default=30, help='interval of split video ') opt.parser.add_argument('--time', type=int, default=5, help='split video time') opt.parser.add_argument('--minmaskarea', type=int, default=2000, help='') opt.parser.add_argument('--quality', type=int, default=45, help='minimal quality') opt.parser.add_argument('--outsize', type=int, default=286, help='') opt.parser.add_argument('--startcnt', type=int, default=0, help='') opt.parser.add_argument('--minsize', type=int, default=96, help='minimal roi size') opt.parser.add_argument('--no_sclectscene', action='store_true', help='') opt = opt.getparse() util.makedirs(opt.savedir) util.writelog( os.path.join(opt.savedir, 'opt.txt'), str(time.asctime(time.localtime(time.time()))) + '\n' + util.opt2str(opt)) videopaths = util.Traversal(opt.datadir) videopaths = util.is_videos(videopaths) random.shuffle(videopaths) # def network net = loadmodel.bisenet(opt, 'roi') result_cnt = opt.startcnt video_cnt = 1
import cv2 import numpy as np try: from cores import Options, core from util import util from util import image_processing as impro from models import loadmodel except Exception as e: print(e) input('Please press any key to exit.\n') sys.exit(0) # python server.py --gpu_id 0 --model_path ./pretrained_models/mosaic/clean_face_HD.pth opt = Options() opt.parser.add_argument('--port', type=int, default=4000, help='') opt = opt.getparse(True) netM = loadmodel.bisenet(opt, 'mosaic') netG = loadmodel.pix2pix(opt) from flask import Flask, request import base64 import shutil app = Flask(__name__) @app.route("/handle", methods=["POST"]) def handle(): result = {} # to opencv img try: