Park-Developer

# 고정 길이 스택 클래스 구현하기(collections.deque 사용)

from typing import Any
from collections import deque

class Stack:
    def __init__(self,maxlen:int=256)-> None:
        '''스택 초기화'''
        self.capacity=maxlen
        self.__stk =deque([],maxlen)

Park-Developer

# 버블 정렬 알고리즘 구현하기

from typing import MutableSequence

def bubble_sort(a:MutableSequence)-> None:
    '''버블 정렬'''
    n=len(a)
    for i in range(n-1):
        for j in range(n-1,i,-1):
            if a[j-1]>a[j]:

Park-Developer

var arr = [];
for(i=1; i<11; i++){
  var keyName = "count"+i
  var count = Math.floor(Math.random()*1000);
  var obj = new Object();
  obj[keyName] = count;
  arr.push(obj);
}

arr.forEach(function(value){

Park-Developer

import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline

np.random.seed(0)
# y=4X+6을 근사, 임의의 값을 노이즈로 만듬
X=2*np.random.rand(100,1)
y=6+4*X+np.random.rand(100,1)

# X,y 데이터 세트 산점도로 시각화

Park-Developer

def decide_encoding(file_path):
    try:
        print("UTF-8")
        f = open(file_path, 'r', encoding='utf-8') #ansi
        txtdata = f.readlines()
        return (True,"utf-9")
    except:
        try:
            print("ANSI")
            f = open(file_path, 'r', encoding='ansi')  # ansi

Park-Developer

void setup() {
  // initialize digital pin 13 as an output.
  pinMode(13, OUTPUT);
  Serial.begin(9600);
}
 
// the loop function runs over and over again forever
void loop() {
  String msg = "";
  digitalWrite(13, HIGH);   // turn the LED on (HIGH is the voltage level)

Park-Developer

#include <FastLED.h>
#define LED_PIN     7
#define NUM_LEDS    20
CRGB leds[NUM_LEDS];
void setup() {
  FastLED.addLeds<WS2812, LED_PIN, GRB>(leds, NUM_LEDS);
  
}
void loop() {
  

Park-Developer

#include <stdio.h>
#include <signal.h>
#include <stdlib.h>
#include <string.h>
#include <unistd.h>

static void printSigset(sigset_t *set);
static void sigHandler(int);

int main(int argc, char **argv){

Park-Developer

import tensorflow_hub as hub
import cv2
import numpy
import tensorflow as tf
import pandas as pd

# Carregar modelos
detector = hub.load("https://tfhub.dev/tensorflow/efficientdet/lite2/detection/1")
labels = pd.read_csv('labels.csv',sep=';',index_col='ID')
labels = labels['OBJECT (2017 REL.)']

Park-Developer

import cv2

cap=cv2.VideoCapture(0) # 카메라 0번 장치 연결

width=cap.get(cv2.CAP_PROP_FRAME_WIDTH) # 프레임 폭
height=cap.get(cv2.CAP_PROP_FRAME_HEIGHT) # 프레임 높이
print("Original Size",width,height)

cap.set(cv2.CAP_PROP_FRAME_WIDTH,320)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT,240)