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运行测试脚本时出现“标签越界”错误。将注释值与类数进行比较时,confusion_matrix 函数会抛出错误。在我的例子中,注释值是一个图像(560x560)和 number_of_classes = 2。
[check_ops.assert_less(labels, num_classes_int64, message='`labels` out of bound')], labels
上述条件总是会失败,因为注释数据大于类的数量。
首先,我很可能误解了代码,但我无法理解它。
其次,如果这是一个有效的检查,那么我该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)]]
我真的迷路了,所以任何帮助或建议都将不胜感激!
最佳答案
同样的问题。
“标签”数组 Y_true
的值为 0, 255
。我用过:
Y_true = Y_true/255
将 Y_true
压缩为 0, 1
。
这消除了错误。
关于Tensorflow:断言失败:[`labels` 越界],我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/46164419/
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