AEDAT parses event-based dynamic-vision system (DVS) data from an input source and streams it to a sink.
AEStream is built in C++, but can be interfaced via CLI or Python (work in progress).
First, install PyTorch and libcaer.
Then install aestream via pip: pip install aestream
# Stream events from a DVS camera over USB at address 2:4
with DVSInput(2, 4, (640, 480)) as stream:
while True:
frame = stream.read() # Provides a (640, 480) tensor
...# Stream events from UDP port 3333 (default)
with UDPInput((640, 480), port=3333) as stream:
while True:
frame = stream.read() # Provides a (640, 480) tensor
...More examples can be found in our example folder.
AEStream produces a binary stream that requires you to specify an input source and an optional output source (defaulting to STDOUT).
The general syntax is as follows (input is required, output is optional):
aestream input <input source> [output <output sink>]We currently support the following inputs:
| Input | Description | Usage |
|---|---|---|
| DAVIS | 346x260 DVS camera with USB address X:Y, Inivation |
input inivation X Y davis |
| DVXplorer | 640x480 DVS camera with USB address X:Y, Inivation |
input inivation X Y dvx |
| Prophesee | 640x480 DVS camera with USB address X, Prophesee |
input prophesee X |
| Prophesee | 1280x720 DVS camera with USB address X, Prophesee |
input prophesee X |
| File | .aedat or .aedat4 |
input file x.aedat4 |
We currently support the following outputs:
| Output | Description | Usage |
|---|---|---|
| STDOUT | Standard output (default output) | output stdout |
| Ethernet over UDP | Outputs to a given IP and port using the SPIF protocol | output udp 10.0.0.1 1234 |
.aedat4 file |
Output to .aedat4 format |
output file my_file.aedat4 |
| CSV file | Output to comma-separated-value (CSV) file format | output file my_file.txt |
| Example | Syntax |
|---|---|
| Read file to STDOUT | aestream input file example/davis.aedat4 |
| Stream DVS Davis346 (USB 0:2) by iniVation AG to STDOUT (Note, requires Inivation libraries) | aestream input inivation 0 2 davis output stdout |
| Stream Prophesee 640x480 (serial Prophesee:hal_plugin_gen31_fx3:00001464) to STDOUT (Note, requires Metavision SDK) | aestream input prophesee Prophesee:hal_plugin_gen31_fx3:00001464 output stdout |
| Read file to remote machine X.X.X.X | aestream input file example/davis.aedat4 output udp X.X.X.X |
AEStream requires libtorch. Metavision SDK, libcaer and OpenCV are optional dependencies, but are needed for some functionality.
AEStream is based on C++20. Since C++20 is not yet fully supported by all compilers, we recommend using GCC >= 10.2.
To build the binaries of this repository, run the following code:
export CMAKE_PREFIX_PATH=`absolute path to libtorch/`
# Optional: Ensure paths to libcaer, Metavision, or OpenCV is in place
mkdir build/
cd build/
cmake -GNinja ..
ninja
If your default C++ compiler doesn't support C++ 20, you will have to install an up-to-date compiler and provide the environmental variable CXX.
For instance like this: CXX=/path/to/g++ cmake -GNinja ..
AEStream is created by
- Jens E. Pedersen (@GitHub jegp), doctoral student at KTH Royal Institute of Technology, Sweden.
- Christian Pehle (@GitHub cpehle), PostDoc at University of Heidelberg, Germany.
The work has received funding from the EC Horizon 2020 Framework Programme under Grant Agreements 785907 and 945539 (HBP) and by the Deutsche Forschungsgemeinschaft (DFG, German Research Fundation) under Germany's Excellence Strategy EXC 2181/1 - 390900948 (the Heidelberg STRUCTURES Excellence Cluster).
Thanks to Philipp Mondorf for interfacing with Metavision SDK and preliminary network code.
Please cite aestream if you use it in your work:
@software{aestream2022,
author = {Pedersen, Jens Egholm and
Pehle, Christian-Gernot},
title = {AEStream - Address Event Streaming library},
month = {August},
year = 2022,
publisher = {Zenodo},
version = {0.2.0},
doi = {10.5281/zenodo.6322829},
url = {https://doi.org/10.5281/zenodo.6322829}
}