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:
