Awesome
Lane Segmentation
:rocket: 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
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