lw-egosuite-devkit 0.1.2

Lightwheel Egosuite DevKit - MCAP conversion and visualization pipeline

LW-Egosuite-DevKit

Backend Installation

Prerequisites

• Operating System: Ubuntu 20.04 or higher

Install

cd lw_egosuite_devkit

conda create -n lw_egosuite_devkit python=3.11 -y
conda activate lw_egosuite_devkit
pip3 install -e .

Usage

1. Conversion for Visualization

Generate visualization-ready MCAP files from raw egosuite MCAP data.

1.1 Single File Conversion

cd lw_egosuite_devkit
mkdir output
lwviz convert --path $input_mcap_path --writer.path $mcap_for_vis_path

• $input_mcap_path: The path to the source MCAP file.
• $mcap_for_vis_path: (Optional) The destination path for the generated MCAP file. Default is ./output/${input_mcap_filename}_vis.mcap.

1.2 Batch Conversion

cd lw_egosuite_devkit
mkdir -p output

data_path="/path/to/your/data"

for input_mcap_path in "$data_path"/*.mcap; do
    [ -e "$input_mcap_path" ] || continue

    base_name=$(basename "$input_mcap_path" .mcap)

    mcap_for_vis_path="./output/${base_name}_vis.mcap"

    echo "Processing: $base_name ..."

    # process the file
    lwviz convert --path "$input_mcap_path" --writer.path "$mcap_for_vis_path"
done

• $data_path: The directory containing the source MCAP files. Each file will be converted and saved with a _vis.mcap suffix in the ./output/ directory.

2. Visualization with Foxglove Studio

Follow these steps to visualize the processed data in Foxglove Studio:

1. Launch Foxglove: Open the Foxglove Studio desktop application or web version.
2. Import Layout: Load the recommended configuration file: assets/default_layout.json.
3. Load Data Streams: Simultaneously load the source file mcap_filename.mcap and the generated visualization file ./output/{mcap_filename}_vis.mcap.

Once loaded, the visualization will appear in the Foxglove Studio dashboard as shown below:

License

This project is licensed under the Apache License 2.0.

Copyright 2026 Lightwheel Team