在做深度学习研究与应用的时候，经常需要爬取样本，例如，超分辨率重建，实际的训练与产品应用中，你需要爬取一些高清的图片，下面提供一个简单的爬虫：
# coding=utf-8import reimport sysimport urllibimport osimport requestsdef get_onepage_urls(onepageurl):if not onepageurl:print('执行结束')return [], ''try:html = requests.get(onepageurl).textexcept Exception as e:print(e)pic_urls = []fanye_url = ''return pic_urls, fanye_urlpic_urls = re.findall('"objURL":"(.*?)",', html, re.S)fanye_urls = re.findall(pile(r'<a href="(.*)" class="n">下一页</a>'), html, flags=0)fanye_url = '' + fanye_urls[0] if fanye_urls else ''fanye_url = fanye_url + "&z=9" #z=9表示爬取特大尺寸return pic_urls, fanye_urldef down_pic(pic_urls,localPath):print ("need download:%d" % len(pic_urls))if not os.path.exists(localPath): #os.mkdir(localPath)"""给出图片链接列表, 下载图片"""for i, pic_url in enumerate(pic_urls):try:pic = requests.get(pic_url, timeout=30)string = str(i + 1) + '.jpg'with open(os.path.join(localPath,'%d.jpg' % i), 'wb')as f:f.write(pic.content)print('成功下载第%s张图片: %s' % (str(i + 1), str(pic_url)))except Exception as e:print('下载第%s张图片时失败: %s' % (str(i + 1), str(pic_url)))print(e)continueif __name__ == '__main__':keyword = sys.argv[1] # 关键词, 改为你想输入的词即可url_init_first = r'/search/flip?tn=baiduimage&ipn=r&ct=26592&cl=2&lm=-1&st=-1&fm=result&fr=&sf=1&fmq=1497491098685_R&pv=&ic=0&nc=1&z=9&se=1&showtab=0&fb=0&width=&height=&face=0&istype=2&ie=utf-8&ctd=1497491098685%5E00_1519X735&word='url_init = url_init_first + urllib.parse.quote(keyword, safe='/')all_pic_urls = []onepage_urls, fanye_url = get_onepage_urls(url_init)all_pic_urls.extend(onepage_urls)fanye_count = 1 # 图片所在页数，下载完后调整这里就行while 1:onepage_urls, fanye_url = get_onepage_urls(fanye_url)fanye_count += 1print('第%s页' % fanye_count)if fanye_url == '' and onepage_urls == []:breakall_pic_urls.extend(onepage_urls)print ("need download:%d" % len(all_pic_urls))down_pic(list(set(all_pic_urls)),os.path.join('./image/'+sys.argv[1]))#保存位置也可以修改
运行环境需要python3支持。
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