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Kneron AI Training/Deployment Platform (mmpose-based)

Introduction


kneron-mmpose is a platform built upon the well-known mmpose for pose estimation . We encourage that you may start with the rsn18_hand_pose_step_by_step.md to build basic knowledge of Kneron-Edition MMPose, and read mmpose docs for detailed mmpose usage.

In this repository, we provide an end-to-end training/deployment flow to realize on Kneron's AI accelerators:

  1. Training/Evalulation:
  2. Converting to onnx:
    • pytorch2onnx_kneron.py (beta)
    • Export optimized and Kneron-toolchain supported onnx
      • Automatically modify model for arbitrary data normalization preprocess
  3. General Evaluation
    • tools/test_kneron.py (beta)
    • Evaluate the model with pytorch checkpoint, onnx, and kneron-nef
  4. Testing
    • inference_kn (beta)
    • Verify the converted NEF model on Kneron USB accelerator with this API
  5. Converting Kneron-NEF: (toolchain feature)
    • Convert the trained pytorch model to Kneron-NEF model, which could be used on Kneron hardware platform.

License

This project is released under the Apache 2.0 license.

Changelog

N/A

Overview of Benchmark and Kneron Model Zoo

Backbone size Mem (GB) AUC PCK EPE Config Download
rsn18 224 0.014 0.855 0.987 3.687 config model

Installation

Getting Started

Tutorial - Kneron Edition

Documents - Kneron Edition

Original mmpose Documents

Contributing


kneron-mmpose a platform built upon OpenMMLab-mmpose

  • For issues regarding to the original mmpose: We appreciate all contributions to improve OpenMMLab-mmpose. Ongoing projects can be found in out GitHub Projects. Welcome community users to participate in these projects. Please refer to CONTRIBUTING.md for the contributing guideline.

  • For issues regarding to this repository kneron-mmpose: Welcome to leave the comment or submit the pull request here to improve kneron-mmpose

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