I am trying to train my model (Image classification) using Tensorflow. I keep getting an error when I try to run the following cell:
hist = model.fit( train_generator, epochs=100, verbose=1, steps_per_epoch=steps_per_epoch, validation_data=valid_generator, validation_steps=val_steps_per_epoch).history
Error is:
Epoch 1/100 27/31 [=========================>....] - ETA: 1s - loss: 0.7309 - acc: 0.6181 --------------------------------------------------------------------------- UnknownError Traceback (most recent call last) <ipython-input-36-b1c104100211> in <module> 2 val_steps_per_epoch = np.ceil(valid_generator.samples/valid_generator.batch_size) 3 ----> 4 hist = model.fit( 5 train_generator, 6 epochs=100, /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/training.py in fit(self, x, y, batch_size, epochs, verbose, callbacks, validation_split, validation_data, shuffle, class_weight, sample_weight, initial_epoch, steps_per_epoch, validation_steps, validation_batch_size, validation_freq, max_queue_size, workers, use_multiprocessing) 1098 _r=1): 1099 callbacks.on_train_batch_begin(step) -> 1100 tmp_logs = self.train_function(iterator) 1101 if data_handler.should_sync: 1102 context.async_wait() /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in __call__(self, *args, **kwds) 826 tracing_count = self.experimental_get_tracing_count() 827 with trace.Trace(self._name) as tm: --> 828 result = self._call(*args, **kwds) 829 compiler = "xla" if self._experimental_compile else "nonXla" 830 new_tracing_count = self.experimental_get_tracing_count() /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/def_function.py in _call(self, *args, **kwds) 853 # In this case we have created variables on the first call, so we run the 854 # defunned version which is guaranteed to never create variables. --> 855 return self._stateless_fn(*args, **kwds) # pylint: disable=not-callable 856 elif self._stateful_fn is not None: 857 # Release the lock early so that multiple threads can perform the call /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py in __call__(self, *args, **kwargs) 2940 (graph_function, 2941 filtered_flat_args) = self._maybe_define_function(args, kwargs) -> 2942 return graph_function._call_flat( 2943 filtered_flat_args, captured_inputs=graph_function.captured_inputs) # pylint: disable=protected-access 2944 /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py in _call_flat(self, args, captured_inputs, cancellation_manager) 1916 and executing_eagerly): 1917 # No tape is watching; skip to running the function. -> 1918 return self._build_call_outputs(self._inference_function.call( 1919 ctx, args, cancellation_manager=cancellation_manager)) 1920 forward_backward = self._select_forward_and_backward_functions( /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/function.py in call(self, ctx, args, cancellation_manager) 553 with _InterpolateFunctionError(self): 554 if cancellation_manager is None: --> 555 outputs = execute.execute( 556 str(self.signature.name), 557 num_outputs=self._num_outputs, /opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/eager/execute.py in quick_execute(op_name, num_outputs, inputs, attrs, ctx, name) 57 try: 58 ctx.ensure_initialized() ---> 59 tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name, 60 inputs, attrs, num_outputs) 61 except core._NotOkStatusException as e: UnknownError: UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7fc88d55c9a0> Traceback (most recent call last): File "/opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/ops/script_ops.py", line 249, in __call__ ret = func(*args) File "/opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/autograph/impl/api.py", line 620, in wrapper return func(*args, **kwargs) File "/opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/data/ops/dataset_ops.py", line 891, in generator_py_func values = next(generator_state.get_iterator(iterator_id)) File "/opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 807, in wrapped_generator for data in generator_fn(): File "/opt/anaconda3/lib/python3.8/site-packages/tensorflow/python/keras/engine/data_adapter.py", line 933, in generator_fn yield x[i] File "/opt/anaconda3/lib/python3.8/site-packages/keras_preprocessing/image/iterator.py", line 65, in __getitem__ return self._get_batches_of_transformed_samples(index_array) File "/opt/anaconda3/lib/python3.8/site-packages/keras_preprocessing/image/iterator.py", line 227, in _get_batches_of_transformed_samples img = load_img(filepaths[j], File "/opt/anaconda3/lib/python3.8/site-packages/keras_preprocessing/image/utils.py", line 114, in load_img img = pil_image.open(io.BytesIO(f.read())) File "/opt/anaconda3/lib/python3.8/site-packages/PIL/Image.py", line 2943, in open raise UnidentifiedImageError( PIL.UnidentifiedImageError: cannot identify image file <_io.BytesIO object at 0x7fc88d55c9a0> [[{{node PyFunc}}]] [[IteratorGetNext]] [Op:__inference_train_function_24233] Function call stack: train_function
I tried changing from loss=’categorical_crossentropy’ to loss=’binary_crossentropy’ but still the issue persists. I wish to train the model but the Epoch keeps getting stuck.
Edit:
The train generator function and where it is used is as follows:
IMAGE_SHAPE = (224, 224) TRAINING_DATA_DIR = str(data_root) datagen_kwargs = dict(rescale=1./255, validation_split=.20) valid_datagen = tf.keras.preprocessing.image.ImageDataGenerator(**datagen_kwargs) valid_generator = valid_datagen.flow_from_directory( TRAINING_DATA_DIR, subset="validation", shuffle=True, target_size=IMAGE_SHAPE ) train_datagen = tf.keras.preprocessing.image.ImageDataGenerator(**datagen_kwargs) train_generator = train_datagen.flow_from_directory( TRAINING_DATA_DIR, subset="training", shuffle=True, target_size=IMAGE_SHAPE) for image_batch, label_batch in train_generator: break image_batch.shape, label_batch.shape
Output: ((32, 224, 224, 3), (32, 2))
print (train_generator.class_indices) labels = 'n'.join(sorted(train_generator.class_indices.keys())) with open('labels.txt', 'w') as f: f.write(labels)
Output: {‘off’: 0, ‘on’: 1}
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Answer
There was an issue with one of the img that was causing an issue and was pointed out by @Lescurel. To view the img you can run the following:
import PIL from pathlib import Path from PIL import UnidentifiedImageError path = Path("INSERT PATH HERE").rglob("*.jpeg") for img_p in path: try: img = PIL.Image.open(img_p) except PIL.UnidentifiedImageError: print(img_p)
You can also do the same for png or other formats. If there is an issue with your image, it will list it as soon as you run it