Comments (4)
In next week. @lunachy
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Thanks!
I have trained a model on the CULane dataset recently, with the same configuration (no additional parameters) the model achieves 65.6 F1-measure. After multiplying all channels by 2, the F1-measure reaches 68.6.
However, I think my evaluation code might have some problems because the original CULane evaluation protocol considers the segmentation to be the input. I directly generate predicted sequences using my own python codes by depending on their Matlab codes as I understand it (which might have some problems).
I will update my codes about CULane in the future, but anyway please feel free to pull requests!
from lstr.
Thanks!
I have trained a model on the CULane dataset recently, with the same configuration (no additional parameters) the model achieves 65.6 F1-measure. After multiplying all channels by 2, the F1-measure reaches 68.6.However, I think my evaluation code might have some problems because the original CULane evaluation protocol considers the segmentation to be the input. I directly generate predicted sequences using my own python codes by depending on their Matlab codes as I understand it (which might have some problems).
I will update my codes about CULane in the future, but anyway please feel free to pull requests!
any plan about pushing CULane dataset‘s work?
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I have uploaded training testing and evaluating codes about culane in the culane branch, please check it!
Now, I will close this issue.
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Related Issues (20)
- ModuleNotFoundError: No module named 'loguru'
- AttributeError: 'NoneType' object has no attribute 'shape'
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- 关于论文的一点小疑惑
- Thank You! HOT 1
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