macrat

import math

import cv2
import numpy


count = 0
for i in range(12):
    print('makeing {0}.mp4 background image'.format(i+1))
    video = cv2.VideoCapture('src/{0}.mp4'.format(i+1))

macrat

import chainer
import numpy
import sklearn.base


class CNNFinder(chainer.FunctionSet):
    def __init__(self):
        super().__init__(conv1=chainer.functions.Convolution2D(1, 10, 4),
                         conv2=chainer.functions.Convolution2D(10, 20, 4),
                         conv3=chainer.functions.Convolution2D(20, 40, 4),

macrat

import math

import cv2
import numpy


MOVIE_NUM = 12


count = 0

macrat

class Tea:
    def __init__(self, n):
        self.n = n

    def __add__(self, v):
        print('add of {}'.format(self.n))

    def __radd__(self, v):
        print('radd of {}'.format(self.n))

macrat

#!/bin/bash

if [ $# -eq 1 ]; then
  channel=$1
else
  echo "usage : $0 channel_name"
  echo "         channel_name list"
  echo "           TBS Radio: TBS"
  echo "           Nippon Cultural Broadcasting: QRR"
  echo "           Nippon Broadcasting: LFR"

macrat

i = 10

while --i >= 0:
    print(i)

macrat

target = input().split(' ')[0]
coins = {*range(10)} - {*map(int, input().split(' '))}

result = ''
for c in target:
    try:
        result += str(min(x for x in coins if int(c) <= x))
    except ValueError:
        for i in range(-1, -len(result), -1):
            try:

macrat

import ast
import sys


if len(sys.argv) != 2:
    print('usage: python {} [FILE.py]'.format(sys.argv[0]))
    sys.exit(1)

with open(sys.argv[1]) as f:
    a = ast.parse(f.read(), f.name)

macrat

defmodule Main do
	def inc x do
		x + 1
	end

	def dec x do
		x - 1
	end

	defp minus(x, y) when x < 0 do

macrat

import enum
import functools
import sys


class Align(enum.Enum):
	left = lambda w, c, x: str(x) + c*(w-len(str(x)))
	right = lambda w, c, x: c*(w-len(str(x))) + str(x)

	@classmethod