<script src="./js/example.js" type="module"></script>

import { ref, createApp } from 'https://unpkg.com/vue@3/dist/vue.esm-browser.js';

import { createApp } from "vue";//ビルドしてもLaravel側で動かない
import { createApp } from "vue/dist/vue.esm-bundler.js";//こうするとビルドすると動く。
//ブレイド側の呼び出しは@vite('ビルドしたファイル名')
//ビルドするファイルの設定はルートディレクトリにあるvite.config.jsを変更すると良い。

Color of the text (iOS), or background color of the button (Android).

import React, { useState } from "react";
import { StyleSheet, Text, TouchableOpacity, View } from "react-native";

const App = () => {
  const [count, setCount] = useState(0);
  const onPress = () => setCount(prevCount => prevCount + 1);

  return (
    <View style={styles.container}>
      <View style={styles.countContainer}>
        <Text>Count: {count}</Text>
      </View>
      <TouchableOpacity
        style={styles.button}
        onPress={onPress}
      >
        <Text>Press Here</Text>
      </TouchableOpacity>
    </View>
  );
};

const styles = StyleSheet.create({
  container: {
    flex: 1,
    justifyContent: "center",
    paddingHorizontal: 10
  },
  button: {
    alignItems: "center",
    backgroundColor: "#DDDDDD",
    padding: 10
  },
  countContainer: {
    alignItems: "center",
    padding: 10
  }
});

export default App;

import cv2
import dlib
detector = dlib.simple_object_detector("yosakoi.svm")
image = cv2.imread("yosakoi.jpg.webp")
naruko =detector(image)
for f in naruko:
        print("left, top, Right, bottom : ", f.left(), f.top(), f.right(), f.bottom())
        cv2.rectangle(image, (f.left(), f.top()), (f.right(), f.bottom()), (255,0,0), 2)
print("{} naruko".format(len(naruko)))
photo = dlib.image_window()
photo.set_image(image)
photo.add_overlay(naruko)
cv2.imwrite("yosakoi-naruko.jpg.webp",image)

import requests
from bs4 import BeautifulSoup
r = requests.get("https://news.yahoo.co.jp/")
soup = BeautifulSoup(r.content, "html.parser")
#ニュース一覧のテキストのみ抽出
f = open("link.csv",mode = "a")
for t,a in zip(soup.find_all("div", "newsFeed_item_title"),soup.find_all("a", "newsFeed_item_link")):
    f.write(t.text + "," + a.get('href') + "\n")
f.close()

#!/usr/local/bin/python3
# coding:utf-8
import os
import sys
import MeCab
import gensim
import markovify
import unicodedata
model = gensim.models.KeyedVectors.load_word2vec_format('/var/www/html/model.vec', binary=False)
f = open('merosu.txt')
tagger = MeCab.Tagger("-Owakati")
tagger.parse('')
text0 = tagger.parse(f.read())
text1 = text0
text0 = text0.replace('\n','')
text0 = text0.replace('\r','')
text1x = text0.split(" ")
text2 = []
try:
    for item in text1x:
        if item.strip():
            results  = model.most_similar(positive=[item],topn=2)
            #"print(results)
            for val1 in results:
                text2.append(val1[0] + "\n")
#
    # print (text1)
    # print (" ".join(text2))
    model_a = markovify.Text(text1 + "\n")
    print(str(model_a.make_sentence()).replace(' ',''))
    model_b = markovify.Text(" ".join(text2))
    print(str(model_b.make_sentence()).replace(' ',''))
    model_combo = markovify.combine([model_a, model_b], [1, 1])
    print(str(model_combo.make_sentence()).replace(' ',''))
except Exception as e:
    print("動作エラー", e.args)
    pass