server.py

import pymysql
from http.server import BaseHTTPRequestHandler, HTTPServer
import requests
import neural_style as ns
from PIL import Image
import matplotlib.pyplot as plt
from torchvision.utils import save_image


port = 8000

class my_handler(BaseHTTPRequestHandler):

    def _set_header(self):
        self.send_response(200)
        self.send_header('Content-Type', 'text/html; charset=utf-8')
        self.end_headers()


    def _key_value_parser(self, lists):
        data = lists.split("&")
        print(data)
        set_ = {}

        for list in data:
            temp = list.split('=')
            set_[temp[0]] = temp[1]

        return set_


    #create
    def do_POST(self):
        self._set_header()
        content_length = int(self.headers['Content-Length'])
        body = self.rfile.read(content_length).decode('utf-8')

        request = self.path.split("192.168.50.67:8000")[0]
        print("=====================")
        print(request)
        print(body)
        
        kv = self._key_value_parser(body)
        print(kv)
        if(request == '/synthesizing'):
            print("1")
            cnn, cnn_normalization_mean, cnn_normalization_std, style_img, content_img, input_img = ns.set_neural_style(kv['content_image'], kv['style_image'])
            output = ns.run_style_transfer(cnn, cnn_normalization_mean, cnn_normalization_std,
                                content_img, style_img, input_img)

            save_img = output[0]
            output_name = '{}x{}.jpg'.format(kv['style_image'], kv['content_image'])
            save_image(save_img, './data/images/output/{}'.format(output_name))

            self.wfile.write('{}'.format(output_name).encode('utf-8'))

            print('synthesizing')
            print('\n\n')

def run():
    httpd = HTTPServer(('192.168.50.67', port), my_handler)
    print('Server running on port : {}'.format(port))
    httpd.serve_forever()

run()