python - 尝试使用 tensorflow.io.gfile.GFile 和 tensorflow.dataset.map，得到“预期的二进制或 unicode 字符串，得到 Tensor dtype=string

问题描述

我对使用 Tensorflow 很陌生，想象一下有人会很快告诉我我在做一些愚蠢的事情，所以就这样吧。

我正在使用 MSTAR 数据集并试图将其读入。这些文件的格式非常奇怪，但可以说，如果在以下代码上急切执行，则会从数据集中读取并显示图像。

import tensorflow as tf
import matplotlib.pyplot as plt
tf.enable_eager_execution()

img1Path='HB15000.018'
img2Path='HB15001.018'

def pathToImgTF(path):
    with tf.io.gfile.GFile(path,'rb') as filePath:
        step1=filePath.readlines()
        step2=[x.strip(b'\n') for x in step1]
        for x in step2:
            if b'PhoenixHeaderLength' in x:
                line=x.strip().split(b'=')
                PhoenixHeaderLength=int(line[1])
            elif b'native_header_length' in x:
                line=x.strip().split(b'=')
                native_header_length=int(line[1])
            elif b'NumberOfColumns' in x:
                line=x.strip().split(b'=')
                NumberOfColumns=int(line[1])
            elif b'NumberOfRows' in x:
                line=x.strip().split(b'=')
                NumberOfRows=int(line[1])
        filePath.seek(PhoenixHeaderLength+native_header_length)
        step3=tf.decode_raw(filePath.read(),out_type=tf.float32,little_endian=False)
        depth_major=tf.reshape(step3,[2,NumberOfRows,NumberOfColumns])
        image=tf.transpose(depth_major,[1,2,0])[:,:,0] #Cut off phase for now
    return image

img=pathToImgTF(imgPath)
plt.imshow(img,cmap='gray')

我想使用 tf.dataset.from_tensor_slices，但似乎这不是一个选项，因为以下代码：

ds=tf.data.Dataset.from_tensor_slices([img1Path,img2Path])
ds=ds.map(pathToImgTF)

给出错误“TypeError: Expected binary or unicode string, got tf.Tensor 'args_0:0' shape=() dtype=string”

在我看来，回溯看起来像是在“filePath.readlines()”上特别中断，任何帮助将不胜感激。

完整的错误输出：

-------------------------------------------------- ------------------------- TypeError Traceback（最近一次调用最后一次）ipython-input-6-e12909fb73cd in module 1 ds=tf.data.Dataset .from_tensor_slices([img1Path,img2Path]) ----> 2 ds=ds.map(pathToImgTF)

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py in map(self, map_func, num_parallel_calls) 1770 如果 num_parallel_calls 为无：1771 返回 DatasetV1Adapter( -> 1772 MapDataset (self, map_func, preserve_cardinality=False)) 1773 else: 1774 return DatasetV1Adapter(

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py in init (self, input_dataset, map_func, use_inter_op_parallelism, preserve_cardinality, use_legacy_function) 3188
self._transformation_name(), 3189 dataset=input_dataset，-> 3190 use_legacy_function=use_legacy_function）3191 variant_tensor = gen_dataset_ops.map_dataset（3192
input_dataset._variant_tensor，#pylint：禁用=保护访问

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py init (self, func, transformation_name, dataset, input_classes, input_shapes, input_types, input_structure, add_to_graph, use_legacy_function, defun_kwargs) 2553 resource_tracker = tracking.ResourceTracker() 2554 with tracking.resource_tracker_scope(resource_tracker): -> 2555 self._function = wrapper_fn._get_concrete_function_internal() 2556 if add_to_graph: 2557
self._function.add_to_graph(ops.get_default_graph())

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _get_concrete_function_internal(self, *args, **kwargs) 1353
"""获取图形函数时绕过错误检查。 """ 1354
graph_function = self._get_concrete_function_internal_garbage_collected( -> 1355 *args, **kwargs) 1356 # 我们将这个具体函数返回给某人，他们可能会保留一个 1357 # 对 FuncGraph 的引用而不保留对

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _get_concrete_function_internal_garbage_collected(self, *args, **kwargs) 1347 if self.input_signature: 1348 args, kwargs = None,无-> 1349 graph_function，_，_ = self._maybe_define_function（args，kwargs）1350 return graph_function 1351

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _maybe_define_function(self, args, kwargs) 1650
graph_function = self._function_cache.primary.get(cache_key, None)
1651如果 graph_function 为 None：-> 1652 graph_function = self._create_graph_function(args, kwargs) 1653 self._function_cache.primary[cache_key] = graph_function 1654 return graph_function, args, kwargs

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\eager\function.py in _create_graph_function(self, args, kwargs, override_flat_arg_shapes) 1543 arg_names=arg_names,
1544 override_flat_arg_shapes=override_flat_arg_shapes，-> 1545 capture_by_value =self._capture_by_value），1546 self._function_attributes）1547

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\framework\func_graph.py in func_graph_from_py_func(name, python_func, args, kwargs, signature, func_graph, autograph, autograph_options, add_control_dependencies, arg_names, op_return_value, collections, capture_by_value, override_flat_arg_shapes) 713 convert_func) 714 --> 715 func_outputs = python_func(*func_args, **func_kwargs) 716 717 # invariant:func_outputs只包含 Tensors, CompositeTensors,

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py in wrapper_fn(*args) 2547 attributes=defun_kwargs)
2548 def wrapper_fn(*args): #pylint: disable =missing-docstring -> 2549 ret = _wrapper_helper(*args) 2550 ret = self._output_structure._to_tensor_list(ret) 2551 return [ops.convert_to_tensor(t) for t in ret]

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\data\ops\dataset_ops.py in _wrapper_helper(*args) 2487 nested_args = (nested_args,) 2488 -> 2489 ret = func(*nested_args ) 2490 # 如果func返回张量列表，nest.flatten()并且 2491 # ops.convert_to_tensor()会合谋尝试堆叠

在 pathToImgTF(path) 9 def pathToImgTF(path): 10 with tf.io.gfile.GFile(path,'rb') as filePath: ---> 11 step1=filePath.readlines() 12 step2=[x.strip (b'\n') for x in step1] 13 for x in step2:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\lib\io\file_io.py in readlines(self) 181 def readlines(self): 182 """返回文件中的所有行一个列表。""" --> 183 self._preread_check() 184 lines = [] 185 while True:

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\lib\io\file_io.py in _preread_check(self) 82“文件未打开读取”) 83 self._read_buf = pywrap_tensorflow。 CreateBufferedInputStream(---> 84 compat.as_bytes(self.__name), 1024 * 512) 85 86 def _prewrite_check(self):

~\AppData\Local\Continuum\anaconda3\lib\site-packages\tensorflow\python\util\compat.py in as_bytes(bytes_or_text, encoding) 63 else: 64 raise TypeError('Expected binary or unicode string, got %r' % ---> 65 (bytes_or_text,)) 66 67

TypeError: Expected binary or unicode string, got tf.Tensor 'args_0:0' shape=() dtype=string

标签： pythontensorflow

python - 尝试使用 tensorflow.io.gfile.GFile 和 tensorflow.dataset.map，得到“预期的二进制或 unicode 字符串，得到 Tensor dtype=string

问题描述

解决方案

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