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Install

  1. Clone the project

    git clone https://github.com/cfzd/Ultra-Fast-Lane-Detection
cd Ultra-Fast-Lane-Detection

  2. Create a conda virtual environment and activate it

    conda create -n lane-det python=3.7 -y
conda activate lane-det

  3. Install dependencies

    # If you dont have pytorch
conda install pytorch torchvision cudatoolkit=10.1 -c pytorch 

pip install -r requirements.txt

  4. Data preparation

    Download CULane and Tusimple. Then extract them to $CULANEROOT and $TUSIMPLEROOT. The directory arrangement of Tusimple should look like:

    $TUSIMPLEROOT
|──clips
|──label_data_0313.json
|──label_data_0531.json
|──label_data_0601.json
|──test_tasks_0627.json
|──test_label.json
|──readme.md

    The directory arrangement of CULane should look like:

    $CULANEROOT
|──driver_100_30frame
|──driver_161_90frame
|──driver_182_30frame
|──driver_193_90frame
|──driver_23_30frame
|──driver_37_30frame
|──laneseg_label_w16
|──list

    For Tusimple, the segmentation annotation is not provided, hence we need to generate segmentation from the json annotation.

    python scripts/convert_tusimple.py --root $TUSIMPLEROOT
# this will generate segmentations and two list files: train_gt.txt and test.txt

  5. Install CULane evaluation tools (Only required for testing).

    If you just want to train a model or make a demo, this tool is not necessary and you can skip this step. If you want to get the evaluation results on CULane, you should install this tool.

    This tools requires OpenCV C++. Please follow here to install OpenCV C++. When you build OpenCV, remove the paths of anaconda from PATH or it will be failed.

    # First you need to install OpenCV C++. 
# After installation, make a soft link of OpenCV include path.

ln -s /usr/local/include/opencv4/opencv2 /usr/local/include/opencv2

    We provide three kinds of complie pipelines to build the evaluation tool of CULane.

    Option 1:

    cd evaluation/culane
make

    Option 2:

    cd evaluation/culane
mkdir build && cd build
cmake ..
make
mv culane_evaluator ../evaluate

    For Windows user:

    mkdir build-vs2017
cd build-vs2017
cmake .. -G "Visual Studio 15 2017 Win64"
cmake --build . --config Release  
# or, open the "xxx.sln" file by Visual Studio and click build button
move culane_evaluator ../evaluate