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aestream-0.4.0
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Streaming library for Address-Event Representation (AER) data
| ویژگی | مقدار |
|---|---|
| سیستم عامل | - |
| نام فایل | aestream-0.4.0 |
| نام | aestream |
| نسخه کتابخانه | 0.4.0 |
| نگهدارنده | [] |
| ایمیل نگهدارنده | [] |
| نویسنده | Jens E. Pedersen, Christian Pehle |
| ایمیل نویسنده | jens@jepedersen.dk, christian.pehle@gmail.com |
| آدرس صفحه اصلی | https://github.com/norse/aestream |
| آدرس اینترنتی | https://pypi.org/project/aestream/ |
| مجوز | MIT |
# AEStream - Address Event streaming library
<p align="center">
<a href="https://github.com/norse/aestream/actions">
<img src="https://github.com/norse/aestream/workflows/Build%20and%20test/badge.svg" alt="Test status"></a>
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</a>
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</a>
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<img src="https://img.shields.io/discord/723215296399147089"
alt="chat on Discord"></a>
<a href="https://www.codacy.com/gh/norse/aestream/dashboard?utm_source=github.com&utm_medium=referral&utm_content=norse/aestream&utm_campaign=Badge_Grade"><img src="https://app.codacy.com/project/badge/Grade/0a04a852daf540a9b9bbe9d78df9eea7"/></a>
<a href="https://doi.org/10.5281/zenodo.6322829"><img src="https://zenodo.org/badge/DOI/10.5281/zenodo.6322829.svg" alt="DOI"></a>
</p>
AEDAT parses event-based dynamic-vision system (DVS) data from an input source and streams it to a sink (see table below).
## Installation
AEStream can be installed with the Python package manage `pip`.
However, **AEStream depends on [PyTorch](https://pytorch.org/), [LZ4](https://lz4.github.io/lz4/), and [libcaer](https://gitlab.com/inivation/dv/libcaer/)**, so please install these dependencies manually **before** you install AEStream.
For PyTorch, recall whether you are using the CPU or CUDA version and use the corresponding command below to install AEStream:
| **PyTorch version** | **Command** |
| -------------------- | --- |
| With CPU | `pip install aestream --extra-index-url https://download.pytorch.org/whl/cpu ` |
| With CUDA | `pip install aestream --extra-index-url https://download.pytorch.org/whl/cu116` |
Note that this uses CUDA 11.6. Other versions can be found and used by copying links from [the website of PyTorch](https://pytorch.org/).
We do not currently support other platforms than Linux, but contributions are most welcome.
## Usage (Python)
The Python API exposes two classes for reading DVS data sources into PyTorch tensors: `USBInput` and `UDPInput`.
```python
# Stream events from a DVS camera over USB
with USBInput((640, 480)) as stream:
while True:
frame = stream.read() # Provides a (640, 480) tensor
...
```
```python
# 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](https://github.com/norse/aestream/tree/master/example).
Please note the examples may require additional dependencies (such as [Norse](https://github.com/norse/norse) for spiking networks or [PySDL](https://github.com/py-sdl/py-sdl2) for rendering). To install all the requirements, simply stand in the `aestream` root directory and run `pip install -r example/requirements.txt`
## Usage (CLI)
Installing AEStream also gives access to the command-line interface (CLI) `aestream`.
To use `aestraem`, simply provide an `input` source and an optional `output` sink (defaulting to STDOUT):
```bash
aestream input <input source> [output <output sink>]
```
## Supported Inputs and Outputs
| Input | Description | Usage |
| --------- | :----------- | ----- |
| DAVIS, DVXPlorer | [Inivation](https://inivation.com/) DVS Camera over USB | `input inivation` |
| EVK Cameras | [Prophesee](https://www.prophesee.ai/) DVS camera over USB | `input prophesee` |
| File | [AEDAT file format](https://gitlab.com/inivation/inivation-docs/blob/master/Software%20user%20guides/AEDAT_file_formats.md) as `.aedat` or `.aedat4` | `input file x.aedat4` |
| Output | Description | Usage |
| --------- | ----------- | ----- |
| STDOUT | Standard output (default output) | `output stdout`
| Ethernet over UDP | Outputs to a given IP and port using the [SPIF protocol](https://github.com/SpiNNakerManchester/spif) | `output udp 10.0.0.1 1234` |
| `.aedat4` file | Output to [`.aedat4` format](https://gitlab.com/inivation/inivation-docs/blob/master/Software%20user%20guides/AEDAT_file_formats.md#aedat-40) | `output file my_file.aedat4` |
| CSV file | Output to comma-separated-value (CSV) file format | `output file my_file.txt` |
### CLI examples
| 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 output stdout` |
| Stream Prophesee 640x480 (serial Prophesee:hal_plugin_gen31_fx3:00001464) to STDOUT (Note, requires Metavision SDK) | `aestream input output stdout` |
| Read file to remote IP X.X.X.X | `aestream input file example/davis.aedat4 output udp X.X.X.X` |
## Custom installation (C++)
AEStream requires [libtorch](https://pytorch.org/cppdocs/installing.html). [Metavision SDK](https://docs.prophesee.ai/stable/metavision_sdk/index.html) and [libcaer](https://github.com/inivation/libcaer) are optional dependencies, but are needed for connecting to Prophesee and Inivation cameras respectively.
AEStream is based on [C++20](https://en.cppreference.com/w/cpp/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 ..`
### Inivation cameras
For [Inivation](https://inivation.com/) cameras, the [libcaer](https://gitlab.com/inivation/dv/libcaer/) library needs to be available, either by a `-DCMAKE_PREFIX_PATH` flag to `cmake` or included in the `PATH` environmental variable.
For examble: `cmake -GNinja -DCMAKE_PREFIX_PATH=/path/to/libcaer`.
Inivation made the library available for most operating systems, but you may have to build it yourself.
### Prophesee cameras
For [Prophesee](https://www.prophesee.ai/) cameras, a version of the [Metavision SDK](https://www.prophesee.ai/metavision-intelligence/) needs to be present.
The open-source version the SDK `openeb` is available with installation instructions at https://github.com/prophesee-ai/openeb.
Using `openeb`, it should be sufficient to install it using `cmake && make && make install` to put it in your path.
Otherwise, you can point to it using the `-DCMAKE_PREFIX_PATH` option in `cmake`.
## Acknowledgments
AEStream is created by
* [Jens E. Pedersen](https://www.kth.se/profile/jeped) (@GitHub [jegp](https://github.com/jegp/)), doctoral student at KTH Royal Institute of Technology, Sweden.
* [Christian Pehle](https://www.kip.uni-heidelberg.de/people/10110) (@GitHub [cpehle](https://github.com/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](https://github.com/PMMon) for interfacing with Metavision SDK and preliminary network code.
## Citation
Please cite `aestream` if you use it in your work:
```bibtex
@software{aestream2022,
author = {Pedersen, Jens Egholm and
Pehle, Christian-Gernot},
title = {AEStream - Address Event Streaming library},
month = {August},
year = 2022,
publisher = {Zenodo},
version = {0.4.0},
doi = {10.5281/zenodo.6322829},
url = {https://doi.org/10.5281/zenodo.6322829}
}
```
زبان مورد نیاز
| مقدار | نام |
|---|---|
| >=3.7 | Python |
نحوه نصب
نصب پکیج whl aestream-0.4.0:
pip install aestream-0.4.0.whl
نصب پکیج tar.gz aestream-0.4.0:
pip install aestream-0.4.0.tar.gz