This is the official implementation code of the paper "Transformer Generates Conditional Convolution Kernels For End-to-End Lane Detection"
Statement: This code is based on CondLaneNet.(Link: https://arxiv.org/abs/2105.05003)
This implementation is based on mmdetection(v2.0.0). Please refer to install.md for installation.
We conducted experiments on CurveLanes, CULane and TuSimple. Please refer to dataset.md for installation.
CurveLanes 1 Edit the "data_root" in the config file to your Curvelanes dataset path. For example, for the small version, open "configs/curvelanes/curvelanes_small_test.py" and set "data_root" to "[your-data-path]/curvelanes".
2 run the test script
cd [project-root]
python tools/condlanenet/curvelanes/test_curvelanes.py configs/condlanenet/curvelanes/curvelanes_small_test.py [model-path] --evaluateIf "--evaluate" is added, the evaluation results will be printed. If you want to save the visualization results, you can add "--show" and add "--show_dst" to specify the save path.
CULane
1 Edit the "data_root" in the config file to your CULane dataset path. For example,for the small version, you should open "configs/culane/culane_small_test.py" and set the "data_root" to "[your-data-path]/culane".
2 run the test script
cd [project-root]
python tools/condlanenet/culane/test_culane.py configs/condlanenet/culane/culane_small_test.py [model-path]- you can add "--show" and add "--show_dst" to specify the save path.
- you can add "--results_dst" to specify the result saving path.
3 We use the official evaluation tools of SCNN to evaluate the results.
TuSimple
1 Edit the "data_root" in the config file to your TuSimple dataset path. For example,for the small version, you should open "configs/tusimple/tusimple_small_test.py" and set the "data_root" to "[your-data-path]/tuSimple".
2 run the test script
cd [project-root]
python tools/condlanenet/tusimple/test_tusimple.py configs/condlanenet/tusimple/tusimple_small_test.py [model-path]- you can add "--show" and add "--show_dst" to specify the save path.
- you can add "--results_dst" to specify the result saving path.
3 We use the official evaluation tools of TuSimple to evaluate the results.
Speed Test
cd [project-root]
python tools/condlanenet/speed_test.py configs/condlanenet/culane/culane_small_test.py [model-path]For example, train CULane using 4 gpus:
cd [project-root]
CUDA_VISIBLE_DEVICES=0,1,2,3 PORT=29001 tools/dist_train.sh configs/condlanenet/culane/culane_small_train.py 4 --no-validate If you find this article very helpful in your research, or if you wish to have a reference when using our results, please cite the following papers: