スクレイピング

import requests
from bs4 import BeautifulSoup

from urllib.parse import urljoin

url = "https://web.pref.hyogo.lg.jp/index.html"

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; WOW64; Trident/7.0; rv:11.0) like Gecko"
}

r = requests.get(url, headers=headers)
r.raise_for_status()

soup = BeautifulSoup(r.content, "html.parser")

tag = soup.select_one("div#tmp_contents > p > img")

link = urljoin(url, tag.get("src"))

r = requests.get(link, headers=headers)
r.raise_for_status()

with open("alert.png", mode="wb") as fw:
    fw.write(r.content)

OCR

tesseract-ocrをインストール

!add-apt-repository ppa:alex-p/tesseract-ocr -y
!apt update
!apt install tesseract-ocr
!apt install libtesseract-dev
!tesseract -v

!apt install tesseract-ocr-jpn  tesseract-ocr-jpn-vert
!apt install tesseract-ocr-script-jpan tesseract-ocr-script-jpan-vert
!tesseract --list-langs
!pip install pytesseract

画像から文字を抽出

import pytesseract

import cv2
import numpy as np

from google.colab.patches import cv2_imshow

# 縁に黒いのが残っているので少し切り抜き
img_bgr = cv2.imread("alert.png")[10:-10, 10:-10]

# グレースケール
img_gray = cv2.cvtColor(img_bgr, cv2.COLOR_BGR2GRAY)

# 色確認
img_bgr[10, 10]

# 画像を確認
cv2_imshow(img_gray)

# 色カウント
black = np.sum(img_gray < 151)
white = np.sum(img_gray > 150)

# 白と黒どちらが多いか確認して黒が多い場合は反転
if white < black:
    ret, thresh = cv2.threshold(img_gray, 150, 255, cv2.THRESH_BINARY_INV)

else:
    ret, thresh = cv2.threshold(img_gray, 150, 255, cv2.THRESH_BINARY)

# 画像を確認
cv2_imshow(thresh)

txt = pytesseract.image_to_string(thresh, lang="jpn", config="--psm 6").strip()

txt