initiate_inference

def initialise_inference(self):
        
        model_xml=self.model
        model_bin = os.path.splitext(model_xml)[0] + ".bin"

        # Plugin initialization for specified device and load extensions library if specified
        log.info("Initializing plugin for {} device...".format(self.device))
        plugin = IEPlugin(device=self.device, plugin_dirs=self.plugin_dir)
        if self.cpu_extension and 'CPU' in self.device:
            log.info("Loading plugins for {} device...".format(self.device))
            plugin.add_cpu_extension(self.cpu_extension)
        
        # Read IR
        log.info("Reading IR...")
        net = IENetwork(model=model_xml, weights=model_bin)

        if plugin.device == "CPU":
            supported_layers = plugin.get_supported_layers(net)
            not_supported_layers = [l for l in net.layers.keys() if l not in supported_layers]
            if len(not_supported_layers) != 0:
                log.error("Following layers are not supported by the plugin for specified device {}:\n {}".
                        format(plugin.device, ', '.join(not_supported_layers)))
                log.error("Please try to specify cpu extensions library path in sample's command line parameters using -l "
                        "or --cpu_extension command line argument")
                sys.exit(1)
        

        assert len(net.inputs.keys()) == 1, "Sample supports only single input topologies"
        assert len(net.outputs) == 1, "Sample supports only single output topologies"
        
        input_blob = next(iter(net.inputs))
        out_blob = next(iter(net.outputs))
        log.info("Loading IR to the plugin...")
        exec_net = plugin.load(network=net, num_requests=2)

        if isinstance(net.inputs[input_blob], list):
            n, c, h, w = net.inputs[input_blob]
        else:
            n, c, h, w = net.inputs[input_blob].shape
        del net
        processor= Processor(exec_net,input_blob,out_blob,n,c,h,w)
        return processor