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Fixed documentation: corrected parameter names

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This commit is contained in:
Andrey Kamaev
2012-05-29 10:36:19 +00:00
parent 67b718f1cb
commit 05de6302fd
39 changed files with 554 additions and 509 deletions
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modules/features2d/doc/common_interfaces_of_descriptor_matchers.rst
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@@ -269,7 +269,7 @@ Brute-force matcher constructor.
.. ocv:function:: BFMatcher::BFMatcher( int normType, bool crossCheck=false )
:param distanceType: One of ``NORM_L1``, ``NORM_L2``, ``NORM_HAMMING``, ``NORM_HAMMING2``. ``L1`` and ``L2`` norms are preferable choices for SIFT and SURF descriptors, ``NORM_HAMMING`` should be used with ORB and BRIEF, ``NORM_HAMMING2`` should be used with ORB when ``WTA_K==3`` or ``4`` (see ORB::ORB constructor description).
:param normType: One of ``NORM_L1``, ``NORM_L2``, ``NORM_HAMMING``, ``NORM_HAMMING2``. ``L1`` and ``L2`` norms are preferable choices for SIFT and SURF descriptors, ``NORM_HAMMING`` should be used with ORB and BRIEF, ``NORM_HAMMING2`` should be used with ORB when ``WTA_K==3`` or ``4`` (see ORB::ORB constructor description).
:param crossCheck: If it is false, this is will be default BFMatcher behaviour when it finds the k nearest neighbors for each query descriptor. If ``crossCheck==true``, then the ``knnMatch()`` method with ``k=1`` will only return pairs ``(i,j)`` such that for ``i-th`` query descriptor the ``j-th`` descriptor in the matcher's collection is the nearest and vice versa, i.e. the ``BFMathcher`` will only return consistent pairs. Such technique usually produces best results with minimal number of outliers when there are enough matches. This is alternative to the ratio test, used by D. Lowe in SIFT paper.
modules/features2d/doc/common_interfaces_of_feature_detectors.rst
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@@ -415,7 +415,7 @@ DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector
----------------------------------------------------------------
The constructor
.. ocv:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjaster, int min_features=400, int max_features=500, int max_iters=5 )
.. ocv:function:: DynamicAdaptedFeatureDetector::DynamicAdaptedFeatureDetector( const Ptr<AdjusterAdapter>& adjuster, int min_features=400, int max_features=500, int max_iters=5 )
:param adjuster: :ocv:class:`AdjusterAdapter` that detects features and adjusts parameters.
modules/features2d/doc/drawing_function_of_keypoints_and_matches.rst
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@@ -71,7 +71,7 @@ Draws keypoints.
:param keypoints: Keypoints from the source image.
:param outImg: Output image. Its content depends on the ``flags`` value defining what is drawn in the output image. See possible ``flags`` bit values below.
:param outImage: Output image. Its content depends on the ``flags`` value defining what is drawn in the output image. See possible ``flags`` bit values below.
:param color: Color of keypoints.