Tensorflow:断言失败：[`labels`越界]

Question

运行测试脚本时出现“Label out out bound”错误。将注释值与类的数量进行比较时，会在confusion_matrix函数中抛出错误。在我的例子中，注释值是一幅图像(560x560)，number_of_classes = 2。

[check_ops.assert_less(labels, num_classes_int64, message='`labels` out of bound')], labels

上面的条件总是会失败，因为注释数据大于类的数量。

首先，我很有可能误解了代码，但我不能理解它。

其次，如果这是一个有效的检查，那么我如何修改我的代码或数据来避免这个错误。

def confusion_matrix(labels, predictions, num_classes=None, dtype=dtypes.int32,
                     name=None, weights=None):
 with ops.name_scope(name, 'confusion_matrix',
                      (predictions, labels, num_classes, weights)) as name:
    labels, predictions = remove_squeezable_dimensions(
        ops.convert_to_tensor(labels, name='labels'),
        ops.convert_to_tensor(
            predictions, name='predictions'))
    predictions = math_ops.cast(predictions, dtypes.int64)
    labels = math_ops.cast(labels, dtypes.int64)

    # Sanity checks - underflow or overflow can cause memory corruption.
    labels = control_flow_ops.with_dependencies(
        [check_ops.assert_non_negative(
            labels, message='`labels` contains negative values')],
        labels)
    predictions = control_flow_ops.with_dependencies(
        [check_ops.assert_non_negative(
            predictions, message='`predictions` contains negative values')],
        predictions)
    print(num_classes)
    if num_classes is None:
      num_classes = math_ops.maximum(math_ops.reduce_max(predictions),
                                     math_ops.reduce_max(labels)) + 1
      #$

    else:
      num_classes_int64 = math_ops.cast(num_classes, dtypes.int64)
      ---->>labels = control_flow_ops.with_dependencies(
          [check_ops.assert_less(
              labels, num_classes_int64, message='`labels` out of bound')],
          labels)<<----
      predictions = control_flow_ops.with_dependencies(
          [check_ops.assert_less(
              predictions, num_classes_int64,
              message='`predictions` out of bound')],
          predictions)

    if weights is not None:
      predictions.get_shape().assert_is_compatible_with(weights.get_shape())
      weights = math_ops.cast(weights, dtype)

    shape = array_ops.stack([num_classes, num_classes])
    indices = array_ops.transpose(array_ops.stack([labels, predictions]))
    values = (array_ops.ones_like(predictions, dtype)
              if weights is None else weights)
    cm_sparse = sparse_tensor.SparseTensor(
        indices=indices, values=values, dense_shape=math_ops.to_int64(shape))
    zero_matrix = array_ops.zeros(math_ops.to_int32(shape), dtype)

    return sparse_ops.sparse_add(zero_matrix, cm_sparse)

Traceback (most recent call last):
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1327, in _do_call
    return fn(*args)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1306, in _run_fn
    status, run_metadata)
  File "C:\Program Files\Python35\lib\contextlib.py", line 66, in __exit__
    next(self.gen)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\framework\errors_impl.py", line 466, in raise_exception_on_not_ok_status
    pywrap_tensorflow.TF_GetCode(status))
tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [`labels` out of bound] [Condition x < y did not hold element-wise:x (mean_iou/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (mean_iou/ToInt64_2:0) = ] [21]
     [[Node: mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert = Assert[T=[DT_STRING, DT_STRING, DT_INT64, DT_STRING, DT_INT64], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_0, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_3, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_2)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "C:/Users/supriya.godge/PycharmProjects/tf-image-segmentation/tf_image_segmentation/recipes/pascal_voc/DeepLab/output/resnet_v1_101_8s_test_airplan.py", line 81, in <module>
    image_np, annotation_np, pred_np, tmp = sess.run([image, annotation, pred, update_op])
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 895, in run
    run_metadata_ptr)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1124, in _run
    feed_dict_tensor, options, run_metadata)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1321, in _do_run
    options, run_metadata)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\client\session.py", line 1340, in _do_call
    raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: assertion failed: [`labels` out of bound] [Condition x < y did not hold element-wise:x (mean_iou/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (mean_iou/ToInt64_2:0) = ] [21]
     [[Node: mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert = Assert[T=[DT_STRING, DT_STRING, DT_INT64, DT_STRING, DT_INT64], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_0, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_3, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_2)]]

Caused by op 'mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert', defined at:
  File "C:/Users/supriya.godge/PycharmProjects/tf-image-segmentation/tf_image_segmentation/recipes/pascal_voc/DeepLab/output/resnet_v1_101_8s_test_airplan.py", line 64, in <module>
    weights=weights)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\contrib\metrics\python\ops\metric_ops.py", line 2245, in streaming_mean_iou
    updates_collections=updates_collections, name=name)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\metrics_impl.py", line 917, in mean_iou
    num_classes, weights)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\metrics_impl.py", line 285, in _streaming_confusion_matrix
    labels, predictions, num_classes, weights=weights, dtype=cm_dtype)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\confusion_matrix.py", line 178, in confusion_matrix
    labels, num_classes_int64, message='`labels` out of bound')],
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\check_ops.py", line 401, in assert_less
    return control_flow_ops.Assert(condition, data, summarize=summarize)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\util\tf_should_use.py", line 175, in wrapped
    return _add_should_use_warning(fn(*args, **kwargs))
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 131, in Assert
    condition, no_op, true_assert, name="AssertGuard")
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\util\deprecation.py", line 296, in new_func
    return func(*args, **kwargs)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 1828, in cond
    orig_res_f, res_f = context_f.BuildCondBranch(false_fn)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 1694, in BuildCondBranch
    original_result = fn()
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\control_flow_ops.py", line 129, in true_assert
    condition, data, summarize, name="Assert")
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\ops\gen_logging_ops.py", line 35, in _assert
    summarize=summarize, name=name)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\framework\op_def_library.py", line 767, in apply_op
    op_def=op_def)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 2630, in create_op
    original_op=self._default_original_op, op_def=op_def)
  File "C:\Program Files\Python35\lib\site-packages\tensorflow\python\framework\ops.py", line 1204, in __init__
    self._traceback = self._graph._extract_stack()  # pylint: disable=protected-access

InvalidArgumentError (see above for traceback): assertion failed: [`labels` out of bound] [Condition x < y did not hold element-wise:x (mean_iou/confusion_matrix/control_dependency:0) = ] [0 0 0...] [y (mean_iou/ToInt64_2:0) = ] [21]
     [[Node: mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert = Assert[T=[DT_STRING, DT_STRING, DT_INT64, DT_STRING, DT_INT64], summarize=3, _device="/job:localhost/replica:0/task:0/cpu:0"](mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_0, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_1, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/data_3, mean_iou/confusion_matrix/assert_less/Assert/AssertGuard/Assert/Switch_2)]]

我真的迷失在这里，所以任何帮助或建议是感激的！

Answer 1

在注释文件中，标签是0、1、2、255。标签的范围是3。所以当在上面的注释文件中检测到255时，就会抛出错误。在我删除了所有255个值之后，代码运行正常，没有任何错误。

Answer 2

这里也有同样的问题。

“labels”数组Y_true的值为0, 255。我使用：

Y_true = Y_true/255

将Y_true压缩到0, 1。

这样就消除了错误。

Answer 3

在tensorflow 1.15.2下，tensorflow/models/research/deeplab基本上是可以的。

错误消息如下：

无效参数:断言失败：labels越界x (mean_iou/confusion_matrix/control_dependency:0) =

很可能是因为没有将背景视为1类。例如deeplab/datasets/data_generator.py

# Number of semantic classes, including the
# background class (if exists). For example, there
# are 20 foreground classes + 1 background class in
# the PASCAL VOC 2012 dataset. Thus, we set
# num_classes=21.