Evaluation error: ERROR: method monoloco_pp at cluster 3 is empty, ZeroDivisionError: division by zero

[wyuzh]

Hi!

After I train the MonoLoco++ by following cmd:

python3 -m monoloco.run train \
    --joints data/arrays/joints-kitti-mono-210422-1600.json \
    --monocular

Then, I evaluate the model with following cmd:

python3 -m monoloco.run eval \
    --model data/outputs/monoloco_pp-240918-1743.pkl \
    --dir_ann /xxx/monoloco/data/kitti/keypoints2 \
    --generate \
    --save \

The output and error I got is:

Created empty output directory data/kitti/monoloco_pp 

Saved in 1508 txt 4094 annotations. Not found 0 images

Method geometric. No directory found. Skipping it..

Method pose. No directory found. Skipping it..

Method monstereo. No directory found. Skipping it..

Method monopsr. No directory found. Skipping it..

Method monodis. No directory found. Skipping it..

Method psf. No directory found. Skipping it..

Method e2e. No directory found. Skipping it..

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ERROR: method monoloco_pp at cluster 3 is empty
----------------------------------------------------------------------------------------------------

Traceback (most recent call last):
  File "/home/xxx/anaconda3/envs/monoloco/lib/python3.8/runpy.py", line 194, in _run_module_as_main
    return _run_code(code, main_globals, None,
  File "/home/xxx/anaconda3/envs/monoloco/lib/python3.8/runpy.py", line 87, in _run_code
    exec(code, run_globals)
  File "/home/xxx/work/monoloco/monoloco/run.py", line 218, in <module>
    main()
  File "/home/xxx/work/monoloco/monoloco/run.py", line 202, in main
    kitti_eval.run()
  File "/home/xxx/work/monoloco/monoloco/eval/eval_kitti.py", line 142, in run
    get_statistics(self.dic_stats['test'][key][clst],
  File "/home/xxx/work/monoloco/monoloco/eval/eval_kitti.py", line 398, in get_statistics
    dic_stats['mean'] = average(errors)
  File "/home/xxx/work/monoloco/monoloco/utils/misc.py", line 69, in average
    return sum(my_list) / len(my_list)
ZeroDivisionError: division by zero

How to solve the problem? Thank you very much!