In Class-PointHead: “During inference, subdivision uses N=8096” Why is 8096？

[JintuZheng]

Thanks for your contribution.
Here are the code-comments in pointrend.py class: PointHead-inference:
"""
During inference, subdivision uses N=8096
(i.e., the number of points in the stride 16 map of a 1024×2048 image)
"""
i found this N=8096 in paper: "5.Experiments: SemanticSegmentation" and as same as your code variable N. I don't understand how to get this N. Is it related to the size of the input image？or maybe something else?

[kelisiya]

Thanks for your contribution.
Here are the code-comments in pointrend.py class: PointHead-inference:
"""
During inference, subdivision uses N=8096
(i.e., the number of points in the stride 16 map of a 1024×2048 image)
"""
i found this N=8096 in paper: "5.Experiments: SemanticSegmentation" and as same as your code variable N. I don't understand how to get this N. Is it related to the size of the input image？or maybe something else?

How to train the code for Segmentation use cityscape ? The error is Dataset not found or incomplete. Please make sure all required folders for the specified "split" and "mode" are inside the "root" directory

[Gancheekim]

Thanks for your contribution. Here are the code-comments in pointrend.py class: PointHead-inference: """ During inference, subdivision uses N=8096 (i.e., the number of points in the stride 16 map of a 1024×2048 image) """ i found this N=8096 in paper: "5.Experiments: SemanticSegmentation" and as same as your code variable N. I don't understand how to get this N. Is it related to the size of the input image？or maybe something else?

hello, this is because 1024 * 2048 / (16 * 16) = 8096. Just think of doing sampling on a 2D image with the interval of 16, in both width and height.