def post(self):
args = parse_args()
if args['type'] == 'face':
m = FaceDetect.Face()
elif args['type'] in [None, 'object']:
m = ObjectDetect.Object()
else:
abort(400, msg='Invalid Model:{}'.format(args['type']))
fip, ext = get_file(args)
detections = m.detect(fip, ext, args)
return detections
if not db.check_credentials(username, password):
abort(401, message='incorrect credentials')
# Identity can be any data that is json serializable
access_token = create_access_token(identity=username)
response = jsonify(access_token=access_token,
expires=g.ACCESS_TOKEN_EXPIRES)
response.status_code = 200
return response
# main init
#inizializzi i modelli per risparmiare tempo poi!
coral_m = ObjectDetectCoral.ObjectCoral()
object_m = ObjectDetect.Object()
app = Flask(__name__)
def get_http_exception_handler(app):
"""Overrides the default http exception handler to return JSON."""
handle_http_exception = app.handle_http_exception
@wraps(handle_http_exception)
def ret_val(exception):
exc = handle_http_exception(exception)
return jsonify({'code': exc.code, 'msg': exc.description}), exc.code
return ret_val
def function_to_run_only_once():
face_obj = FaceRecog.Face()
od_obj = ObjectDetect.Object()
# If you want to use ZM
# note your URL may need /cgi-bin/zm/nph-zms - make sure you specify it correctly
# CAPTURE_SRC='https://demo.zoneminder.com/cgi-bin-zm/nph-zms?mode=jpeg&maxfps=5&buffer=1000&monitor=18&user=zmuser&pass=zmpass'
#--------- end ----------------------------
ap = argparse.ArgumentParser()
ap.add_argument('-c', '--config', required=True, help='config file with path')
ap.add_argument('-s', '--source', required=True, help='source file')
args, u = ap.parse_known_args()
args = vars(args)
utils.process_config(args)
import modules.object as ObjectDetect
od_obj = ObjectDetect.Object()
#pb_dir = '/home/iconnor/Downloads/ssd_mobilenet_v2_coco_2018_03_29'
pb_dir = '/home/iconnor/ssdlite_mobilenet_v2_coco_2018_05_09'
pb = pb_dir + '/frozen_inference_graph.pb'
pbtxt = pb_dir + '/frozen_inference_graph.pbtxt'
tfNet = cv2.dnn.readNetFromTensorflow(pb, pbtxt)
login_url = BASE_API_URL + '/login'
object_url = BASE_API_URL + '/detect/object'
access_token = None
auth_header = None
# Draws bounding box around detections
def draw_boxes(frame, data):