diff --git a/modules/inference_engine_openvino.py b/modules/inference_engine_openvino.py
index a664709..ab668fa 100644
--- a/modules/inference_engine_openvino.py
+++ b/modules/inference_engine_openvino.py
@@ -1,28 +1,28 @@
 import os
 
 import numpy as np
-from openvino.inference_engine import IENetwork, IECore
+from openvino.inference_engine import IECore
 
 
 class InferenceEngineOpenVINO:
     def __init__(self, net_model_xml_path, device):
         self.device = device
+        self.ie = IECore()
 
         net_model_bin_path = os.path.splitext(net_model_xml_path)[0] + '.bin'
-        self.net = IENetwork(model=net_model_xml_path, weights=net_model_bin_path)
+        self.net = self.ie.read_network(model=net_model_xml_path, weights=net_model_bin_path)
         required_input_key = {'data'}
-        assert required_input_key == set(self.net.inputs.keys()), \
+        assert required_input_key == set(self.net.input_info.keys()), \
             'Demo supports only topologies with the following input key: {}'.format(', '.join(required_input_key))
         required_output_keys = {'features', 'heatmaps', 'pafs'}
         assert required_output_keys.issubset(self.net.outputs.keys()), \
             'Demo supports only topologies with the following output keys: {}'.format(', '.join(required_output_keys))
 
-        self.ie = IECore()
         self.exec_net = self.ie.load_network(network=self.net, num_requests=1, device_name=device)
 
     def infer(self, img):
-        input_layer = next(iter(self.net.inputs))
-        n, c, h, w = self.net.inputs[input_layer].shape
+        input_layer = next(iter(self.net.input_info))
+        n, c, h, w = self.net.input_info[input_layer].input_data.shape
         if h != img.shape[0] or w != img.shape[1]:
             self.net.reshape({input_layer: (n, c, img.shape[0], img.shape[1])})
             self.exec_net = self.ie.load_network(network=self.net, num_requests=1, device_name=self.device)