Augmented (albumentations) BBox outside the range [0.0, 1.0]

🐛 Bug

Describe the bug The error occur during training in this Plantdoc notebook: learn.fine_tune(20, 0.012, freeze_epochs=3)

It occurs in:

File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 330, in check_bbox
    "to be in the range [0.0, 1.0], got {value}.".format(bbox=bbox, name=name, value=value)
ValueError: Expected x_max for bbox (0.00038580246913580245, 0.022119341563786008, 1.4683641975308641, 0.625, 0) to be in the range [0.0, 1.0], got 1.4683641975308641.

Error stack:

ValueError                                Traceback (most recent call last)
<ipython-input-47-2d489cf4c395> in <module>()
      1 from fastai.callback.tracker import SaveModelCallback
----> 2 learn.fine_tune(20, 0.012, freeze_epochs=3)

17 frames
/usr/local/lib/python3.6/dist-packages/fastcore/logargs.py in _f(*args, **kwargs)
     54         init_args.update(log)
     55         setattr(inst, 'init_args', init_args)
---> 56         return inst if to_return else f(*args, **kwargs)
     57     return _f

/usr/local/lib/python3.6/dist-packages/fastai/callback/schedule.py in fine_tune(self, epochs, base_lr, freeze_epochs, lr_mult, pct_start, div, **kwargs)
    159     "Fine tune with `freeze` for `freeze_epochs` then with `unfreeze` from `epochs` using discriminative LR"
    160     self.freeze()
--> 161     self.fit_one_cycle(freeze_epochs, slice(base_lr), pct_start=0.99, **kwargs)
    162     base_lr /= 2
    163     self.unfreeze()

/usr/local/lib/python3.6/dist-packages/fastcore/logargs.py in _f(*args, **kwargs)
     54         init_args.update(log)
     55         setattr(inst, 'init_args', init_args)
---> 56         return inst if to_return else f(*args, **kwargs)
     57     return _f

/usr/local/lib/python3.6/dist-packages/fastai/callback/schedule.py in fit_one_cycle(self, n_epoch, lr_max, div, div_final, pct_start, wd, moms, cbs, reset_opt)
    111     scheds = {'lr': combined_cos(pct_start, lr_max/div, lr_max, lr_max/div_final),
    112               'mom': combined_cos(pct_start, *(self.moms if moms is None else moms))}
--> 113     self.fit(n_epoch, cbs=ParamScheduler(scheds)+L(cbs), reset_opt=reset_opt, wd=wd)
    114 
    115 # Cell

/usr/local/lib/python3.6/dist-packages/fastcore/logargs.py in _f(*args, **kwargs)
     54         init_args.update(log)
     55         setattr(inst, 'init_args', init_args)
---> 56         return inst if to_return else f(*args, **kwargs)
     57     return _f

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in fit(self, n_epoch, lr, wd, cbs, reset_opt)
    205             self.opt.set_hypers(lr=self.lr if lr is None else lr)
    206             self.n_epoch = n_epoch
--> 207             self._with_events(self._do_fit, 'fit', CancelFitException, self._end_cleanup)
    208 
    209     def _end_cleanup(self): self.dl,self.xb,self.yb,self.pred,self.loss = None,(None,),(None,),None,None

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    153 
    154     def _with_events(self, f, event_type, ex, final=noop):
--> 155         try:       self(f'before_{event_type}')       ;f()
    156         except ex: self(f'after_cancel_{event_type}')
    157         finally:   self(f'after_{event_type}')        ;final()

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _do_fit(self)
    195         for epoch in range(self.n_epoch):
    196             self.epoch=epoch
--> 197             self._with_events(self._do_epoch, 'epoch', CancelEpochException)
    198 
    199     @log_args(but='cbs')

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    153 
    154     def _with_events(self, f, event_type, ex, final=noop):
--> 155         try:       self(f'before_{event_type}')       ;f()
    156         except ex: self(f'after_cancel_{event_type}')
    157         finally:   self(f'after_{event_type}')        ;final()

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _do_epoch(self)
    189 
    190     def _do_epoch(self):
--> 191         self._do_epoch_train()
    192         self._do_epoch_validate()
    193 

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _do_epoch_train(self)
    181     def _do_epoch_train(self):
    182         self.dl = self.dls.train
--> 183         self._with_events(self.all_batches, 'train', CancelTrainException)
    184 
    185     def _do_epoch_validate(self, ds_idx=1, dl=None):

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in _with_events(self, f, event_type, ex, final)
    153 
    154     def _with_events(self, f, event_type, ex, final=noop):
--> 155         try:       self(f'before_{event_type}')       ;f()
    156         except ex: self(f'after_cancel_{event_type}')
    157         finally:   self(f'after_{event_type}')        ;final()

/usr/local/lib/python3.6/dist-packages/fastai/learner.py in all_batches(self)
    159     def all_batches(self):
    160         self.n_iter = len(self.dl)
--> 161         for o in enumerate(self.dl): self.one_batch(*o)
    162 
    163     def _do_one_batch(self):

/usr/local/lib/python3.6/dist-packages/fastai/data/load.py in __iter__(self)
    100         self.before_iter()
    101         self.__idxs=self.get_idxs() # called in context of main process (not workers/subprocesses)
--> 102         for b in _loaders[self.fake_l.num_workers==0](self.fake_l):
    103             if self.device is not None: b = to_device(b, self.device)
    104             yield self.after_batch(b)

/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in __next__(self)
    361 
    362     def __next__(self):
--> 363         data = self._next_data()
    364         self._num_yielded += 1
    365         if self._dataset_kind == _DatasetKind.Iterable and \

/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in _next_data(self)
    987             else:
    988                 del self._task_info[idx]
--> 989                 return self._process_data(data)
    990 
    991     def _try_put_index(self):

/usr/local/lib/python3.6/dist-packages/torch/utils/data/dataloader.py in _process_data(self, data)
   1012         self._try_put_index()
   1013         if isinstance(data, ExceptionWrapper):
-> 1014             data.reraise()
   1015         return data
   1016 

/usr/local/lib/python3.6/dist-packages/torch/_utils.py in reraise(self)
    393             # (https://bugs.python.org/issue2651), so we work around it.
    394             msg = KeyErrorMessage(msg)
--> 395         raise self.exc_type(msg)

ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/worker.py", line 185, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.6/dist-packages/torch/utils/data/_utils/fetch.py", line 34, in fetch
    data = next(self.dataset_iter)
  File "/usr/local/lib/python3.6/dist-packages/fastai/data/load.py", line 111, in create_batches
    yield from map(self.do_batch, self.chunkify(res))
  File "/usr/local/lib/python3.6/dist-packages/fastcore/utils.py", line 159, in chunked
    res = list(itertools.islice(it, chunk_sz))
  File "/usr/local/lib/python3.6/dist-packages/fastai/data/load.py", line 124, in do_item
    try: return self.after_item(self.create_item(s))
  File "/usr/local/lib/python3.6/dist-packages/fastai/data/load.py", line 130, in create_item
    def create_item(self, s):  return next(self.it) if s is None else self.dataset[s]
  File "/usr/local/lib/python3.6/dist-packages/icevision/data/dataset.py", line 35, in __getitem__
    data = self.tfm(data)
  File "/usr/local/lib/python3.6/dist-packages/icevision/tfms/transform.py", line 13, in __call__
    tfmed = self.apply(**data)
  File "/usr/local/lib/python3.6/dist-packages/icevision/tfms/albumentations/tfms.py", line 110, in apply
    d = self.tfms(**params)
  File "/usr/local/lib/python3.6/dist-packages/albumentations/core/composition.py", line 180, in __call__
    p.preprocess(data)
  File "/usr/local/lib/python3.6/dist-packages/albumentations/core/utils.py", line 62, in preprocess
    data[data_name] = self.check_and_convert(data[data_name], rows, cols, direction="to")
  File "/usr/local/lib/python3.6/dist-packages/albumentations/core/utils.py", line 70, in check_and_convert
    return self.convert_to_albumentations(data, rows, cols)
  File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 51, in convert_to_albumentations
    return convert_bboxes_to_albumentations(data, self.params.format, rows, cols, check_validity=True)
  File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 303, in convert_bboxes_to_albumentations
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 303, in <listcomp>
    return [convert_bbox_to_albumentations(bbox, source_format, rows, cols, check_validity) for bbox in bboxes]
  File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 251, in convert_bbox_to_albumentations
    check_bbox(bbox)
  File "/usr/local/lib/python3.6/dist-packages/albumentations/augmentations/bbox_utils.py", line 330, in check_bbox
    "to be in the range [0.0, 1.0], got {value}.".format(bbox=bbox, name=name, value=value)
ValueError: Expected x_max for bbox (0.00038580246913580245, 0.022119341563786008, 1.4683641975308641, 0.625, 0) to be in the range [0.0, 1.0], got 1.4683641975308641.

[lgvaz]

Hi @attibalazs, I don’t think the error you’re getting is related to this issue, can you open a separate issue?

why is it looking into “C:\Users\appveyor”

This is not where is looking for the image, but where opencv is installed and the error is being thrown

[FraPochetti]

The only other explanation is if we have a bug there

The code snippet I ran proves the contrary. All records seem fine.

Super weird if albumentations is the root cause.