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gyro_std of new dataset #8

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DLuminary opened this issue Jul 4, 2021 · 4 comments
Open

gyro_std of new dataset #8

DLuminary opened this issue Jul 4, 2021 · 4 comments

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@DLuminary
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Hello Brossar and thanks for sharing your work.

I'm trying to use your method with a different dataset. In order to train and test the network - it seems like gyro_std needs to be defined.
How can one obtain the values for some arbitrary dataset?

Thanks again!

@mbrossar
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mbrossar commented Jul 4, 2021 via email

@DLuminary
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DLuminary commented Jul 11, 2021

Thanks for your rapid reply @mbrossar

Some questions regarding the main run file - in dataset_params:

  1. Does N represent approximately the window size? (in your paper it is 448 and it seems like 500 is used in the code)
  2. Do min_train_freq and max_train_freq represent the loss function factors?
  3. When using data with 100Hz measurements instead of 200Hz, would you advise lowering the window size and loss factors? What other changes would you suggest?

Best regards

@RXvo
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RXvo commented Mar 16, 2022

感谢您的快速回复@mbrossar

关于主运行文件的一些问题 - 在 dataset_params 中:

  1. N 是否近似代表窗口大小?(在你的论文中它是 448 并且似乎在代码中使用了 500)
  2. min_train_freq 和 max_train_freq 代表损失函数因子吗?
  3. 当使用 100Hz 测量而不是 200Hz 的数据时,您会建议降低窗口大小和损耗因子吗?您还建议进行哪些其他更改?

最好的祝福

Hello, do you still have the corresponding optimization parameters and data set of this code? The author's links have all failed. Thank you!

@alun9258
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Thanks for your rapid reply @mbrossar

Some questions regarding the main run file - in dataset_params:

  1. Does N represent approximately the window size? (in your paper it is 448 and it seems like 500 is used in the code)
  2. Do min_train_freq and max_train_freq represent the loss function factors?
  3. When using data with 100Hz measurements instead of 200Hz, would you advise lowering the window size and loss factors? What other changes would you suggest?

Best regards

Hello, do you still have the corresponding optimization parameters and data set of this code? The author's links have all failed. Thank you!

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