def predict(self, image):
    '\n        This method is meant for running predictions on the input image.\n        '
    if np.all(np.array(image.shape)):
        net_input = {self.input_blob: self.preprocess_input(image)}
        if self.async_infer:
            self.infer_request_handle = self.exec_network.start_async(request_id=0, inputs=net_input)
            if (self.exec_network.requests[0].wait((- 1)) == 0):
                outputs = self.infer_request_handle.outputs[self.output_blob]
                (eyes_coords, crop_left, crop_right) = self.preprocess_output(outputs, image)
        else:
            self.infer_request_handle = self.exec_network.infer(inputs=net_input)
            outputs = self.infer_request_handle[self.output_blob]
            (eyes_coords, crop_left, crop_right) = self.preprocess_output(outputs, image)
    else:
        eyes_coords = []
        crop_left = []
        crop_right = []
    return (eyes_coords, crop_left, crop_right)
This method is meant for running predictions on the input image.
def predict(self, image):
    '\n        \n        '
    if np.all(np.array(image.shape)):
        net_input = {self.input_blob: self.preprocess_input(image)}
        if self.async_infer:
            self.infer_request_handle = self.exec_network.start_async(request_id=0, inputs=net_input)
            if (self.exec_network.requests[0].wait((- 1)) == 0):
                outputs = self.infer_request_handle.outputs[self.output_blob]
                (eyes_coords, crop_left, crop_right) = self.preprocess_output(outputs, image)
        else:
            self.infer_request_handle = self.exec_network.infer(inputs=net_input)
            outputs = self.infer_request_handle[self.output_blob]
            (eyes_coords, crop_left, crop_right) = self.preprocess_output(outputs, image)
    else:
        eyes_coords = []
        crop_left = []
        crop_right = []
    return (eyes_coords, crop_left, crop_right)