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Fix grammatical mistakes in doc #477

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Nov 29, 2017
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Fix grammatical mistakes in doc #477

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3a73d4d
grammatical errors
yuyu2172 Oct 27, 2017
7ebd029
inputs -> input
yuyu2172 Oct 27, 2017
384aa3e
merge master
yuyu2172 Oct 27, 2017
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6 changes: 3 additions & 3 deletions chainercv/utils/bbox/non_maximum_suppression.py
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Expand Up @@ -39,9 +39,9 @@ def non_maximum_suppression(bbox, thresh, score=None,
confidence of prediction.

This function accepts both :obj:`numpy.ndarray` and :obj:`cupy.ndarray` as
inputs. Please note that both :obj:`bbox` and :obj:`score` need to be
same type.
The output is same type as the type of the inputs.
an input. Please note that both :obj:`bbox` and :obj:`score` need to be
the same type.
The type of the output is the same as the input.

Args:
bbox (array): Bounding boxes to be transformed. The shape is
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2 changes: 1 addition & 1 deletion docs/source/tutorial/detection.rst
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Expand Up @@ -192,7 +192,7 @@ Last, an evaluation function is called with the ground truth annotations and the

In contrast to evaluators that hide details,
evaluation functions such as :meth:`chainercv.evaluations.eval_detection_voc`
are provided for those who need finer level of control.
are provided for those who need a finer level of control.
These functions take the ground truth annotations and prediction results as arguments
and return measured performance.

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