ValueError: cannot convert float NaN to integer

Thanks for this open source contribution!

I am seeing the same problem as in issue #37 - although I am using the fix for that issue (commit c85ca3f5b1c00b785ca346882a8983d57287d75f to generate my datalist)

Specifically, when I train on my own data (open source dataset FinTabNet) I see the following errors:

/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/core/mask/lp_mask_target.py:55: RuntimeWarning: Mean of empty slice.
  middle_x, middle_y = round(np.where(box_text == 1)[1].mean()), round(np.where(box_text == 1)[0].mean())
/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/core/mask/lp_mask_target.py:55: RuntimeWarning: Mean of empty slice.
Traceback (most recent call last):
  File "acx-tsr/scripts/train_lgpma.py", line 316, in <module>
    main()
  File "acx-tsr/scripts/train_lgpma.py", line 311, in main
    meta=meta,
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_common/apis/train.py", line 174, in train_model
  middle_x, middle_y = round(np.where(box_text == 1)[1].mean()), round(np.where(box_text == 1)[0].mean())
    runner.run(data_loaders, cfg.workflow)
  File "/home/usr/mmcv/mmcv/runner/epoch_based_runner.py", line 125, in run
    epoch_runner(data_loaders[i], **kwargs)
  File "/home/usr/mmcv/mmcv/runner/epoch_based_runner.py", line 50, in train
    self.run_iter(data_batch, train_mode=True, **kwargs)
  File "/home/usr/mmcv/mmcv/runner/epoch_based_runner.py", line 30, in run_iter
    **kwargs)
  File "/home/usr/mmcv/mmcv/parallel/data_parallel.py", line 67, in train_step
    return self.module.train_step(*inputs[0], **kwargs[0])
  File "/home/usr/mmdetection/mmdet/models/detectors/base.py", line 247, in train_step
    losses = self(**data)
  File "/opt/conda/lib/python3.6/site-packages/torch/nn/modules/module.py", line 918, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/home/usr/mmcv/mmcv/runner/fp16_utils.py", line 124, in new_func
    output = old_func(*new_args, **new_kwargs)
  File "/home/usr/mmdetection/mmdet/models/detectors/base.py", line 181, in forward
    return self.forward_train(img, img_metas, **kwargs)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/models/detectors/lgpma.py", line 132, in forward_train
    **kwargs)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/models/roi_heads/lgpma_roi_head.py", line 84, in forward_train
    gt_masks, img_metas, gt_bboxes)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/models/roi_heads/lgpma_roi_head.py", line 131, in _mask_forward_train
    self.train_cfg, gt_bboxes)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/models/roi_heads/mask_heads/lpma_mask_head.py", line 105, in get_targets
    gt_lpma_hor, gt_lpma_ver = get_lpmasks(gt_masks, gt_bboxes)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/core/mask/lp_mask_target.py", line 30, in get_lpmasks
    gt_masks_temp = list(gt_masks_temp)
  File "/home/usr/DAVAR-Lab-OCR/davarocr/davar_table/core/mask/lp_mask_target.py", line 55, in get_lpmask_single
    middle_x, middle_y = round(np.where(box_text == 1)[1].mean()), round(np.where(box_text == 1)[0].mean())
  ValueError: cannot convert float NaN to integer

Any help would be very appreciated!

[qiaoliang6]

Could you provide the datalist you generated (you may send it by email)?

[julianmack]

To update on this if anyone else is having this issue I added a hack to fix it here: https://github.com/AccelexTechnology/DAVAR-Lab-OCR/commit/ce6d9ce766573362e3354ece5718ca722feaa4c4

^ this was only appropriate as it affected a small proportion of my dataset (~1/5000 samples) - it will give bad results otherwise as I am setting the index to an arbitrary (and hence likely incorrect) non-NaN value

I spent a long time looking at one of the samples from FinTabNet that was causing the issue here:

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But couldn’t see anything wrong that would allow me to programatically filter the bad samples out of the dataset. I think the issue arose in the DavarLoadAnnotations._poly2mask function but didn’t debug further than this