Recordings and Datasets

Sample recordings

Those recordings are available in multiple formats: RAW (EVT2 or EVT3), DAT and HDF5 event files.

Name

Screenshot

Description

Sensor

Duration

Recordings

spinner

_images/spinner.png

Turning Spinner

Gen3.0

5 s

HDF5 (152.8 MB)

RAW EVT2 (207.9 MB)

DAT (413.2 MB)

hand_spinner

_images/hand_spinner.png

Turning 3-Blade Hand Spinner

Gen3.1

5 s

HDF5 (38.7 MB)

RAW EVT2 (46.9 MB)

laser

_images/laser.png

High-speed laser motion

Gen4.1

3 s

HDF5 (236.5 MB)

RAW EVT3 (326.2 MB)

80_balls

_images/80_balls.png

Falling 80 balls

Gen3.0

6.3 s

HDF5 (14.8 MB)

RAW EVT2 (19.2 MB)

195_falling_particles

_images/195_falling_particles.png

Falling 195 particles of

different sizes (synthetic data)

Gen3.1

32 ms

HDF5 (58.2 MB)

RAW EVT2 (77.3 MB)

monitoring_40_50hz

_images/monitoring_40_50hz.png

Object vibration at 40 and 50Hz

Gen3.0

6 s

HDF5 (113 MB)

RAW EVT2 (157 MB)

sparklers

_images/sparklers.png

High-speed scatter-like motion

of small particles

Gen3.0

95 ms

HDF5 (1.5 MB)

RAW EVT2 (2 MB)

200_jets_at_200hz

_images/200_jets.png

200 horizontal fluid jets

Gen3.1

2 s

HDF5 (1.5 MB)

RAW EVT2 (2.3 MB)

pedestrians

_images/pedestrians.png

Pedestrians in multiple directions

Gen4.1

30 s

HDF5 (126.6 MB)

RAW EVT3 (183.7 MB)

traffic_monitoring

_images/traffic_monitoring.png

Cars moving on a highway

(static camera)

Gen3.0

28 s

HDF5 (62.5 MB)

RAW EVT2 (70.3 MB)

driving_sample

_images/driving_sample.png

Driving on a street road

(moving camera)

Gen4.1

12.5 s

HDF5 (270.2 MB)

RAW EVT3 (352.2 MB)

box

_images/box.png

Camera moving around a box

(to use with metavision_model_3d_tracking sample)

Gen3.1

28.6 s

ZIP EVT2 (645.1 MB)

cube

_images/cube.png

Camera moving around a cube

(to use with metavision_model_3d_tracking sample)

Gen3.1

17.7 s

ZIP EVT2 (378.3 MB)

marker

_images/marker.png

Camera moving around a marker

(to use with metavision_model_3d_tracking sample)

Gen3.1

22.3 s

ZIP EVT2 (339.2 MB)

active_marker

_images/active_marker.png

Active Marker moving in front of the camera

(to use with Active Marker samples:

2D tracking and 3D tracking)

IMX636

31.6 s

ZIP EVT3 (53.4 MB)

aruco_marker

_images/aruco_marker.png

ArUco marker moving in front of the camera

(to use with metavision_aruco_marker_tracking sample)

IMX636

16.2 s

ZIP EVT3 (839.7 MB)

Datasets

Dataset

Application

Sensor

Resolution

Size

Format

1 Megapixel Automotive Detection

Automotive detection

Gen4.0

1280×720

1.6TB compressed

3.5TB uncompressed

Recording in DAT format

Labels in numpy format

HVGA ATIS Corner

Corner detection

Gen3.0 ATIS

480×360

6GB compressed

11GB uncompressed

Recording in DAT format

Gen1 N-CARS

Car classification

Gen1.0

crops from

304×240

280MB compressed

Recording in DAT format

Gen1 Automotive Detection

Automotive detection

Gen1.0

304×240

200GB compressed

750GB uncompressed

Recording in DAT format

Labels in numpy format

Simplified mini-dataset

ML Quick Start Tutorial

Gen4.0

1280×720

24GB uncompressed

Recording in DAT format

Labels in numpy format

Gen3 Gesture/Chifoumi dataset

Gesture classification

Gen3.1

640x480

113GB uncompressed

Recording in DAT format

Labels in numpy format

Precomputed Datasets

Those datasets were precompiled in an HDF5 tensor file format for faster training and smaller disk usage.

Dataset

Preprocessing

Sensor

Resolution

Size

Format

Gen4 automotive dataset

Event Cube

Gen4.0

1280×720 down to 640x360

211.3GB

HDF5

Labels in numpy format

Gen4 automotive dataset

Multi Channel Timesurface

Gen4.0

1280×720 down to 640x360

288.4GB

HDF5

Labels in numpy format

Gen4 automotive dataset

Histograms

Gen4.0

1280×720 down to 640x360

86GB

HDF5

Labels in numpy format

Gen1 automotive dataset

Event Cube

Gen1.0

304×240

59.3GB

HDF5

Labels in numpy format

Gen3 Gesture/Chifoumi dataset

histo_quantized

Gen3.1

640x480

3.2GB

HDF5

Labels in numpy format