Hello!
I am doing the first lesson 'Is it a bird? Creating a model from your own data"
And I don’t know what to do with this error
pil_img = PILImage.create('bird.jpg')
is_bird,_,probs = learn.predict(pil_img)
I have the following error - AttributeError: read
The file exists. The path is correct. All versions are updated.
The text of the error
AttributeError Traceback (most recent call last)
/tmp/ipykernel_17/665255836.py in
----> 1 is_bird,_,probs = learn.predict(img)
2 print(f"This is a: {is_bird}.“)
3 print(f"Probability it’s a bird: {probs[0]:.4f}”)
/opt/conda/lib/python3.7/site-packages/fastai/learner.py in predict(self, item, rm_type_tfms, with_input)
319 def predict(self, item, rm_type_tfms=None, with_input=False):
320 dl = self.dls.test_dl([item], rm_type_tfms=rm_type_tfms, num_workers=0)
→ 321 inp,preds,_,dec_preds = self.get_preds(dl=dl, with_input=True, with_decoded=True)
322 i = getattr(self.dls, ‘n_inp’, -1)
323 inp = (inp,) if i==1 else tuplify(inp)
/opt/conda/lib/python3.7/site-packages/fastai/learner.py in get_preds(self, ds_idx, dl, with_input, with_decoded, with_loss, act, inner, reorder, cbs, **kwargs)
306 if with_loss: ctx_mgrs.append(self.loss_not_reduced())
307 with ContextManagers(ctx_mgrs):
→ 308 self._do_epoch_validate(dl=dl)
309 if act is None: act = getcallable(self.loss_func, ‘activation’)
310 res = cb.all_tensors()
/opt/conda/lib/python3.7/site-packages/fastai/learner.py in _do_epoch_validate(self, ds_idx, dl)
242 if dl is None: dl = self.dls[ds_idx]
243 self.dl = dl
→ 244 with torch.no_grad(): self._with_events(self.all_batches, ‘validate’, CancelValidException)
245
246 def _do_epoch(self):
/opt/conda/lib/python3.7/site-packages/fastai/learner.py in with_events(self, f, event_type, ex, final)
197
198 def with_events(self, f, event_type, ex, final=noop):
→ 199 try: self(f’before{event_type}'); f()
200 except ex: self(f’after_cancel{event_type}‘)
201 self(f’after_{event_type}’); final()
/opt/conda/lib/python3.7/site-packages/fastai/learner.py in all_batches(self)
203 def all_batches(self):
204 self.n_iter = len(self.dl)
→ 205 for o in enumerate(self.dl): self.one_batch(*o)
206
207 def _backward(self): self.loss_grad.backward()
/opt/conda/lib/python3.7/site-packages/fastai/data/load.py in iter(self)
125 self.before_iter()
126 self.__idxs=self.get_idxs() # called in context of main process (not workers/subprocesses)
→ 127 for b in _loadersself.fake_l.num_workers==0:
128 # pin_memory causes tuples to be converted to lists, so convert them back to tuples
129 if self.pin_memory and type(b) == list: b = tuple(b)
/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py in next(self)
519 if self._sampler_iter is None:
520 self._reset()
→ 521 data = self._next_data()
522 self._num_yielded += 1
523 if self._dataset_kind == _DatasetKind.Iterable and \
/opt/conda/lib/python3.7/site-packages/torch/utils/data/dataloader.py in _next_data(self)
559 def _next_data(self):
560 index = self._next_index() # may raise StopIteration
→ 561 data = self._dataset_fetcher.fetch(index) # may raise StopIteration
562 if self._pin_memory:
563 data = _utils.pin_memory.pin_memory(data)
/opt/conda/lib/python3.7/site-packages/torch/utils/data/_utils/fetch.py in fetch(self, possibly_batched_index)
32 raise StopIteration
33 else:
—> 34 data = next(self.dataset_iter)
35 return self.collate_fn(data)
36
/opt/conda/lib/python3.7/site-packages/fastai/data/load.py in create_batches(self, samps)
136 if self.dataset is not None: self.it = iter(self.dataset)
137 res = filter(lambda o:o is not None, map(self.do_item, samps))
→ 138 yield from map(self.do_batch, self.chunkify(res))
139
140 def new(self, dataset=None, cls=None, **kwargs):
/opt/conda/lib/python3.7/site-packages/fastcore/basics.py in chunked(it, chunk_sz, drop_last, n_chunks)
228 if not isinstance(it, Iterator): it = iter(it)
229 while True:
→ 230 res = list(itertools.islice(it, chunk_sz))
231 if res and (len(res)==chunk_sz or not drop_last): yield res
232 if len(res)<chunk_sz: return
/opt/conda/lib/python3.7/site-packages/fastai/data/load.py in do_item(self, s)
151 def prebatched(self): return self.bs is None
152 def do_item(self, s):
→ 153 try: return self.after_item(self.create_item(s))
154 except SkipItemException: return None
155 def chunkify(self, b): return b if self.prebatched else chunked(b, self.bs, self.drop_last)
/opt/conda/lib/python3.7/site-packages/fastai/data/load.py in create_item(self, s)
158 def retain(self, res, b): return retain_types(res, b[0] if is_listy(b) else b)
159 def create_item(self, s):
→ 160 if self.indexed: return self.dataset[s or 0]
161 elif s is None: return next(self.it)
162 else: raise IndexError(“Cannot index an iterable dataset numerically - must use None.”)
/opt/conda/lib/python3.7/site-packages/fastai/data/core.py in getitem(self, it)
456
457 def getitem(self, it):
→ 458 res = tuple([tl[it] for tl in self.tls])
459 return res if is_indexer(it) else list(zip(*res))
460
/opt/conda/lib/python3.7/site-packages/fastai/data/core.py in (.0)
456
457 def getitem(self, it):
→ 458 res = tuple([tl[it] for tl in self.tls])
459 return res if is_indexer(it) else list(zip(*res))
460
/opt/conda/lib/python3.7/site-packages/fastai/data/core.py in getitem(self, idx)
415 res = super().getitem(idx)
416 if self._after_item is None: return res
→ 417 return self._after_item(res) if is_indexer(idx) else res.map(self._after_item)
418
419 # %% …/…/nbs/03_data.core.ipynb 53
/opt/conda/lib/python3.7/site-packages/fastai/data/core.py in _after_item(self, o)
375 raise
376 def subset(self, i): return self._new(self._get(self.splits[i]), split_idx=i)
→ 377 def _after_item(self, o): return self.tfms(o)
378 def repr(self): return f"{self.class.name}: {self.items}\ntfms - {self.tfms.fs}"
379 def iter(self): return (self[i] for i in range(len(self)))
/opt/conda/lib/python3.7/site-packages/fastcore/transform.py in call(self, o)
206 self.fs = self.fs.sorted(key=‘order’)
207
→ 208 def call(self, o): return compose_tfms(o, tfms=self.fs, split_idx=self.split_idx)
209 def repr(self): return f"Pipeline: {’ → '.join([f.name for f in self.fs if f.name != ‘noop’])}"
210 def getitem(self,i): return self.fs[i]
/opt/conda/lib/python3.7/site-packages/fastcore/transform.py in compose_tfms(x, tfms, is_enc, reverse, **kwargs)
156 for f in tfms:
157 if not is_enc: f = f.decode
→ 158 x = f(x, **kwargs)
159 return x
160
/opt/conda/lib/python3.7/site-packages/fastcore/transform.py in call(self, x, **kwargs)
79 @property
80 def name(self): return getattr(self, ‘_name’, _get_name(self))
—> 81 def call(self, x, **kwargs): return self._call(‘encodes’, x, **kwargs)
82 def decode (self, x, **kwargs): return self._call(‘decodes’, x, **kwargs)
83 def repr(self): return f’{self.name}:\nencodes: {self.encodes}decodes: {self.decodes}’
/opt/conda/lib/python3.7/site-packages/fastcore/transform.py in _call(self, fn, x, split_idx, **kwargs)
89 def _call(self, fn, x, split_idx=None, **kwargs):
90 if split_idx!=self.split_idx and self.split_idx is not None: return x
—> 91 return self._do_call(getattr(self, fn), x, **kwargs)
92
93 def _do_call(self, f, x, **kwargs):
/opt/conda/lib/python3.7/site-packages/fastcore/transform.py in do_call(self, f, x, **kwargs)
95 if f is None: return x
96 ret = f.returns(x) if hasattr(f,‘returns’) else None
—> 97 return retain_type(f(x, **kwargs), x, ret)
98 res = tuple(self.do_call(f, x, **kwargs) for x in x)
99 return retain_type(res, x)
/opt/conda/lib/python3.7/site-packages/fastcore/dispatch.py in call(self, *args, **kwargs)
118 elif self.inst is not None: f = MethodType(f, self.inst)
119 elif self.owner is not None: f = MethodType(f, self.owner)
→ 120 return f(*args, **kwargs)
121
122 def get(self, inst, owner):
/opt/conda/lib/python3.7/site-packages/fastai/vision/core.py in create(cls, fn, **kwargs)
123 if isinstance(fn,bytes): fn = io.BytesIO(fn)
124 if isinstance(fn,Image.Image) and not isinstance(fn,cls): return cls(fn)
→ 125 return cls(load_image(fn, **merge(cls._open_args, kwargs)))
126
127 def show(self, ctx=None, **kwargs):
/opt/conda/lib/python3.7/site-packages/fastai/vision/core.py in load_image(fn, mode)
96 def load_image(fn, mode=None):
97 “Open and load a PIL.Image and convert to mode”
—> 98 im = Image.open(fn)
99 im.load()
100 im = im._new(im.im)
/opt/conda/lib/python3.7/site-packages/PIL/Image.py in open(fp, mode, formats)
2919 exclusive_fp = True
2920
→ 2921 prefix = fp.read(16)
2922
2923 preinit()
/opt/conda/lib/python3.7/site-packages/PIL/Image.py in getattr(self, name)
539 )
540 return self._category
→ 541 raise AttributeError(name)
542
543 @property
AttributeError: read