Please update documentation with more details on training the other midas backbones

[MalekWahidi]

I have been trying to train a new ZoeDepth_N model on the NYUv2 dataset with the more efficient DPT_SwinV2_L_384 MiDaS backbone for real-time performance. However, it is not clear from the current documentation about how to properly setup the dataset and config parameters. I have no idea where to find the "shortcuts/datasets/nyu_depth_v2/official_splits/test/". The train_mono script is just printing the config params and does nothing else. What am I missing?

[Shiyao-Xu]

Have the same question here.

[Gilgamesh666666]

me too

[Gilgamesh666666]

I find the solution here https://github.com/cleinc/bts/tree/master#prepare-nyu-depth-v2-test-set. you can follow the instruction to download the NYU mat file and then copy the python file into your own directory and download the split.mat in this github.

[MalekWahidi]

Yes thanks, this worked for me too.

[Shiyao-Xu]

I find the solution here https://github.com/cleinc/bts/tree/master#prepare-nyu-depth-v2-test-set. you can follow the instruction to download the NYU mat file and then copy the python file into your own directory and download the split.mat in this github.

Thanks for sharing! Yet I still got error: only integer scalar arrays can be converted to a scalar index. Seems from h5py. Any idea how to fix that?

[AlexMousaei]

@MalekWahidi I'm new to this what is required to switch the backbone? Given that you've navigated already, I was wondering if you could share some insights or a brief step-by-step guide on how you made the switch? Thank you.

[AlexMousaei]

I find the solution here https://github.com/cleinc/bts/tree/master#prepare-nyu-depth-v2-test-set. you can follow the instruction to download the NYU mat file and then copy the python file into your own directory and download the split.mat in this github.

Thanks for sharing! Yet I still got error: only integer scalar arrays can be converted to a scalar index. Seems from h5py. Any idea how to fix that?

@Shiyao-Xu In "extract_official_train_test_set_from_mat.py" Replace line 87: scenes = [u''.join(chr(c) for c in h5_file[obj_ref]) for obj_ref in h5_file['sceneTypes'][0]] With: scenes = [u''.join(chr(c[0]) for c in h5_file[obj_ref][:]) for obj_ref in h5_file['sceneTypes'][0]]

[baibizhe]

scenes = [u''.join(chr(c[0]) for c in h5_file[obj_ref][:]) for obj_ref in h5_file['sceneTypes'][0]]

Thanks!