event-camera-drivers 0.0.3

Python event camera drivers for Inivation and AEStream

C++/Python event camera drivers

C++ drivers wrapped in a Python library for interfacing with event-based cameras, supporting both Prophesee and iniVation devices.

Features

• Support for Prophesee event-based cameras via OpenEB
• Support for iniVation DVS cameras via libcaer
• Python bindings using nanobind
• Cross-platform support (Linux, macOS, Windows)

Installation

From PyPI

... Coming soon

From Source

Using Nix (recommended)

If you have Nix installed with flakes enabled:

# Enter development environment
nix develop

# Install in development mode
pip install -e .

Manual Installation

Prerequisites:

• CMake (3.16 or higher)
• C++ compiler with C++17 support
• Python 3.9 or higher
• OpenEB 5.0.0
• libcaer

1. Clone the repository:

git clone https://github.com/aestream/event-camera-drivers
cd event-camera-drivers

2. Create and activate a virtual environment:

python -m venv .venv
source .venv/bin/activate  # On Windows: .venv\Scripts\activate

3. Install development dependencies:

pip install scikit-build-core pytest build nanobind

4. Install in development mode:

pip install -e .

Usage

import event_camera_drivers as evd

camera = evd.InivationCamera()
for packet in camera:
    print(packet)

Or, in conjuction with Faery (read more in the Faery documentation):

import faery

faery.events_stream_from_inivation_camera()
  ...

Development

Setup Development Environment

1. Install Nix package manager (recommended):

curl -L https://nixos.org/nix/install | sh

2. Enable Nix flakes (if not already enabled).

3. Enter development environment:

nix develop

Building Wheels

pip install build
python -m build

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

This project is licensed under LGPLv3 - see the LICENSE file for details.

Acknowledgments

• OpenEB - Prophesee's Open Event-Based Vision SDK
• libcaer - Minimal C library to access neuromorphic sensors