我有一个文件夹结构，其中每个子文件夹代表一个类，每个类都有一个示例图片。我想在如下所述的Keras数据集中加载数据:https://www.tensorflow.org/api_docs/python/tf/keras/preprocessing/image_dataset_from_directory我希望得到元组"(图像，标签)"返回，但是当我将函数的输出赋值给元组时，我得到了一个错误。
下面是我的代码:import pathlib
data_path = "./patterns"
data_dir = pathlib.Path(data_path)
batch_size = 32
img_height = 120
img_width = 30
train_ds, train_labels = tf.keras.preprocessing.image_dataset_from_directory(
data_dir,
labels='inferred',
label_mode='categorical', #int
validation_split=0.2,
subset="training",
seed=123,
image_size=(img_height, img_width),
batch_size=batch_size)
我收到的错误是:
Found 2160 files belonging to 2160 classes.
Using 1728 files for training.
---------------------------------------------------------------------------
InvalidArgumentError Traceback (most recent call last)
/usr/local/lib/python3.7/site-packages/tensorflow/python/eager/context.py in execution_mode(mode)
2101 ctx.executor = executor_new
-> 2102 yield
2103 finally:
/usr/local/lib/python3.7/site-packages/tensorflow/python/data/ops/iterator_ops.py in _next_internal(self)
757 output_types=self._flat_output_types,
--> 758 output_shapes=self._flat_output_shapes)
759
/usr/local/lib/python3.7/site-packages/tensorflow/python/ops/gen_dataset_ops.py in iterator_get_next(iterator, output_types, output_shapes, name)
2609 except _core._NotOkStatusException as e:
-> 2610 _ops.raise_from_not_ok_status(e, name)
2611 except _core._FallbackException:
/usr/local/lib/python3.7/site-packages/tensorflow/python/framework/ops.py in raise_from_not_ok_status(e, name)
6842 # pylint: disable=protected-access
-> 6843 six.raise_from(core._status_to_exception(e.code, message), None)
6844 # pylint: enable=protected-access
/usr/local/lib/python3.7/site-packages/six.py in raise_from(value, from_value)
InvalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]
[[{{node decode_image/cond_jpeg/else/_1/decode_image/cond_jpeg/cond_png/else/_20/decode_image/cond_jpeg/cond_png/cond_gif/else/_39/decode_image/cond_jpeg/cond_png/cond_gif/Assert/Assert}}]] [Op:IteratorGetNext]
During handling of the above exception, another exception occurred:
InvalidArgumentError Traceback (most recent call last)
<ipython-input-74-f878a6f234dd> in <module>
7 seed=123,
8 image_size=(img_height, img_width),
----> 9 batch_size=batch_size)
/usr/local/lib/python3.7/site-packages/tensorflow/python/data/ops/iterator_ops.py in __next__(self)
734
735 def __next__(self): # For Python 3 compatibility
--> 736 return self.next()
737
738 def _next_internal(self):
/usr/local/lib/python3.7/site-packages/tensorflow/python/data/ops/iterator_ops.py in next(self)
770 def next(self):
771 try:
--> 772 return self._next_internal()
773 except errors.OutOfRangeError:
774 raise StopIteration
/usr/local/lib/python3.7/site-packages/tensorflow/python/data/ops/iterator_ops.py in _next_internal(self)
762 return self._element_spec._from_compatible_tensor_list(ret) # pylint: disable=protected-access
763 except AttributeError:
--> 764 return structure.from_compatible_tensor_list(self._element_spec, ret)
765
766 @property
/usr/local/lib/python3.7/contextlib.py in __exit__(self, type, value, traceback)
128 value = type()
129 try:
--> 130 self.gen.throw(type, value, traceback)
131 except StopIteration as exc:
132 # Suppress StopIteration *unless* it's the same exception that
/usr/local/lib/python3.7/site-packages/tensorflow/python/eager/context.py in execution_mode(mode)
2103 finally:
2104 ctx.executor = executor_old
-> 2105 executor_new.wait()
2106
2107
/usr/local/lib/python3.7/site-packages/tensorflow/python/eager/executor.py in wait(self)
65 def wait(self):
66 """Waits for ops dispatched in this executor to finish."""
---> 67 pywrap_tfe.TFE_ExecutorWaitForAllPendingNodes(self._handle)
68
69 def clear_error(self):
InvalidArgumentError: assertion failed: [Unable to decode bytes as JPEG, PNG, GIF, or BMP]
[[{{node decode_image/cond_jpeg/else/_1/decode_image/cond_jpeg/cond_png/else/_20/decode_image/cond_jpeg/cond_png/cond_gif/else/_39/decode_image/cond_jpeg/cond_png/cond_gif/Assert/Assert}}]]
不管怎样，有趣的是我仍然得到输出:
Found 2160 files belonging to 2160 classes.
Using 1728 files for training.
当我将函数输出只分配给单个变量(train_ds)时，我没有收到错误。
我认为您的图像之一已损坏。使用这个函数，看看它是否崩溃。它将在读取文件名之前打印文件名，这样您就可以看到哪个图片损坏了。
修改os.listdir()部分，使其包含不同文件夹中的所有图像。
import tensorflow as tf
import os
def validate_image(file_name):
tf.py_function(tf.print, inp=[file_name], Tout=[])
image = tf.io.read_file(file_name)
image = tf.io.decode_image(image, channels=3)
return image
os.chdir(r'pathtoimages')
accepted_extensions = ('jpg', 'png', 'bmp', 'gif')
files = list(filter(lambda x: x.lower().endswith(accepted_extensions), os.listdir()))
ds = tf.data.Dataset.from_tensor_slices(files).map(validate_image)
for i in ds:
pass