unot

情報処理研修

発表者：細木、宇埜

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目次

• 情報処理基礎
• 画像処理

unot

#!/bin/bash
# calculate mean values of Lab
# $ cat file1
# L1_1 a1_1 b1_1
# L1_2 a1_2 b1_2
# $ cat file2
# L2_1 a2_1 b2_1
# L2_2 a2_2 b2_2
# $ cat file3
# L3_1 a3_1 b3_1

unot

// Use Gists to store code you would like to remember later on
console.log(window); // log the "window" object to the console

unot

# -*- coding:utf-8 -*-

import numpy
from scipy import stats

n = 200
#正規分布にあてはまる乱数を生成
score_x = numpy.random.normal(171.77, 5.54, n)
score_y = numpy.random.normal(62.49, 7.89, n)

unot

from matplotlib import pyplot as plt
import numpy as np
import cv2
import sys


def printing(position):
    #print(position)
    return

unot

using System;
using System.Windows.Forms;

namespace StringToHexConverter
{
    public partial class Form1 : Form
    {
        public Form1()
        {
            InitializeComponent();