torchreid-embedder-service

An person embedder for features based person tracking

Configure your torchreid-embedder-service vision service

{
  "model_path": "/path/to/your/model"
}

Run test

make setup #or make setup-jp6 on jetson machines
source build/.venv/bin/activate
export PYTHONPATH=$PYTHONPATH:$(pwd)\
python src/test_integration.py

Makefile targets for arm-jetson JP6 machines only

This project includes a Makefile script to automate the PyInstaller build process for Jetson machines. Building and deploying the module for other platforms should be done through CI. PyInstaller is used to create standalone executables from the Python module scripts.

1. Build dev environment

Run :

make setup-jp6

1. installs system dependencies (cuDNN and cuSPARSELt)
2. creates venv environment (under ./build/.venv)
3. gets/builds python packages wheel files - Torch, Torchvision (built from source)

Cleaned with make clean (this also deletes pyinstaller build directory)

2. Build module executable

make pyinstaller

This command builds the module executable using PyInstaller.

This creates the PyInstaller executable under ./build/pyinstaller_dist.

3. Upload to viam registry:

Edit first_run field in meta.json file

"first_run": "first_run_jp6.sh"

Compress the module with the updated meta.json and first_run_jp6.sh using:

make module.tar.gz

and upload to the registry:

viam login
viam module upload --version 0.0.0-rc0 --platform linux/arm64 --tags 'jetpack:6' module.tar.gz

Cleaned with make clean