Question about the existence of lanes in tusimple and culane dataset about pytorch-auto-drive

[voldemortX]

@solidexu Existing datasets use line slope to determine existence. Note that existence is only needed for multi-class segmentation approaches (their seg label is also generated based on slope), the original script is cpp in https://github.com/XingangPan/seg_label_generate . You can refer to #40 for more discussions (Python scripts and such).

[solidexu]

Thank you ~ I just found the C++ script from XingangPan. Using slope to determine the existence of lane is definitely a genius idea. But I am not sure if it works well with CurveLanes Dataset. Anyway, I will try it. Thanks again!

[voldemortX]

But I am not sure if it works well with CurveLanes Dataset.

We also have problem doing this for CurveLanes, please share to us if you have a solution for this kind of dataset.

[daeunni]

@voldemortX Hi, you mean we don't use lane existence label in train.txt (e.g. 1111) except segmentation-based model? :0

[voldemortX]

@voldemortX Hi, you mean we don't use lane existence label in train.txt (e.g. 1111) except segmentation-based model? :0

Yes. It is only meant for semantic segmentation.

[Albertchamberlain]

Thank you ~ I just found the C++ script from XingangPan. Using slope to determine the existence of lane is definitely a genius idea. But I am not sure if it works well with CurveLanes Dataset. Anyway, I will try it. Thanks again!
@solidexu
Hi，Does it work on the Curvelanes dataset?