网页爬虫抓取百度图片(知乎话题『美女』下所有问题中回答所出现的图片)
优采云 发布时间: 2021-11-16 07:05网页爬虫抓取百度图片(知乎话题『美女』下所有问题中回答所出现的图片)
＃更新
声明：所有与性别、人脸颜值评分等直接或间接、明示或暗示相关的文字、图片及相关外部链接均由相关人脸检测界面给出。没有任何客观性，仅供参考。
1 数据来源
知乎“美女”主题下所有问题的答案中出现的图片
2 履带
Python 3，并使用第三方库Requests、lxml、AipFace，共100+行代码
3 必要的环境
Mac / Linux / Windows（Linux没测试过，理论上可以。Windows之前反应过异常，但检查后是Windows限制了本地文件名中的字符，使用了常规过滤），无需登录知乎（即无需提供知乎账号密码），人脸检测服务需要百度云账号（即百度云盘/贴吧账号）
4 人脸检测库
百度云AI开放平台提供的AipFace是一个可以进行人脸检测的Python SDK。可以直接通过HTTP访问，免费使用
5 测试过滤条件
6 实现逻辑
7 抓取结果
直接存放在文件夹中（angelababy实力出国）。另外，目前拍摄的照片中，除了baby，88分是最高分。我个人不同意排名，我的妻子不是最高分。
8码
8. 1 直接使用百度云Python-SDK-去掉代码
8. 2 不使用SDK，直接构造HTTP请求版本。直接使用这个版本的好处是不依赖于SDK的版本（百度云现在有两个版本的接口-V2和V3。现阶段百度云同时支持这两个接口，所以直接用SDK没问题。以后百度不支持V2就得升级SDK或者用这个直接构造HTTP版本）
#coding: utf-8
import time
import os
import re
import requests
from lxml import etree
from aip import AipFace
#百度云 人脸检测 申请信息
#唯一必须填的信息就这三行
APP_ID = "xxxxxxxx"
API_KEY = "xxxxxxxxxxxxxxxxxxxxxxxx"
SECRET_KEY = "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx"
# 文件存放目录名，相对于当前目录
DIR = "image"
# 过滤颜值阈值，存储空间大的请随意
BEAUTY_THRESHOLD = 45
#浏览器中打开知乎，在开发者工具复制一个，无需登录
#如何替换该值下文有讲述
AUTHORIZATION = "oauth c3cef7c66a1843f8b3a9e6a1e3160e20"
#以下皆无需改动
#每次请求知乎的讨论列表长度，不建议设定太长，注意节操
LIMIT = 5
#这是话题『美女』的 ID，其是『颜值』（20013528）的父话题
SOURCE = "19552207"
#爬虫假装下正常浏览器请求
USER_AGENT = "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/534.55.3 (KHTML, like Gecko) Version/5.1.5 Safari/534.55.3"
#爬虫假装下正常浏览器请求
REFERER = "https://www.zhihu.com/topic/%s/newest" % SOURCE
#某话题下讨论列表请求 url
BASE_URL = "https://www.zhihu.com/api/v4/topics/%s/feeds/timeline_activity"
#初始请求 url 附带的请求参数
URL_QUERY = "?include=data%5B%3F%28target.type%3Dtopic_sticky_module%29%5D.target.data%5B%3F%28target.type%3Danswer%29%5D.target.content%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%3Bdata%5B%3F%28target.type%3Dtopic_sticky_module%29%5D.target.data%5B%3F%28target.type%3Danswer%29%5D.target.is_normal%2Ccomment_count%2Cvoteup_count%2Ccontent%2Crelevant_info%2Cexcerpt.author.badge%5B%3F%28type%3Dbest_answerer%29%5D.topics%3Bdata%5B%3F%28target.type%3Dtopic_sticky_module%29%5D.target.data%5B%3F%28target.type%3Darticle%29%5D.target.content%2Cvoteup_count%2Ccomment_count%2Cvoting%2Cauthor.badge%5B%3F%28type%3Dbest_answerer%29%5D.topics%3Bdata%5B%3F%28target.type%3Dtopic_sticky_module%29%5D.target.data%5B%3F%28target.type%3Dpeople%29%5D.target.answer_count%2Carticles_count%2Cgender%2Cfollower_count%2Cis_followed%2Cis_following%2Cbadge%5B%3F%28type%3Dbest_answerer%29%5D.topics%3Bdata%5B%3F%28target.type%3Danswer%29%5D.target.content%2Crelationship.is_authorized%2Cis_author%2Cvoting%2Cis_thanked%2Cis_nothelp%3Bdata%5B%3F%28target.type%3Danswer%29%5D.target.author.badge%5B%3F%28type%3Dbest_answerer%29%5D.topics%3Bdata%5B%3F%28target.type%3Darticle%29%5D.target.content%2Cauthor.badge%5B%3F%28type%3Dbest_answerer%29%5D.topics%3Bdata%5B%3F%28target.type%3Dquestion%29%5D.target.comment_count&limit=" + str(LIMIT)
#指定 url，获取对应原始内容 / 图片
def fetch_image(url):
try:
headers = {
"User-Agent": USER_AGENT,
"Referer": REFERER,
"authorization": AUTHORIZATION
}
s = requests.get(url, headers=headers)
except Exception as e:
print("fetch last activities fail. " + url)
raise e
return s.content
#指定 url，获取对应 JSON 返回 / 话题列表
def fetch_activities(url):
try:
headers = {
"User-Agent": USER_AGENT,
"Referer": REFERER,
"authorization": AUTHORIZATION
}
s = requests.get(url, headers=headers)
except Exception as e:
print("fetch last activities fail. " + url)
raise e
return s.json()
#处理返回的话题列表
def process_activities(datums, face_detective):
for data in datums["data"]:
target = data["target"]
if "content" not in target or "question" not in target or "author" not in target:
continue
#解析列表中每一个元素的内容
html = etree.HTML(target["content"])
seq = 0
#question_url = target["question"]["url"]
question_title = target["question"]["title"]
author_name = target["author"]["name"]
#author_id = target["author"]["url_token"]
print("current answer: " + question_title + " author: " + author_name)
#获取所有图片地址
images = html.xpath("//img/@src")
for image in images:
if not image.startswith("http"):
continue
s = fetch_image(image)
#请求人脸检测服务
scores = face_detective(s)
for score in scores:
filename = ("%d--" % score) + author_name + "--" + question_title + ("--%d" % seq) + ".jpg"
filename = re.sub(r'(?u)[^-\w.]', '_', filename)
#注意文件名的处理，不同平台的非法字符不一样，这里只做了简单处理，特别是 author_name / question_title 中的内容
seq = seq + 1
with open(os.path.join(DIR, filename), "wb") as fd:
fd.write(s)
#人脸检测 免费，但有 QPS 限制
time.sleep(2)
if not datums["paging"]["is_end"]:
#获取后续讨论列表的请求 url
return datums["paging"]["next"]
else:
return None
def get_valid_filename(s):
s = str(s).strip().replace(' ', '_')
return re.sub(r'(?u)[^-\w.]', '_', s)
import base64
def detect_face(image, token):
try:
URL = "https://aip.baidubce.com/rest/2.0/face/v3/detect"
params = {
"access_token": token
}
data = {
"face_field": "age,gender,beauty,qualities",
"image_type": "BASE64",
"image": base64.b64encode(image)
}
s = requests.post(URL, params=params, data=data)
return s.json()["result"]
except Exception as e:
print("detect face fail. " + url)
raise e
def fetch_auth_token(api_key, secret_key):
try:
URL = "https://aip.baidubce.com/oauth/2.0/token"
params = {
"grant_type": "client_credentials",
"client_id": api_key,
"client_secret": secret_key
}
s = requests.post(URL, params=params)
return s.json()["access_token"]
except Exception as e:
print("fetch baidu auth token fail. " + url)
raise e
def init_face_detective(app_id, api_key, secret_key):
# client = AipFace(app_id, api_key, secret_key)
# 百度云 V3 版本接口，需要先获取 access token
token = fetch_auth_token(api_key, secret_key)
def detective(image):
#r = client.detect(image, options)
# 直接使用 HTTP 请求
r = detect_face(image, token)
#如果没有检测到人脸
if r is None or r["face_num"] == 0:
return []
scores = []
for face in r["face_list"]:
#人脸置信度太低
if face["face_probability"] < 0.6:
continue
#颜值低于阈值
if face["beauty"] < BEAUTY_THRESHOLD:
continue
#性别非女性
if face["gender"]["type"] != "female":
continue
scores.append(face["beauty"])
return scores
return detective
def init_env():
if not os.path.exists(DIR):
os.makedirs(DIR)
init_env()
face_detective = init_face_detective(APP_ID, API_KEY, SECRET_KEY)
url = BASE_URL % SOURCE + URL_QUERY
while url is not None:
print("current url: " + url)
datums = fetch_activities(url)
url = process_activities(datums, face_detective)
#注意节操，爬虫休息间隔不要调小
time.sleep(5)
# vim: set ts=4 sw=4 sts=4 tw=100 et:
9 操作准备
需要登录，百度账号可以直接使用（贴吧/网盘通用），不用注册
随便填，这个阶段V3和V2都是默认勾选的。如果没有，请检查所有
在代码中填写AppID ApiKek SecretKey
{
"error": {
"message": "ZERR_NO_AUTH_TOKEN",
"code": 100,
"name": "AuthenticationInvalidRequest"
}
}
Chrome浏览器；找到一个知乎链接，点进去，打开开发者工具，查看HTTP请求头；无需登录
10 结论
欢迎关注我的专栏
面向薪资的编程-收录 Java 语言面试文章
编程基础和一些理论
编程的日常娱乐——用Python做一些有趣的事情
