machine_learn/draw/web_index.py

import time

from flask import Flask, request
import json
import MTCNN_person

app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello World!'

import requests
#图片链接
headers ={
    'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36'
}
dir = 'C:\\Users\\yufen\\Pictures\\face\\'
def do_download(url):
    url1 = url.split('?')[0]
    name = url1.split('/')[-1]
    r = requests.get(url, headers=headers)
    # 下载图片
    # 二进制数据需要用r.content 进行提取
    # 将图片放在‘图库’文件夹下，‘图库’是文件夹的名称，将图片放入该文件夹中，该文件夹与py文件在同一目录下
    f = open(dir + name, 'wb')
    f.write(r.content)
    f.close()
    return name

@app.route('/download')
def download():
    url = request.args.get('url')
    time1 = int(round(time.time() * 1000))
    print('info=%s' % url)
    do_download(url)
    time2 = int(round(time.time() * 1000))
    print('over %s from %s' % (time2 - time1, time1))
    return 'Hello World!'

@app.route('/face')
def face():
    info = request.args.get('url')
    time1 = int(round(time.time() * 1000))
    print('info=%s' % info)
    name = do_download(info)
    time2 = int(round(time.time() * 1000))
    faces = MTCNN_person.detector(dir + name)
    time3 = int(round(time.time() * 1000))
    print('over %s from %s' % (time3 - time1, time1))
    return json.dumps(faces)


if __name__ == '__main__':
    app.run(port=5000)
    # do_download(url='https://img.bbztx.com/article/live150178/team217182/20230913192631_tmp_9fbaaecf98fd1a3e91a6571f744f4b34511300d6c5a5b358.jpg?x-oss-process=image/resize,h_1000,m_lfit')
    # MTCNN_person.detector('C:\\Users\\yufen\\Pictures\\face\\20230913192631_tmp_9fbaaecf98fd1a3e91a6571f744f4b34511300d6c5a5b358.jpg')