def output_json(data, code, headers=None):
"""Makes a Flask response with a JSON encoded body"""
# 如果是app接口，且不是支付回调，加密后返回
Logger.log("请求id：%s 响应\n返回JSON：%s\n" % (session['requestId'], data))
resp = make_response(json.dumps(data), code)
resp.headers.extend(headers or {})
return resp
def handle(self):
parser = reqparse.RequestParser()
parser.add_argument('type')
args = parser.parse_args()
usage = ''
if args.type is None:
return CommonUtil.json_response(-1, '缺少参数:type')
elif args.type == '0':
usage = 'regAccount' # 注册账号
elif args.type == '1':
usage = 'findPassword' # 找回密码
elif args.type == '2':
usage = 'adminLogin' # 管理台登录
else:
return CommonUtil.json_response(-1, 'type参数格式错误')
# 用客户端ip来作为sendId是为了使频繁请求时可以替换这个key下面原来的验证码
md5 = hashlib.md5()
md5.update("validimage_{}_{}".format(request.environ['REMOTE_ADDR'],
usage).encode('utf-8'))
sendId = md5.hexdigest()
validImage = ValidImage.create()
Redis.setex(sendId, 60, validImage['code'])
data = {"img": validImage['img'], "sendId": sendId}
Logger.log("生成图片验证码 ip:{} sendId:{} code:{}".format(
request.environ['REMOTE_ADDR'], sendId, validImage['code']))
return CommonUtil.json_response(0, "success", data)
def __init__(self):
md5 = hashlib.md5()
md5.update(os.urandom(24))
session['requestId'] = md5.hexdigest()
Logger.log("请求 请求id：%s\n来源IP：%s\n请求方法：%s\n请求路径：%s\n请求参数：%s" %
(session['requestId'], request.environ['REMOTE_ADDR'],
request.environ['REQUEST_METHOD'], request.url,
json.dumps(request.form)))
Resource.__init__(self)
def __init__(self):
md5 = hashlib.md5()
md5.update(os.urandom(24))
session['requestId'] = md5.hexdigest()
Logger.log(
">>>>>>>>>>>>>>>>>>>>>>> 请求 请求id：%s >>>>>>>>>>>>>>>>>>>>>>>\n%s|%s|%s|%s|%s"
%
(session['requestId'],
time.strftime("%Y-%m-%d %H:%M:%S", time.localtime()),
request.environ['REMOTE_ADDR'], request.environ['REQUEST_METHOD'],
request.url, request.get_data()))
Resource.__init__(self)
def real_time_recognize(
self,
width=640,
height=360,
resize=1.0,
detector="mtcnn",
flip=False,
graphics=True,
socket=None,
mtcnn_stride=1,
):
"""Real-time facial recognition
:param width: width of frame (default: 640)
:param height: height of frame (default: 360)
:param resize: resize scale (default: 1. = no resize)
:param detector: face detector type (default: "mtcnn")
:param flip: whether to flip horizontally or not (default: False)
:param graphics: whether or not to use graphics (default: True)
:param socket: socket (dev) (default: None)
:param mtcnn_stride: stride frame stride (default: 1)
"""
assert self._db, "data must be provided"
assert 0.0 <= resize <= 1.0, "resize must be in [0., 1.]"
graphics_controller = GraphicsRenderer(width, height, resize)
logger = Logger(frame_limit=10, frame_threshold=5)
pbar = ProgressBar(logger, ws=socket)
cap = Camera()
detector = FaceDetector(detector,
self.img_shape,
min_face_size=240,
stride=mtcnn_stride)
while True:
_, frame = cap.read()
cframe = frame.copy()
# resize frame
if resize != 1:
frame = cv2.resize(frame, (0, 0), fx=resize, fy=resize)
# facial detection and recognition
info = self.recognize(frame, detector, flip=flip)
face, is_recognized, best_match, elapsed = info
# logging and socket
if is_recognized and is_looking(face):
log_result = logger.log(best_match)
pbar.update(end=log_result is not None)
if log_result and socket:
socket.send(json.dumps({"best_match": best_match}))
# graphics
if graphics:
graphics_controller.add_graphics(cframe, *info)
cv2.imshow("AI Security v2021.0.1", cframe)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
cap.release()
cv2.destroyAllWindows()
def json_response(cls, code, msg, data={}):
res = {"code": code, "message": msg, "data": data}
Logger.log("响应 请求id：%s\n返回内容：%s" %
(session['requestId'], json.dumps(res)))
return res