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Tools for reading, processing, and writing CUWB data

Project description

process_cuwb_data

Tools for reading, processing, and writing CUWB data

Steps

  1. Copy .env.template to .env and update variables

  2. Install packages

    just build

  3. Download/create ground_truth_tray_carry.csv

  4. Generate pickled groundtruth features dataframe from ground_truth_tray_carry.csv

    process_cuwb_data \
        generate-tray-carry-groundtruth \
        --groundtruth-csv ./ignore/ground_truth_tray_carry.csv
  1. Train and pickle Tray Carry Detection Model using pickled groundtruth features
    process_cuwb_data \
        train-tray-carry-model \
        --groundtruth-features ./output/groundtruth/2021-05-13T12:53:26_tray_carry_groundtruth_features.pkl
  1. Infer Tray Interactions using pickled Tray Carry Detection Model
    process_cuwb_data \
      infer-tray-interactions \
      --environment greenbrier \
      --start 2021-04-20T9:00:00-0500 \
      --end 2021-04-20T9:05:00-0500 \
      --tray-carry-model ./output/models/2021-05-13T14:49:32_tray_carry_model.pkl

Other CLI Commands/Options

Export pickled UWB data

Working with Honeycomb's UWB endpoint can be painfully slow. For that reason there is an option to export pickled UWB data and provide that to subsequent inference commands.

    process_cuwb_data \
        fetch-cuwb-data \
        --environment greenbrier \
        --start 2021-04-20T9:00:00-0500 \
        --end 2021-04-20T9:05:00-0500

Use UWB export to run Tray Interaction Inference

    process_cuwb_data \
        infer-tray-interactions \
        --environment greenbrier \
        --start 2021-04-20T9:00:00-0500 \
        --end 2021-04-20T9:05:00-0500 \
        --tray-carry-model ./output/models/2021-05-13T14:49:32_tray_carry_model.pkl \
        --cuwb-data ./output/uwb_data/uwb-greenbrier-20210420-140000-20210420-140500.pkl

Supply Pose Track Inference to Tray Interaction Inference

Use Pose Tracks when determining nearest person to tray carry events.

Pose Inferences need to be sourced in a local directory. The pose directory can be supplied via CLI options.

    process_cuwb_data \
        infer-tray-interactions \
        --environment greenbrier \
        --start 2021-04-20T9:00:00-0500 \
        --end 2021-04-20T9:05:00-0500 \
        --tray-carry-model ./output/models/2021-05-13T14:49:32_tray_carry_model.pkl \
        --cuwb-data ./output/uwb_data/uwb-greenbrier-20210420-140000-20210420-140500.pkl \
        --pose-inference-id 3c2cca86ceac4ab1b13f9f7bfed7834e

Development

MacOS (Big Sur)

  1. Install pyenv: brew install pyenv
  2. Create a 3.8 venv: pyenv virtualenv 3.8.x wf-process-cuwb-data
  3. Trick pip to think you're running OS X: export SYSTEM_VERSION_COMPAT=1
  4. Install add'l packages: just install-dev

Project details


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