SenZHANG-GitHub / ekf-imu-depth

[ECCV 2022] Towards Scale-Aware, Robust, and Generalizable Unsupervised Monocular Depth Estimation by Integrating IMU Motion Dynamics
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organization of datasets #6

Open scarLiu opened 1 year ago

scarLiu commented 1 year ago

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~

scarLiu commented 1 year ago

and how can I use the pertained model in the process of evolution? 😊

SenZHANG-GitHub commented 1 year ago

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~

I use the original format of KITTI except for the matched IMU files. The details can be found in https://journals.sagepub.com/doi/pdf/10.1177/0278364913491297

SenZHANG-GitHub commented 1 year ago

and how can I use the pertained model in the process of evolution? blush

We can use the argument --load_weights_folder to load the pretrained model : )

scarLiu commented 1 year ago

and how can I use the pertained model in the process of evolution? blush

We can use the argument --load_weights_folder to load the pretrained model : )

Thank you for reply! And now I am troubled by a problem, that is, when the imu between two img frames is missing, how do you process the aligned data and get the predicted poses?

SenZHANG-GitHub commented 1 year ago

and how can I use the pertained model in the process of evolution? blush

We can use the argument --load_weights_folder to load the pretrained model : )

Thank you for reply! And now I am troubled by a problem, that is, when the imu between two img frames is missing, how do you process the aligned data and get the predicted poses?

Hi @scarLiu , I simply mark it as 'nan' in the matched imu files, and ignore those pairs with missing imu during training. Please note that we do not require imu during inference : )