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This C++ example demonstrates how to visualize VRS files with Rerun. VRS is a file format optimized to record & playback streams of sensor data, such as images, audio samples, and any other discrete sensors (IMU, temperature, etc), stored in per-device streams of time-stamped records.
Logging and visualizing with Rerun
The visualizations in this example were created with the following Rerun code:
3D arrows
void IMUPlayer::log_accelerometer(const std::array<float, 3>& accelMSec2) {
_rec->log(_entity_path + "/accelerometer", rerun::Arrows3D::from_vectors({accelMSec2}));
// … existing code for scalars …
}
Scalars
void IMUPlayer::log_accelerometer(const std::array<float, 3>& accelMSec2) {
// … existing code for Arrows3D …
_rec->log(_entity_path + "/accelerometer/x", rerun::Scalar(accelMSec2[0]));
_rec->log(_entity_path + "/accelerometer/y", rerun::Scalar(accelMSec2[1]));
_rec->log(_entity_path + "/accelerometer/z", rerun::Scalar(accelMSec2[2]));
}
void IMUPlayer::log_gyroscope(const std::array<float, 3>& gyroRadSec) {
_rec->log(_entity_path + "/gyroscope/x", rerun::Scalar(gyroRadSec[0]));
_rec->log(_entity_path + "/gyroscope/y", rerun::Scalar(gyroRadSec[1]));
_rec->log(_entity_path + "/gyroscope/z", rerun::Scalar(gyroRadSec[2]));
}
void IMUPlayer::log_magnetometer(const std::array<float, 3>& magTesla) {
_rec->log(_entity_path + "/magnetometer/x", rerun::Scalar(magTesla[0]));
_rec->log(_entity_path + "/magnetometer/y", rerun::Scalar(magTesla[1]));
_rec->log(_entity_path + "/magnetometer/z", rerun::Scalar(magTesla[2]));
}
Images
_rec->log(
_entity_path,
rerun::Image({
frame->getHeight(),
frame->getWidth(),
frame->getSpec().getChannelCountPerPixel()},
frame->getBuffer()
)
);
Text document
_rec->log_timeless(_entity_path + "/configuration", rerun::TextDocument(layout_str));
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Visualize streams of multimodal data. Fast, easy to use, and simple to integrate. Built in Rust using egui.
Build time aware visualizations of multimodal data
Use the Rerun SDK (available for C++, Python and Rust) to log data like images, tensors, point clouds, and text. Logs are streamed to the Rerun Viewer for live visualization or to file for later use.
A short taste
import rerun as rr # pip install rerun-sdk
rr.init("rerun_example_app")
rr.connect() # Connect to a remote viewer
# rr.spawn() # Spawn a child process with a viewer and connect
# rr.save("recording.rrd") # Stream all logs to disk
# Associate subsequent data with 42 on the “frame” timeline
rr.set_time_sequence("frame", 42)
# Log colored 3D points to the entity at `path/to/points`
rr.log("path/to/points", rr.Points3D(positions, colors=colors…
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