taskgrouping no training instances

Trying to run the command python3 train_taskonomy.py -d=/taskonomy-sample-model-1-master/ -a=xception_taskonomy_new -j 4 -b 96 -lr=.1 --fp16 -sbn --tasks=dnerac -r

but found 0 training instances.

Kindly help me out

Oct 11 '22 05:10 umkhanqta

How is your data arranged? The data must be aranged in inputs:
root/rgb/building/point_x_view_x.png labels: root/task/building/point_x_view_x.png

Oct 11 '22 08:10 tstandley

The data is arranged as following image:

I did not find the "task" folder

Can you send the latest/correct dataset link?

Oct 11 '22 08:10 umkhanqta

There is no download link. You must organize the data yourself. The code was written when the data was laid out differently. If you make a script to do it, would you mind sharing?

There is no folder with the name "task". That referred to the name of the task (for example, normals)

Oct 11 '22 16:10 tstandley

so I need to add a "building" folder and put "rgb" in that. Also rename all the files and remove "_domain_rgb"?

Oct 12 '22 02:10 umkhanqta

Sorry, I don't know how the data you have is organized. I downloaded the dataset years ago and they've since changed it.

Oct 12 '22 02:10 tstandley

OK thanks for the help

Oct 12 '22 02:10 umkhanqta

All the paths are correct but this section is not running. because "building" is not in the "model_whitelist" any suggestion?

Oct 12 '22 07:10 umkhanqta

My guess is that I wasn't clear before that "building" isn't the string literal 'bulding', but the actual building name of the model. Each image comes from a 3d model of a building. There are about 400 buildings IIRC. Each building has a name. So the data needs to be laid out such that the highest directory is the one that contains all the tasks. Within each task directory is a directory for each building, and within each of those is a bunch of views. So for example, one file is located at: "/taskonomy_data/normal/carpio/point_52_view_5.png"

Here "carpio" is the name of the building.

Oct 12 '22 08:10 tstandley