 3x3 rotation matrix, t 3x1 translation, s scale.
    i.e. solves the orthogonal Procrutes problem.
    '''

engelen

/**
 * Retrieve the array key corresponding to the largest element in the array.
 *
 * @param {Array.<number>} array Input array
 * @return {number} Index of array element with largest value
 */
function argMax(array) {
  return array.map((x, i) => [x, i]).reduce((r, a) => (a[0] > r[0] ? a : r))[1];
}

kingspp

# -*- coding: utf-8 -*-
"""
| **@created on:** 11/05/17,
| **@author:** Prathyush SP,
| **@version:** v0.0.1
|
| **Description:**
| DL Module Tests
| **Sphinx Documentation Status:** Complete
|

kylehounslow

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'

j-min

from __future__ import print_function
'''
Basic Multi GPU computation example using TensorFlow library.
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''

'''
This tutorial requires your machine to have 1 GPU
"/cpu:0": The CPU of your machine.

harpone

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))
    

lexruee

sudo apt-get update
sudo apt-get install python-pip python-dev ipython

sudo apt-get install bluetooth libbluetooth-dev
sudo pip install pybluez

jensenb

import cv2
import numpy as np


def in_front_of_both_cameras(first_points, second_points, rot, trans):
    # check if the point correspondences are in front of both images
    rot_inv = rot
    for first, second in zip(first_points, second_points):
        first_z = np.dot(rot[0, :] - second[0]*rot[2, :], trans) / np.dot(rot[0, :] - second[0]*rot[2, :], second)
        first_3d_point = np.array([first[0] * first_z, second[0] * first_z, first_z])

pkuczynski

#!/bin/sh
parse_yaml() {
   local prefix=$2
   local s='[[:space:]]*' w='[a-zA-Z0-9_]*' fs=$(echo @|tr @ '\034')
   sed -ne "s|^\($s\)\($w\)$s:$s\"\(.*\)\"$s\$|\1$fs\2$fs\3|p" \
        -e "s|^\($s\)\($w\)$s:$s\(.*\)$s\$|\1$fs\2$fs\3|p"  $1 |
   awk -F$fs '{
      indent = length($1)/2;
      vname[indent] = $2;
      for (i in vname) {if (i > indent) {delete vname[i]}}