打开网址，F12。发现网页直接跳转了~

那么，就新建一个标签页，先F12，设置，禁用JS

再次粘贴网址，跳转。对比一下网页的文字和html源代码中的文字。

 

下一步确认一下文字动态还是静态

按照上面的方法，再次新建一个标签页，重新打开网址，发现是两次源代码的文字是不一样的。确认是动态加载！

 

并且字体为base64编码，提取出来，保存为TTF文件！

这里推荐一个查字体的网站：https://www.bejson.com/ui/font/

打开网站后，上传字体文件。

 

分析到这里，大致的思路已经出来了~

读取网页源代码->提取base64编码的字体文件->取出来字体文件中的字符图片以及真实的Unicode字符->识别图片中的文字->按照规则进行文章的文字替换

 

取出来字体文件中的字符图片以及真实的Unicode字符

 

现在的目的达到了，接下来就是识别这个字符的字，然后把文章的"要"替换为"发"

现在软件可以通过uni8981查询到这个字是"要"，但是软件是不知道这个字代表的是"发"

所以，我的思路就是使用图像识别

 

import base64
import re
 
import bs4
import easyocr
import requests
from fontTools.ttLib import TTFont
from PIL import Image, ImageDraw, ImageFont
import os
 
 
def ocr(folder_dir: str) -> dict:
    reader = easyocr.Reader(['ch_sim'], gpu=False)
    key_words = {}
    directory = folder_dir
    dir_list = os.listdir(directory)
    for file_name in dir_list:
        full_path = os.path.join(directory, file_name)
        # print(full_path)
        error_key_word = f'\\{file_name}'.encode('utf-8').decode('unicode_escape').replace('.png', '')
        try:
            success_key_word = reader.readtext(full_path, detail=False)[0]
        except IndexError:
            success_key_word = '一'
        key_words.update({error_key_word: success_key_word})
    return key_words
 
 
def get_html():
    url = "https://www.zhihu.com/market/paid_column/1730607810226688000/section/1730181148968325120"
 
    payload = {}
    headers = {
        'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
        'accept-language': 'zh-CN,zh-TW;q=0.9,zh;q=0.8',
        'cache-control': 'no-cache',
        'pragma': 'no-cache',
        'sec-ch-ua': '"Google Chrome";v="123", "Not:A-Brand";v="8", "Chromium";v="123"',
        'sec-ch-ua-mobile': '?0',
        'sec-ch-ua-platform': '"Windows"',
        'sec-fetch-dest': 'document',
        'sec-fetch-mode': 'navigate',
        'sec-fetch-site': 'none',
        'sec-fetch-user': '?1',
        'upgrade-insecure-requests': '1',
        'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/123.0.0.0 Safari/537.36'
    }
 
    response = requests.request("GET", url, headers=headers, data=payload)
 
    return response.text
 
 
def html_analyze(html_body: str):
    html_obj = bs4.BeautifulSoup(html_body, features="html.parser")
    return '\n'.join([item.get_text() for item in html_obj.findAll('p')])
 
 
def clear_directory(path):
    for filename in os.listdir(path):
        filepath = os.path.join(path, filename)
        try:
            if os.path.isfile(filepath):
                os.remove(filepath)
        except Exception as e:
            print(f"Error deleting {filepath}: {e}")
 
 
def export_glyph_images(ttf_file_path, output_folder, image_size=(200, 200), font_size=200):
    if not os.path.exists(output_folder):
        os.makedirs(output_folder)
 
    font = TTFont(ttf_file_path)
    cmap = font.getBestCmap()
    pil_font = ImageFont.truetype(ttf_file_path, font_size)
 
    for unicode_char, glyph_name in cmap.items():
        char = chr(unicode_char)
        img = Image.new("RGBA", image_size, color="white")
        draw = ImageDraw.Draw(img)
 
        # 绘制字符
        draw.text((0, 0), char, font=pil_font, fill="black", font_size=24, align="center")
        # 保存图片
        unicode_hex_str = f'u{unicode_char:04X}' + ".png"
        print(unicode_hex_str)
        image_file_path = os.path.join(output_folder, unicode_hex_str)
        img.save(image_file_path)
 
    font.close()
 
 
if __name__ == '__main__':
    # 字体缓存地址
    output_folder = r"xxxxxxx"
 
    clear_directory(output_folder)
    html_body = get_html()
    font_face_regex = re.findall(r'@font-face\s*{([^}]*)}', html_body)
    base64_string = re.findall('base64,(.*?)\);', font_face_regex[3])[0]
    binary_data = base64.b64decode(base64_string)
    with open('zhihu.ttf', 'wb') as f:
        f.write(bytes(binary_data))
    # 指定TTF文件的路径
    ttf_file_path = "zhihu.ttf"
    # 调用函数导出字形图片
    export_glyph_images(ttf_file_path, output_folder)
 
    keywords = ocr(output_folder)
    content = [item for item in html_analyze(html_body)]
 
    filter_list = []
    for error_key, success_key in keywords.items():
        for index in range(len(content)):
            if content[index] == error_key and index not in filter_list:
                content[index] = success_key
                filter_list.append(index)
 
    with open('知乎盐选.txt', 'w', encoding='utf-8') as f:
        f.write(''.join(content))

文章来源：https://www.52pojie.cn/thread-1911970-1-1.html