ValueError: cannot convert float NaN to integer

[julianmack]

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]

Hi - thanks very much. I've just sent now

[qiaoliang6]

Hi - thanks very much. I've just sent now

I have not received the email yet. The file might exceed the capacity limit of the email. Could you please upload the file one the GoogleDrive or OneDrive and share with the link?

[julianmack]

I have not received the email yet.

Hi @qiaoliang6 that's strange. I sent by WeTranfer to [email protected] but the link expires tomorrow - perhaps it went into junk. In any case - I've sent again just now by sharepoint. Thanks again!

[julianmack]

Hi - thanks again for your help. The WeTransfer link is now dead but the Sharepoint should still work - let me know if you had trouble accessing and I will send via another method

[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:

{"pdf/RCL/2017/page_60_95895.png": {"height": 888, "width": 2065, "content_ann": {"bboxes": [[], [1195, 11, 1529, 43], [], [761, 177, 832, 209], [1013, 116, 1146, 209], [1325, 116, 1399, 209], [1608, 116, 1682, 209], [1855, 116, 2002, 209], [0, 233, 337, 273], [], [], [], [], [], [24, 292, 497, 334], [663, 293, 914, 334], [946, 293, 1197, 334], [1229, 293, 1480, 334], [1512, 293, 1763, 334], [1795, 293, 2046, 334], [24, 353, 475, 394], [752, 354, 914, 394], [1066, 354, 1197, 394], [1349, 354, 1480, 394], [1631, 354, 1763, 394], [1915, 354, 2046, 394], [24, 414, 147, 455], [783, 415, 914, 455], [1066, 415, 1197, 455], [1349, 415, 1480, 455], [1631, 415, 1763, 455], [1915, 415, 2046, 455], [0, 475, 326, 516], [915, 512, 917, 516], [], [], [], [], [24, 535, 472, 576], [732, 536, 914, 576], [1036, 536, 1197, 576], [1319, 536, 1480, 576], [1601, 536, 1763, 576], [1885, 536, 2046, 576], [0, 596, 337, 637], [915, 634, 917, 638], [], [], [], [], [24, 656, 497, 697], [752, 657, 914, 697], [1036, 657, 1197, 697], [1319, 657, 1480, 697], [1601, 657, 1763, 697], [1885, 657, 2046, 697], [24, 717, 452, 758], [803, 718, 914, 758], [1106, 718, 1197, 758], [1389, 718, 1480, 758], [1672, 718, 1763, 758], [1935, 718, 2046, 758], [24, 777, 147, 819], [803, 778, 914, 819], [1106, 778, 1197, 819], [1370, 778, 1480, 819], [1672, 778, 1763, 819], [2006, 778, 2046, 819], [0, 839, 83, 879], [663, 839, 914, 879], [946, 839, 1197, 879], [1229, 839, 1480, 879], [1512, 839, 1763, 879], [1795, 839, 2046, 879]], "texts": ["", "Payments due by period", "", "Total", "Less than 1 year", "1-3 years", "3-5 years", "More than 5 years", "Operating Activities:", "", "", "", "", "", "Operating lease obligations(1)", "$241,468", "$29,420", "$44,191", "$22,644", "$145,213", "Interest on long-term debt(2)", "1,275,346", "250,600", "415,000", "292,665", "317,081", "Other(3)", "879,206", "214,444", "282,570", "150,003", "232,189", "Investing Activities:", "0", "", "", "", "", "Ship purchase obligations(4)", "10,888,494", "2,368,806", "3,063,165", "4,089,153", "1,367,370", "Financing Activities:", "0", "", "", "", "", "Long-term debt obligations(5)", "7,506,312", "1,185,038", "2,047,882", "2,012,922", "2,260,470", "Capital lease obligations(6)", "33,139", "3,476", "7,210", "8,395", "14,058", "Other(7)", "21,552", "8,868", "11,217", "1,467", "\u2014", "Total", "$20,845,517", "$4,060,652", "$5,871,235", "$6,577,249", "$4,336,381"], "texts_tokens": [[], ["P", "a", "y", "m", "e", "n", "t", "s", " ", "d", "u", "e", " ", "b", "y", " ", "p", "e", "r", "i", "o", "d"], [], ["T", "o", "t", "a", "l"], ["L", "e", "s", "s", " ", "t", "h", "a", "n", " ", "1", " ", "y", "e", "a", "r"], ["1", "-", "3", " ", "y", "e", "a", "r", "s"], ["3", "-", "5", " ", "y", "e", "a", "r", "s"], ["M", "o", "r", "e", " ", "t", "h", "a", "n", " ", "5", " ", "y", "e", "a", "r", "s"], ["O", "p", "e", "r", "a", "t", "i", "n", "g", " ", "A", "c", "t", "i", "v", "i", "t", "i", "e", "s", ":"], [], [], [], [], [], ["O", "p", "e", "r", "a", "t", "i", "n", "g", " ", "l", "e", "a", "s", "e", " ", "o", "b", "l", "i", "g", "a", "t", "i", "o", "n", "s", "<sup>", "(", "1", ")", "</sup>"], ["$", "2", "4", "1", ",", "4", "6", "8"], ["$", "2", "9", ",", "4", "2", "0"], ["$", "4", "4", ",", "1", "9", "1"], ["$", "2", "2", ",", "6", "4", "4"], ["$", "1", "4", "5", ",", "2", "1", "3"], ["I", "n", "t", "e", "r", "e", "s", "t", " ", "o", "n", " ", "l", "o", "n", "g", "-", "t", "e", "r", "m", " ", "d", "e", "b", "t", "<sup>", "(", "2", ")", "</sup>"], ["1", ",", "2", "7", "5", ",", "3", "4", "6"], ["2", "5", "0", ",", "6", "0", "0"], ["4", "1", "5", ",", "0", "0", "0"], ["2", "9", "2", ",", "6", "6", "5"], ["3", "1", "7", ",", "0", "8", "1"], ["O", "t", "h", "e", "r", "<sup>", "(", "3", ")", "</sup>"], ["8", "7", "9", ",", "2", "0", "6"], ["2", "1", "4", ",", "4", "4", "4"], ["2", "8", "2", ",", "5", "7", "0"], ["1", "5", "0", ",", "0", "0", "3"], ["2", "3", "2", ",", "1", "8", "9"], ["I", "n", "v", "e", "s", "t", "i", "n", "g", " ", "A", "c", "t", "i", "v", "i", "t", "i", "e", "s", ":"], ["0"], [], [], [], [], ["S", "h", "i", "p", " ", "p", "u", "r", "c", "h", "a", "s", "e", " ", "o", "b", "l", "i", "g", "a", "t", "i", "o", "n", "s", "<sup>", "(", "4", ")", "</sup>"], ["1", "0", ",", "8", "8", "8", ",", "4", "9", "4"], ["2", ",", "3", "6", "8", ",", "8", "0", "6"], ["3", ",", "0", "6", "3", ",", "1", "6", "5"], ["4", ",", "0", "8", "9", ",", "1", "5", "3"], ["1", ",", "3", "6", "7", ",", "3", "7", "0"], ["F", "i", "n", "a", "n", "c", "i", "n", "g", " ", "A", "c", "t", "i", "v", "i", "t", "i", "e", "s", ":"], ["0"], [], [], [], [], ["L", "o", "n", "g", "-", "t", "e", "r", "m", " ", "d", "e", "b", "t", " ", "o", "b", "l", "i", "g", "a", "t", "i", "o", "n", "s", "<sup>", "(", "5", ")", "</sup>"], ["7", ",", "5", "0", "6", ",", "3", "1", "2"], ["1", ",", "1", "8", "5", ",", "0", "3", "8"], ["2", ",", "0", "4", "7", ",", "8", "8", "2"], ["2", ",", "0", "1", "2", ",", "9", "2", "2"], ["2", ",", "2", "6", "0", ",", "4", "7", "0"], ["C", "a", "p", "i", "t", "a", "l", " ", "l", "e", "a", "s", "e", " ", "o", "b", "l", "i", "g", "a", "t", "i", "o", "n", "s", "<sup>", "(", "6", ")", "</sup>"], ["3", "3", ",", "1", "3", "9"], ["3", ",", "4", "7", "6"], ["7", ",", "2", "1", "0"], ["8", ",", "3", "9", "5"], ["1", "4", ",", "0", "5", "8"], ["O", "t", "h", "e", "r", "<sup>", "(", "7", ")", "</sup>"], ["2", "1", ",", "5", "5", "2"], ["8", ",", "8", "6", "8"], ["1", "1", ",", "2", "1", "7"], ["1", ",", "4", "6", "7"], ["\u2014"], ["T", "o", "t", "a", "l"], ["$", "2", "0", ",", "8", "4", "5", ",", "5", "1", "7"], ["$", "4", ",", "0", "6", "0", ",", "6", "5", "2"], ["$", "5", ",", "8", "7", "1", ",", "2", "3", "5"], ["$", "6", ",", "5", "7", "7", ",", "2", "4", "9"], ["$", "4", ",", "3", "3", "6", ",", "3", "8", "1"]], "cells": [[0, 0, 0, 0], [0, 1, 0, 5], [1, 0, 1, 0], [1, 1, 1, 1], [1, 2, 1, 2], [1, 3, 1, 3], [1, 4, 1, 4], [1, 5, 1, 5], [2, 0, 2, 0], [2, 1, 2, 1], [2, 2, 2, 2], [2, 3, 2, 3], [2, 4, 2, 4], [2, 5, 2, 5], [3, 0, 3, 0], [3, 1, 3, 1], [3, 2, 3, 2], [3, 3, 3, 3], [3, 4, 3, 4], [3, 5, 3, 5], [4, 0, 4, 0], [4, 1, 4, 1], [4, 2, 4, 2], [4, 3, 4, 3], [4, 4, 4, 4], [4, 5, 4, 5], [5, 0, 5, 0], [5, 1, 5, 1], [5, 2, 5, 2], [5, 3, 5, 3], [5, 4, 5, 4], [5, 5, 5, 5], [6, 0, 6, 0], [6, 1, 6, 1], [6, 2, 6, 2], [6, 3, 6, 3], [6, 4, 6, 4], [6, 5, 6, 5], [7, 0, 7, 0], [7, 1, 7, 1], [7, 2, 7, 2], [7, 3, 7, 3], [7, 4, 7, 4], [7, 5, 7, 5], [8, 0, 8, 0], [8, 1, 8, 1], [8, 2, 8, 2], [8, 3, 8, 3], [8, 4, 8, 4], [8, 5, 8, 5], [9, 0, 9, 0], [9, 1, 9, 1], [9, 2, 9, 2], [9, 3, 9, 3], [9, 4, 9, 4], [9, 5, 9, 5], [10, 0, 10, 0], [10, 1, 10, 1], [10, 2, 10, 2], [10, 3, 10, 3], [10, 4, 10, 4], [10, 5, 10, 5], [11, 0, 11, 0], [11, 1, 11, 1], [11, 2, 11, 2], [11, 3, 11, 3], [11, 4, 11, 4], [11, 5, 11, 5], [12, 0, 12, 0], [12, 1, 12, 1], [12, 2, 12, 2], [12, 3, 12, 3], [12, 4, 12, 4], [12, 5, 12, 5]], "labels": [[1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1], [1]]}}}

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