There’s something really weird going on when I try to create a dataBunch from a single image.
I’m gona post the code and errors in the exactly order their appear:
When i first type data, everything is all right. But after doing
imb, _ = data.one_item(im, detach=False, denorm=False) ; imb I try to get data again, we get an error.
What’s happening? Why imb, _ = data.one_item(im, detach=False, denorm=False) ; imb doesnt work and why it is breaking data?
Thanks
Can you share the full stack trace of the error ?
Sure.
For imb, _ = data.one_item(im, detach=False, denorm=False) ; imb it is:
RuntimeError Traceback (most recent call last)
<ipython-input-16-ff4fc946a627> in <module>
----> 1 imb, _ = data.one_item(im, detach=False, denorm=False) ; imb
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\basic_data.py in one_item(self, item, detach, denorm, cpu)
179 ds = self.single_ds
180 with ds.set_item(item):
--> 181 return self.one_batch(ds_type=DatasetType.Single, detach=detach, denorm=denorm, cpu=cpu)
182
183 def show_batch(self, rows:int=5, ds_type:DatasetType=DatasetType.Train, reverse:bool=False, **kwargs)->None:
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\basic_data.py in one_batch(self, ds_type, detach, denorm, cpu)
166 w = self.num_workers
167 self.num_workers = 0
--> 168 try: x,y = next(iter(dl))
169 finally: self.num_workers = w
170 if detach: x,y = to_detach(x,cpu=cpu),to_detach(y,cpu=cpu)
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\basic_data.py in __iter__(self)
73 def __iter__(self):
74 "Process and returns items from `DataLoader`."
---> 75 for b in self.dl: yield self.proc_batch(b)
76
77 @classmethod
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\utils\data\dataloader.py in __next__(self)
558 if self.num_workers == 0: # same-process loading
559 indices = next(self.sample_iter) # may raise StopIteration
--> 560 batch = self.collate_fn([self.dataset[i] for i in indices])
561 if self.pin_memory:
562 batch = _utils.pin_memory.pin_memory_batch(batch)
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\utils\data\dataloader.py in <listcomp>(.0)
558 if self.num_workers == 0: # same-process loading
559 indices = next(self.sample_iter) # may raise StopIteration
--> 560 batch = self.collate_fn([self.dataset[i] for i in indices])
561 if self.pin_memory:
562 batch = _utils.pin_memory.pin_memory_batch(batch)
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\data_block.py in __getitem__(self, idxs)
649 else: x,y = self.item ,0
650 if self.tfms or self.tfmargs:
--> 651 x = x.apply_tfms(self.tfms, **self.tfmargs)
652 if hasattr(self, 'tfms_y') and self.tfm_y and self.item is None:
653 y = y.apply_tfms(self.tfms_y, **{**self.tfmargs_y, 'do_resolve':False})
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in apply_tfms(self, tfms, do_resolve, xtra, size, resize_method, mult, padding_mode, mode, remove_out)
120 elif tfm in size_tfms:
121 if resize_method in (ResizeMethod.CROP,ResizeMethod.PAD):
--> 122 x = tfm(x, size=_get_crop_target(size,mult=mult), padding_mode=padding_mode)
123 else: x = tfm(x)
124 return x.refresh()
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in __call__(self, x, *args, **kwargs)
516 def __call__(self, x:Image, *args, **kwargs)->Image:
517 "Randomly execute our tfm on `x`."
--> 518 return self.tfm(x, *args, **{**self.resolved, **kwargs}) if self.do_run else x
519
520 def _resolve_tfms(tfms:TfmList):
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in __call__(self, p, is_random, use_on_y, *args, **kwargs)
462 def __call__(self, *args:Any, p:float=1., is_random:bool=True, use_on_y:bool=True, **kwargs:Any)->Image:
463 "Calc now if `args` passed; else create a transform called prob `p` if `random`."
--> 464 if args: return self.calc(*args, **kwargs)
465 else: return RandTransform(self, kwargs=kwargs, is_random=is_random, use_on_y=use_on_y, p=p)
466
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in calc(self, x, *args, **kwargs)
467 def calc(self, x:Image, *args:Any, **kwargs:Any)->Image:
468 "Apply to image `x`, wrapping it if necessary."
--> 469 if self._wrap: return getattr(x, self._wrap)(self.func, *args, **kwargs)
470 else: return self.func(x, *args, **kwargs)
471
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in pixel(self, func, *args, **kwargs)
170 def pixel(self, func:PixelFunc, *args, **kwargs)->'Image':
171 "Equivalent to `image.px = func(image.px)`."
--> 172 self.px = func(self.px, *args, **kwargs)
173 return self
174
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in px(self)
143 def px(self)->TensorImage:
144 "Get the tensor pixel buffer."
--> 145 self.refresh()
146 return self._px
147 @px.setter
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in refresh(self)
130 self._logit_px = None
131 if self._affine_mat is not None or self._flow is not None:
--> 132 self._px = _grid_sample(self._px, self.flow, **self.sample_kwargs)
133 self.sample_kwargs = {}
134 self._flow = None
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in _grid_sample(x, coords, mode, padding_mode, remove_out)
532 d = min(x.shape[1]/coords.shape[1], x.shape[2]/coords.shape[2])/2
533 # If we're resizing up by >200%, and we're zooming less than that, interpolate first
--> 534 if d>1 and d>z: x = F.interpolate(x[None], scale_factor=1/d, mode='area')[0]
535 return F.grid_sample(x[None], coords, mode=mode, padding_mode=padding_mode)[0]
536
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\nn\functional.py in interpolate(input, size, scale_factor, mode, align_corners)
2549 return adaptive_avg_pool1d(input, _output_size(1))
2550 elif input.dim() == 4 and mode == 'area':
-> 2551 return adaptive_avg_pool2d(input, _output_size(2))
2552 elif input.dim() == 5 and mode == 'area':
2553 return adaptive_avg_pool3d(input, _output_size(3))
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\nn\functional.py in adaptive_avg_pool2d(input, output_size)
787 """
788 _output_size = _list_with_default(output_size, input.size())
--> 789 return torch._C._nn.adaptive_avg_pool2d(input, _output_size)
790
791
RuntimeError: "adaptive_avg_pool2d_cpu" not implemented for 'Byte'and for data it is:
RuntimeError Traceback (most recent call last)
~\Anaconda3\envs\fastaienv\lib\site-packages\IPython\core\formatters.py in __call__(self, obj)
700 type_pprinters=self.type_printers,
701 deferred_pprinters=self.deferred_printers)
--> 702 printer.pretty(obj)
703 printer.flush()
704 return stream.getvalue()
~\Anaconda3\envs\fastaienv\lib\site-packages\IPython\lib\pretty.py in pretty(self, obj)
400 if cls is not object \
401 and callable(cls.__dict__.get('__repr__')):
--> 402 return _repr_pprint(obj, self, cycle)
403
404 return _default_pprint(obj, self, cycle)
~\Anaconda3\envs\fastaienv\lib\site-packages\IPython\lib\pretty.py in _repr_pprint(obj, p, cycle)
695 """A pprint that just redirects to the normal repr function."""
696 # Find newlines and replace them with p.break_()
--> 697 output = repr(obj)
698 for idx,output_line in enumerate(output.splitlines()):
699 if idx:
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\basic_data.py in __repr__(self)
101
102 def __repr__(self)->str:
--> 103 return f'{self.__class__.__name__};\n\nTrain: {self.train_ds};\n\nValid: {self.valid_ds};\n\nTest: {self.test_ds}'
104
105 @staticmethod
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\data_block.py in __repr__(self)
611
612 def __repr__(self)->str:
--> 613 items = [self[i] for i in range(min(5,len(self.items)))]
614 res = f'{self.__class__.__name__} ({len(self.items)} items)\n'
615 res += f'x: {self.x.__class__.__name__}\n{show_some([i[0] for i in items])}\n'
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\data_block.py in <listcomp>(.0)
611
612 def __repr__(self)->str:
--> 613 items = [self[i] for i in range(min(5,len(self.items)))]
614 res = f'{self.__class__.__name__} ({len(self.items)} items)\n'
615 res += f'x: {self.x.__class__.__name__}\n{show_some([i[0] for i in items])}\n'
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\data_block.py in __getitem__(self, idxs)
649 else: x,y = self.item ,0
650 if self.tfms or self.tfmargs:
--> 651 x = x.apply_tfms(self.tfms, **self.tfmargs)
652 if hasattr(self, 'tfms_y') and self.tfm_y and self.item is None:
653 y = y.apply_tfms(self.tfms_y, **{**self.tfmargs_y, 'do_resolve':False})
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in apply_tfms(self, tfms, do_resolve, xtra, size, resize_method, mult, padding_mode, mode, remove_out)
120 elif tfm in size_tfms:
121 if resize_method in (ResizeMethod.CROP,ResizeMethod.PAD):
--> 122 x = tfm(x, size=_get_crop_target(size,mult=mult), padding_mode=padding_mode)
123 else: x = tfm(x)
124 return x.refresh()
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in __call__(self, x, *args, **kwargs)
516 def __call__(self, x:Image, *args, **kwargs)->Image:
517 "Randomly execute our tfm on `x`."
--> 518 return self.tfm(x, *args, **{**self.resolved, **kwargs}) if self.do_run else x
519
520 def _resolve_tfms(tfms:TfmList):
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in __call__(self, p, is_random, use_on_y, *args, **kwargs)
462 def __call__(self, *args:Any, p:float=1., is_random:bool=True, use_on_y:bool=True, **kwargs:Any)->Image:
463 "Calc now if `args` passed; else create a transform called prob `p` if `random`."
--> 464 if args: return self.calc(*args, **kwargs)
465 else: return RandTransform(self, kwargs=kwargs, is_random=is_random, use_on_y=use_on_y, p=p)
466
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in calc(self, x, *args, **kwargs)
467 def calc(self, x:Image, *args:Any, **kwargs:Any)->Image:
468 "Apply to image `x`, wrapping it if necessary."
--> 469 if self._wrap: return getattr(x, self._wrap)(self.func, *args, **kwargs)
470 else: return self.func(x, *args, **kwargs)
471
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in pixel(self, func, *args, **kwargs)
170 def pixel(self, func:PixelFunc, *args, **kwargs)->'Image':
171 "Equivalent to `image.px = func(image.px)`."
--> 172 self.px = func(self.px, *args, **kwargs)
173 return self
174
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in px(self)
143 def px(self)->TensorImage:
144 "Get the tensor pixel buffer."
--> 145 self.refresh()
146 return self._px
147 @px.setter
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in refresh(self)
130 self._logit_px = None
131 if self._affine_mat is not None or self._flow is not None:
--> 132 self._px = _grid_sample(self._px, self.flow, **self.sample_kwargs)
133 self.sample_kwargs = {}
134 self._flow = None
~\Anaconda3\envs\fastaienv\lib\site-packages\fastai\vision\image.py in _grid_sample(x, coords, mode, padding_mode, remove_out)
532 d = min(x.shape[1]/coords.shape[1], x.shape[2]/coords.shape[2])/2
533 # If we're resizing up by >200%, and we're zooming less than that, interpolate first
--> 534 if d>1 and d>z: x = F.interpolate(x[None], scale_factor=1/d, mode='area')[0]
535 return F.grid_sample(x[None], coords, mode=mode, padding_mode=padding_mode)[0]
536
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\nn\functional.py in interpolate(input, size, scale_factor, mode, align_corners)
2549 return adaptive_avg_pool1d(input, _output_size(1))
2550 elif input.dim() == 4 and mode == 'area':
-> 2551 return adaptive_avg_pool2d(input, _output_size(2))
2552 elif input.dim() == 5 and mode == 'area':
2553 return adaptive_avg_pool3d(input, _output_size(3))
~\Anaconda3\envs\fastaienv\lib\site-packages\torch\nn\functional.py in adaptive_avg_pool2d(input, output_size)
787 """
788 _output_size = _list_with_default(output_size, input.size())
--> 789 return torch._C._nn.adaptive_avg_pool2d(input, _output_size)
790
791
RuntimeError: "adaptive_avg_pool2d_cpu" not implemented for 'Byte'I am not sure why the error propagates to all data, but can you try with:
image2 = PIL.Image.open(directory+image_name).convert('RGB')
t = pil2tensor(image2, dtype=np.float32)
t.div_(255)
im = Image(t)
imb, _ = data.one_item(im, detach=False, denorm=False); imb
That’s how fastai opens an image by default.
Makes no sense, right? I’d like to know why it happened
Nice! It works. Thanks!
Where did you find it in fastai?
I still don’t know why it happened, but for the way fastai opens images, they way it works is:
ImageList.get, which calls ImageList.open (you can find it in fastai.vision.data)open_image, which is placed in fastai.vision.image. The code is:def open_image(fn:PathOrStr, div:bool=True, convert_mode:str='RGB', cls:type=Image,
after_open:Callable=None)->Image:
"Return `Image` object created from image in file `fn`."
with warnings.catch_warnings():
warnings.simplefilter("ignore", UserWarning) # EXIF warning from TiffPlugin
x = PIL.Image.open(fn).convert(convert_mode)
if after_open: x = after_open(x)
x = pil2tensor(x,np.float32)
if div: x.div_(255)
return cls(x)