sevivi readme

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

• Free software: MIT license

• Documentation: https://sevivi.readthedocs.io.

Features

• TODO

Installation

Install the package from pypi:

pip install sevivi

Usage

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 git@github.com:your_name_here/sevivi.git
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(
    video_path="test_files/videos/imu_sync.mp4",
    imu_pb_path="test_files/sensors/video_imu_capture_app/video_meta.pb3"
)

# create a GraphImageProvider for each of your sensors
sensor_config = ManuallySynchronizedSensorConfig()
sensor_config.offset_seconds = 0.0
sensor_config.name = "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])
renderer.render_video()

Template Credits

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