Deleted all trailing whitespace.
This commit is contained in:
Roman Donchenko
@@ -5,9 +5,9 @@ Detection of planar objects
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.. highlight:: cpp
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The goal of this tutorial is to learn how to use *features2d* and *calib3d* modules for detecting known planar objects in scenes.
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The goal of this tutorial is to learn how to use *features2d* and *calib3d* modules for detecting known planar objects in scenes.
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*Test data*: use images in your data folder, for instance, ``box.png`` and ``box_in_scene.png``.
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*Test data*: use images in your data folder, for instance, ``box.png`` and ``box_in_scene.png``.
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#.
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Create a new console project. Read two input images. ::
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@@ -22,7 +22,7 @@ The goal of this tutorial is to learn how to use *features2d* and *calib3d* modu
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FastFeatureDetector detector(15);
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vector<KeyPoint> keypoints1;
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detector.detect(img1, keypoints1);
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... // do the same for the second image
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#.
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@@ -32,7 +32,7 @@ The goal of this tutorial is to learn how to use *features2d* and *calib3d* modu
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SurfDescriptorExtractor extractor;
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Mat descriptors1;
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extractor.compute(img1, keypoints1, descriptors1);
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... // process keypoints from the second image as well
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#.
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@@ -69,4 +69,4 @@ The goal of this tutorial is to learn how to use *features2d* and *calib3d* modu
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perspectiveTransform(Mat(points1), points1Projected, H);
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#.
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Use ``drawMatches`` for drawing inliers.
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Use ``drawMatches`` for drawing inliers.
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@@ -5,166 +5,166 @@
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Learn about how to use the feature points detectors, descriptors and matching framework found inside OpenCV.
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.. include:: ../../definitions/tocDefinitions.rst
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.. include:: ../../definitions/tocDefinitions.rst
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|Harris| **Title:** :ref:`harris_detector`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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Why is it a good idea to track corners? We learn to use the Harris method to detect corners
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===================== ==============================================
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.. |Harris| image:: images/trackingmotion/Harris_Detector_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|ShiTomasi| **Title:** :ref:`good_features_to_track`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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Where we use an improved method to detect corners more accuratelyI
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===================== ==============================================
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.. |ShiTomasi| image:: images/trackingmotion/Shi_Tomasi_Detector_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|GenericCorner| **Title:** :ref:`generic_corner_detector`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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Here you will learn how to use OpenCV functions to make your personalized corner detector!
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===================== ==============================================
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.. |GenericCorner| image:: images/trackingmotion/Generic_Corner_Detector_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|Subpixel| **Title:** :ref:`corner_subpixeles`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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Is pixel resolution enough? Here we learn a simple method to improve our accuracy.
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===================== ==============================================
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.. |Subpixel| image:: images/trackingmotion/Corner_Subpixeles_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|FeatureDetect| **Title:** :ref:`feature_detection`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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In this tutorial, you will use *features2d* to detect interest points.
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===================== ==============================================
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.. |FeatureDetect| image:: images/Feature_Detection_Tutorial_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|FeatureDescript| **Title:** :ref:`feature_description`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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In this tutorial, you will use *features2d* to calculate feature vectors.
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===================== ==============================================
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.. |FeatureDescript| image:: images/Feature_Description_Tutorial_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|FeatureFlann| **Title:** :ref:`feature_flann_matcher`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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In this tutorial, you will use the FLANN library to make a fast matching.
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===================== ==============================================
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.. |FeatureFlann| image:: images/Feature_Flann_Matcher_Tutorial_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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===================== ==============================================
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|FeatureHomo| **Title:** :ref:`feature_homography`
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*Compatibility:* > OpenCV 2.0
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*Author:* |Author_AnaH|
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In this tutorial, you will use *features2d* and *calib3d* to detect an object in a scene.
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===================== ==============================================
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.. |FeatureHomo| image:: images/Feature_Homography_Tutorial_Cover.jpg
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:height: 90pt
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:width: 90pt
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.. tabularcolumns:: m{100pt} m{300pt}
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.. cssclass:: toctableopencv
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@@ -175,7 +175,7 @@ Learn about how to use the feature points detectors, descriptors and matching f
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*Author:* |Author_VictorE|
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You will use *features2d* and *calib3d* modules for detecting known planar objects in scenes.
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You will use *features2d* and *calib3d* modules for detecting known planar objects in scenes.
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===================== ==============================================
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