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Clone the project
git clone https://github.com/cfzd/Ultra-Fast-Lane-Detection cd Ultra-Fast-Lane-Detection
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Create a conda virtual environment and activate it
conda create -n lane-det python=3.7 -y conda activate lane-det
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Install dependencies
# If you dont have pytorch conda install pytorch torchvision cudatoolkit=10.1 -c pytorch pip install -r requirements.txt
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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
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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