sevivi readme Documentation Status Updates

sevivi is a python package and command line tool to generate videos of sensor data graphs synchronized to a video of the sensor movement.


  • TODO


Install the package from pypi:

pip install sevivi


Check out the usage documentation, please! If you just want to render a video to get started, keep reading. After you have downloaded the repository, you can use our test data. Run the following:

git clone
cd sevivi/
pip install sevivi
sevivi test-files/test-data-configs/kinect_sync_squatting.toml

If you want to use sevivi as a library, you can copy-paste the following code into your project. You should download our test files for this to run immediately.

import pandas as pd

from sevivi.config import RenderConfig, ManuallySynchronizedSensorConfig
from sevivi.image_provider import GraphImageProvider, VideoImuCaptureAppImageProvider
from sevivi.video_renderer import VideoRenderer

video_provider = VideoImuCaptureAppImageProvider(

# create a GraphImageProvider for each of your sensors
sensor_config = ManuallySynchronizedSensorConfig()
sensor_config.offset_seconds = 0.0 = "Human-Readable Name"
sensor_config.path = "test_files/sensors/imu_synchronization/camera_imu.csv.gz"
data = pd.read_csv(sensor_config.path, index_col=0, parse_dates=True)
graph_image_provider = GraphImageProvider(data, sensor_config)

# render the video
renderer = VideoRenderer(RenderConfig(), video_provider, [graph_image_provider])

Template Credits

This package was created with Cookiecutter and the pyOpenSci/cookiecutter-pyopensci project template, based off audreyr/cookiecutter-pypackage.