This repo contains various general tools for event camera data processing as well as many general modules or models for deep learning on event camera, especially for graph-based methods or video reconstruction from events.
Now we have implemented:
- The Event2Graph Dataset from the paper Graph-Based Object Classification for Neuromorphic Vision Sensing, based on the code.
- The FireNet from the paper Fast Image Reconstruction with an Event Camera, based on the code.
- The event data voxel grid representations from the paper High Speed and High Dynamic Range Video with an Event Camera, based on the code.
- torch >= 1.4.0
- torchvision >= 0.5.0
- torch_geometric >= 1.5.0
- opencv-python
- scipy
a. Install PyTorch 1.5 and torchvision 0.6 following the official instructions.
b. Install Pytorch Geometric 1.5 following the official instructions.
c. Clone the repository.
git clone https://github.com/Flawless1202/tjevents.git
d. Install the other requirements.
pip install -r requirements.txt
d. Install.
python(3) setup.py install # add --user if you want to install it locally
# or "pip install ."
a. Prepare the dataset: Download the ASL-Dataset
and unzip them all to data/NVS2Graph/raw
.
b. Run the train example with spcific config
python examples/train_e2g.py --load_config ./config/dgcnn.yaml