mmdeploy VS openvino

The RK3588 also has a NPU for accelerating neural networks. The bad news is the API is not supported by any of the inference engines (afaik), but the NPU can run models directly that have been converted to the RKNN format. It is a long shot, but you can find details here.

BibTeX @misc{=mmdeploy, title={OpenMMLab's Model Deployment Toolbox.}, author={MMDeploy Contributors}, howpublished = {\url{https://github.com/open-mmlab/mmdeploy}}, year={2021} }

I have a semantic segmentation model trained using the mmdetection repo. Then it is converted to the ONNX format using the mmdeploy repo.

V766 An item with the same key '"SoftPlus"' has already been added. cpu_types.cpp 198

Ever wonder how some AI projects manage to deliver breakthroughs in record time? OpenVINO, an open-source toolkit designed for optimizing and deploying AI models, is one such standout. With C++ at its core, this repository has consistently delivered on its promises. But what really sets it apart?

In fact, the analyzer didn't find that many errors. All the interesting and important errors fit into just a couple of articles. The code is quite beautiful and secure. The commit I was using to build and test the project is still the same: 2d8ac08.

The commit I built the project on for checking it: 2d8ac08.