def inference_with_visualization()

in source/neo/eval.py [0:0]

• 14 lines of code
• 2 McCabe index (conditional complexity)

    def inference_with_visualization(self, neo_optimized=True):
        """
        object detector inference and dump the image with bounding boxes and confidences plotted

        :return: None
        """
        image_data_for_raw_model, image_data_for_neo_optimized_model = self.get_model_input()
        if not neo_optimized:
            response = self.eval_without_neo(x=image_data_for_raw_model)
            save_path = 'body_det_vis.jpg'
        else:
            response = self.eval_with_neo(x=image_data_for_neo_optimized_model)
            save_path = 'body_det_vis_with_neo.jpg'

        # save image with bounding boxes plotted
        self.visualize(
            full_path=self._test_image_path,
            bbox_coords=response['bbox_coords'],
            bbox_scores=response['bbox_scores'],
            label_name='Person',
            save_path=save_path)