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Feature Detection {#tutorial_feature_detection}
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=================
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@tableofcontents
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@prev_tutorial{tutorial_corner_subpixels}
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@next_tutorial{tutorial_feature_description}
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| -: | :- |
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| Original author | Ana Huamán |
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| Compatibility | OpenCV >= 3.0 |
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Goal
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----
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In this tutorial you will learn how to:
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- Use the @ref cv::FeatureDetector interface in order to find interest points. Specifically:
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- Use the cv::xfeatures2d::SURF and its function cv::xfeatures2d::SURF::detect to perform the
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detection process
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- Use the function @ref cv::drawKeypoints to draw the detected keypoints
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\warning You need the <a href="https://github.com/opencv/opencv_contrib">OpenCV contrib modules</a> to be able to use the SURF features
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(alternatives are ORB, KAZE, ... features).
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Theory
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------
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Code
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----
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@add_toggle_cpp
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp)
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@include samples/cpp/tutorial_code/features2D/feature_detection/SURF_detection_Demo.cpp
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@end_toggle
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@add_toggle_java
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java)
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@include samples/java/tutorial_code/features2D/feature_detection/SURFDetectionDemo.java
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@end_toggle
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@add_toggle_python
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This tutorial code's is shown lines below. You can also download it from
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[here](https://github.com/opencv/opencv/tree/master/samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py)
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@include samples/python/tutorial_code/features2D/feature_detection/SURF_detection_Demo.py
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@end_toggle
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Explanation
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-----------
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Result
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------
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-# Here is the result of the feature detection applied to the `box.png` image:
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-# And here is the result for the `box_in_scene.png` image:
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