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ekf-imu-depth's Issues

How to train on custom data

I have RTK data and image data,and I have matched RTK data to the image data。Can I train the network on my custom data。
Wait for your help.

datasets

Hello teacher, do you have any relevant organization methods for datasets? At present, I am facing several problems:

  1. Is the path to the dataset a root path?
  2. Can the organization of the dataset provide relevant examples?
  3. The dataset includes those parts.

Trans_scale_factor in options.py

I have been testing you model some, and I was wondering about this trans_scale_factor which is set to 5.4 by default.

From my understanding, this has to do with the stereo-configuration in KITTI. As such we should not use it when running with mono only? That is: set trans_scale_factor = 1.0 when not training using stereo.
Otherwise the relative motions between images will be wrong. This wouldn't be an issue if we only used the pose-network since it could learn to deal with this scale. However, this scale is also used in the compute_imu_pose_with_inv function, meaning that the acceleration-based translation will be incorrect. (Though this may be somewhat corrected by the velocity network)

Have I understood this correctly? I saw that my predicted depths were surprisingly low before I changed this scale factor to 1.

Data preparation

Thanks for your work!
Using IMU is very instructive for solving the scale problem of monocular depth estimation.

I think providing a detailed description of data preparation can help others better follow your research.

organization of datasets

It is commendable that your work has been very meticulous, but if you can list the organization format of each file in your Kitti dataset, it will be more friendly to beginners~

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