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Where do the values fov_up=3, fov_down=-25 and img_means and img_stds in arch_cfg.yaml file come from?
Since I currently have a model applied to the SemanticKitti dataset that uses these values and now want to apply it to another dataset, I am trying to figure out if I can reuse these values.
Are these values only dependent on the scanner that is used? So if a scanner of the same type (here: Velodyne HDL64) was used, are the above values also the same or what do these values depend on?
Thanks a lot!
The text was updated successfully, but these errors were encountered:
The fov_up and fov_down are sensor-specific and are the field of view of the Velodyne HDL-64E. The img_mean and img_stds are computed from the range images. As noted in #43, these values are computed on the training data. However, it's somehow lost how these values are exactly are computed.
And I guess this question is more related to lidar-bonnetal?
Thanks for the quick reply, helps me a lot! Yes that's right, this issue is more related to lidar-bonnetal.
Does signal mean the remission of a point or what does the value for signal in img_means and img_std stand for?
Where do the values fov_up=3, fov_down=-25 and img_means and img_stds in arch_cfg.yaml file come from?
Since I currently have a model applied to the SemanticKitti dataset that uses these values and now want to apply it to another dataset, I am trying to figure out if I can reuse these values.
Are these values only dependent on the scanner that is used? So if a scanner of the same type (here: Velodyne HDL64) was used, are the above values also the same or what do these values depend on?
Thanks a lot!
The text was updated successfully, but these errors were encountered: