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import cv2 
# variables 
# distance from camera to object(face) measured
Known_distance = 30 #centimeter
# width of face in the real world or Object Plane
Known_width =14.3 
# Colors
GREEN = (0,255,0)
RED = (0,0,255)
WHITE = (255,255,255)

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import logging
import os, sys
import abc
import gym
import numpy as np
import json
from os import listdir
from os.path import isfile, join

gym.scoreboard.api_key = "sk_hJMbMlYzSpSsucakOMOULg"

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#!/bin/bash

# stop on error
set -e

############################################

# Dependencies

sudo apt-get install build-essential checkinstall

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import org.apache.spark.sql.Column

/**
  * Optimized Median calculation for a distributed dataframe built on three findings :
  * 1. Real world datasets are made from low cardinality domains 
  * 2. Median calculation requires sort which is O(N * log N), it implies that computation time increase by a factor significantly greater than 2 for a list twice as long.
  * 3. Hive UDF support only primitive data types hence in the algo the datastructure transferred to a single node is a Seq[String] instead of Seq[Struct{}]
  **/
def insertMedianOnKey(inputDF: DataFrame,
                      key: Seq[Column],

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Direct links to free Springer books (pdf versions)

Graduate texts in mathematics

duplicates = multiple editions

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

A Classical Introduction to Modern Number Theory, Kenneth Ireland Michael Rosen

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###Python###

# Byte-compiled / optimized / DLL files
__pycache__/
*.py[cod]

# C extensions
*.so

# Distribution / packaging