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Athlete-Spy

Output example

Human pose estimation tool using TensorFlow Lite and OpenCV

A simple commandline tool for extracting and saving keypoints of a human pose from videos.

(C) Copyright Nico Mahler 2024

Prerequisites

  • Python v 3.4+

      $ python --version
    
  • CMake v 3.15+

      $ cmake --version
    
  • Conan package manager

      $ pip install conan
    

    (Hint: If not installed globally, add the scripts directory to path enviroment variable)

      %USERPROFILE%\AppData\Local\Packages\%PYTHON_VERSION%\local-packages\%PYTHON_VERSION%\scripts
    

Installation

  • Clone repository

      $ git clone https://github.com/Phlegmati/Athlete-Spy
    
  • Create conan build profile

      $ conan profile detect
    
  • Installing dependencies with Conan

      $ conan install . -s compiler.cppstd=17 --build=missing
    
  • Building

      $ cmake --preset conan-default
      $ cmake --build --preset conan-release
    

Usage

  • Run build with examples

      $ build\Release\athlete-spy.exe
    

    (Hint: Looks for example files in the "asset" folder in the current runtime enviroment)

      athlete-spy
      ├── assets
      │   ├── lite-model_movenet_singlepose_lightning_tflite_float16_4.tflite
      │   └── [email protected]
      └── build
          └── Release
              └── athlete-spy.exe
    
  • Manual Page

      $ build\Release\athlete-spy.exe --help
    
  • Pass video file (supported: *.mp4 *.avi)

      $ build\Release\athlete-spy.exe --video=path/to/video.file
    
  • Pass model file (supported: *.tflite)

      $ build\Release\athlete-spy.exe --model=path/to/model.file
    

Output

  • The processed pose video will be saved as an *.avi video and *.txt file

      athlete-spy
      └── output
          ├── video_processed.txt
          └── video_processed.mp4
    

References

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