Skip to content

The repository supports TensorRT, QNN platform inference, 2D obstacle detection yolo series (yolov5-yolo11), semantic segmentation and so on.

License

Notifications You must be signed in to change notification settings

liwuhen/CVDeploy-2D

Repository files navigation

AI model deployment based on NVIDIA and Qualcomm platforms

Architecture   |   Documentation   |   Blog   |   Roadmap   |   Slack


License ARM Linux Ubuntu NVIDIA Qualcomm Parallel Computing HPC Performance GPU Accelerated

The repository mainly provides 2D model inference functionality, and the code provides daily development of packaged libs for integration, testing, and inference. The framework provides multi-threaded, singleton pattern, producer and consumer patterns. Cache log analysis is also supported.

third-party Third-party Libraries

Libraries Eigen Gflags Glog Yaml-cpp Cuda Cudnn Tensorrt Opencv
Version 3.4 2.2.2 0.6.0 0.8.0 11.4 8.4 8.4 3.4.5

Getting Started

Visit our documentation to learn more.

Performances

Model Platform Resolution FPS Memory Cpu
Yolov5 NVIDIA RTX4060 640x640 - - -
Yolov5 NVIDIA orin 640x640 - - -
Yolox NVIDIA RTX4060 416x416 - - -
Yolox NVIDIA orin 416x416 - - -

Contribute Contributing

Welcome users to participate in these projects. Please refer to CONTRIBUTING.md for the contributing guideline.We encourage you to join the effort and contribute feedback, ideas, and code. You can participate in Working Groups, Working Groups have most of their discussions on Slack or QQ (938558640).

References

About

The repository supports TensorRT, QNN platform inference, 2D obstacle detection yolo series (yolov5-yolo11), semantic segmentation and so on.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published