Lane Segmentation

🚀 This project is built based on InSPyReNet (ACCV 2022). Please refer to the original repository for training and other details.

1. Create environment

Create conda environment with following command conda create -y -n lane python
Activate environment with following command conda activate lane
Install requirements with following command pip install -r requirements.txt

2. Preparation

Pre-trained Checkpoint

Download ImageNet pre-trained checkpoint for backbone network from Link
Download checkpoint from Link
Move file as follows ./snapshots/HighwayLane/latest.pth. Create folder if needed.

Dataset

Train
Test

3. Inference

Prepare your image folder
python run/Inference.py --source [IMAGE_FOLDER_DIR]

Performance - KAIST Highway Dataset

Maximum F1 Score: 94.8
Maximum IoU: 88.5
Throughput: 43 fps
GPU Mem Usage: 1.5 GB