How to use TensorRT to accelerate segmentation models in YOLOv6 project?

[CrazySummerday]

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• I have read the README carefully. 我已经仔细阅读了README上的操作指引。

• I want to train my custom dataset, and I have read the tutorials for training your custom data carefully and organize my dataset correctly; (FYI: We recommand you to apply the config files of xx_finetune.py.) 我想训练自定义数据集，我已经仔细阅读了训练自定义数据的教程，以及按照正确的目录结构存放数据集。（FYI: 我们推荐使用xx_finetune.py等配置文件训练自定义数据集。）

• I have pulled the latest code of main branch to run again and the problem still existed. 我已经拉取了主分支上最新的代码，重新运行之后，问题仍不能解决。

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Question

Hello, while exploring the use of YOLOv6 for object detection tasks, I have also noticed the potential applications of YOLOv6 in the field of image segmentation. Although YOLOv6 itself is an object detection framework, I have found during my research that it can be used for segmentation tasks with some adjustments. However, I did not find any guidance on how to use TensorRT to accelerate segmentation models within the YOLOv6 framework.

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