EvLSD-IED: Event-Based Line Segment Detection with Image-to-Event Distillation

This repository contains the official PyTorch implementation of the paper: “EvLSD-IED: Event-Based Line Segment Detection with Image-to-Event Distillation”

Table of Contents

• Installation
• Testing Pre-trained Models
• Downloading the Dataset
• Distillation

Installation

We have trained and tested our models on CUDA 11.1, Python 3.8.0, torch 1.10.1.

For ease of reproducibility, you are suggested to install miniconda (or anaconda if you prefer) before following executing the following commands.

git clone https://github.com/Qiuben/EvLSD-IED

cd EvLSD-IED

pip install -r requirements.txt

Testing Pre-trained Models

You can download the pretrained model on E-wirferame from OneDrive.

Downloading the Dataset

You can download the synthetic dataset E-wireframe as well as the real-scene datset RE-LSD from OneDrive. You can directly download the EST representation or download the raw event data and convert it to frame representations using the event2frame.py

Distillation

Step 1 : training the teacher

python train.py -m image -d E-wireframe

Step 2 : training the student

python train_IED.py -m event -d E-wireframe