Utilities for event-based vision
Project description
EV Utils
EV-utils is a collection of utilities for working event based data inspired by the event_utils library. This library aims at being camera independent (yet also supporting specific camera vendors) with minimal dependencies but also performent. The library is divided into severla modules some of which can be used without installing all the dependencies. These include:
└── augment - Event augmentations
└── dataset - Wrappers for various dataset loaders
└── events
└── io
├── reader
└── writer
└── random
└── torch
└── types
└── vis
├── histogram
└── reconstructor
Installation
From Git
git clone --recurse-submodules git@git.ee.ethz.ch:pbl/research/event-camera/evutils.git
cd evutils
pip install .
pip install -e . # Use this to install an editable version of the package
Quick API overview
augment
Event augmentations
dataset
Wrappers for various dataset loaders
io
The io module provides methods for reading and writing events into various event formats. It provides a simple .read() and .write() interface as well as more advanced interfaces using iterators and slicing.
from evutils.io.reader import EventReader_RAW
ev_file = EventReader_RAW("raw_file.raw", delta_t=10e3)
events = ev_file.read()
utils
Various utility functions
random
Generating random events and adding noise to event recordings
types
This provides several standard types for representing Events in numpy arrays
vis
The vis moduels provides several methods for visualizing the events (for example as histograms), but also provides a streamlined interface for more complex visualization techneques, such as using the E2Vid reconstructor.
You need to download the pretrained weights:
wget "http://rpg.ifi.uzh.ch/data/E2VID/models/E2VID_lightweight.pth.tar" -O models/E2VID_lightweight.pth.tar
from evutils.vis.reconstructor import RPG_Reconstructor
reconstructor = RPG_Reconstructor(1280, 720)
img = reconstructor.gen_frame(events)
Running tests
You can run tests on using the pytest utility:
pytest -s
Acknowledgements
Thanks to all the contributors for supporting this project:
- Elia Franc
- Jakub Mandula
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