pytorch-auto-drive
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Question about the existence of lanes in tusimple and culane dataset
The original dataset just supplies the coordinates of lane points. I wonder how we can determine which lane exists. I currently focus on another dataset which just have lane points info. Maybe I should relabel the existence info by myself or is there an another method to quickly identify the which lane existence and add the info into the train.txt?
@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).
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!
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.
@voldemortX Hi, you mean we don't use lane existence label in train.txt (e.g. 1111) except segmentation-based model? :0
@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.
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?