python实现知乎高颜值图片爬取
2019-08-12 14:18
1496 查看
导入相关包
import time import pydash import base64 import requests from lxml import etree from aip import AipFace from pathlib import Path
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 = "xxxxxxxxxxxxxxxx" SECRET_KEY = "xxxxxxxxxxxxxxxx" # 过滤颜值阈值,存储空间大的请随意 BEAUTY_THRESHOLD = 55 AUTHORIZATION = "oauth c3cef7c66a1843f8b3a9e6a1e3160e20" # 如果权限错误,浏览器中打开知乎,在开发者工具复制一个,无需登录 # 建议最好换一个,因为不知道知乎的反爬虫策略,如果太多人用同一个,可能会影响程序运行
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" 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) HEADERS = { "User-Agent": USER_AGENT, "Referer": REFERER, "authorization": AUTHORIZATION
指定 url,获取对应原始内容 / 图片
def fetch_image(url): try: response = requests.get(url, headers=HEADERS) except Exception as e: raise e return response.content
指定 url,获取对应 JSON 返回 / 话题列表
def fetch_activities(url): try: response = requests.get(url, headers=HEADERS) except Exception as e: raise e return response.json()
处理返回的话题列表
def parser_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 html = etree.HTML(target["content"]) seq = 0 title = target["question"]["title"] author = target["author"]["name"] images = html.xpath("//img/@src") for image in images: if not image.startswith("http"): continue image_data = fetch_image(image) score = face_detective(image_data) if not score: continue name = "{}--{}--{}--{}.jpg".format(score, author, title, seq) seq = seq + 1 path = Path(__file__).parent.joinpath("image").joinpath(name) try: f = open(path, "wb") f.write(image_data) f.flush() f.close() print(path) time.sleep(2) except Exception as e: continue if not datums["paging"]["is_end"]: return datums["paging"]["next"] else: return None
初始化颜值检测工具
def init_detective(app_id, api_key, secret_key): client = AipFace(app_id, api_key, secret_key) options = {"face_field": "age,gender,beauty,qualities"} def detective(image): image = str(base64.b64encode(image), "utf-8") response = client.detect(str(image), "BASE64", options) response = response.get("result") if not response: return if (not response) or (response["face_num"] == 0): return face_list = response["face_list"] if pydash.get(face_list, "0.face_probability") < 0.6: return if pydash.get(face_list, "0.beauty") < BEAUTY_THRESHOLD: return if pydash.get(face_list, "0.gender.type") != "female": return score = pydash.get(face_list, "0.beauty") return score return detective
程序入口
def main(): face_detective = init_detective(APP_ID, API_KEY, SECRET_KEY) url = BASE_URL % SOURCE + URL_QUERY while url is not None: datums = fetch_activities(url) url = parser_activities(datums, face_detective) time.sleep(5) if __name__ == '__main__': main()
以上就是本文的全部内容,希望对大家的学习有所帮助
您可能感兴趣的文章:
相关文章推荐
- Python爬虫 + 人脸检测 + 颜值检测 = 知乎高颜值图片抓取
- Python项目实战:实现简单爬取知乎问题下的图片
- Python 实现简单的网络抓取图片
- python实现识别相似图片小结
- 用python实现对比两张图片的不同
- Python实现图片滑动式验证识别方法
- 使用Python-OpenCV向图片添加噪声的实现(高斯噪声、椒盐噪声)
- Python使用Scrapy爬虫框架全站爬取图片并保存本地的实现代码
- 相似图片检测:感知哈希算法之dHash的Python实现
- python实现多线程抓取知乎用户
- Python 实现的下载op海贼王网的图片(网络爬虫)
- Python 实现输入名字自动批量下载图片
- python爬虫技术实现图片提取
- Python3实现转换Image图片格式
- Python爬虫实现获取动态gif格式搞笑图片的方法示例
- python实现路由追踪,并生成追踪图片
- python实现趣味图片字符化
- Python 2.6.2 + mongodb 2.0.7 +GridFS 实现图片的存取
- python+pyqt实现12306图片验证效果
- python实现图片转字符画