Beispiel #1
0
        void DoProcess()
        {
            if (!(owner.Value is OpenCVForUnityPlayMakerActions.SIFT))
            {
                LogError("owner is not initialized. Add Action \"newSIFT\".");
                return;
            }
            OpenCVForUnity.Features2dModule.SIFT wrapped_owner = OpenCVForUnityPlayMakerActionsUtils.GetWrappedObject <OpenCVForUnityPlayMakerActions.SIFT, OpenCVForUnity.Features2dModule.SIFT>(owner);

            storeResult.Value = wrapped_owner.getDefaultName();
        }
Beispiel #2
0
        //
        // C++: static Ptr_SIFT cv::SIFT::create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
        //

        /**
         * Create SIFT with specified descriptorType.
         *     param nfeatures The number of best features to retain. The features are ranked by their scores
         *     (measured in SIFT algorithm as the local contrast)
         *
         *     param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
         *     number of octaves is computed automatically from the image resolution.
         *
         *     param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
         *     (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
         *
         *     <b>Note:</b> The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
         *     nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
         *     this argument to 0.09.
         *
         *     param edgeThreshold The threshold used to filter out edge-like features. Note that the its meaning
         *     is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
         *     filtered out (more features are retained).
         *
         *     param sigma The sigma of the Gaussian applied to the input image at the octave \#0. If your image
         *     is captured with a weak camera with soft lenses, you might want to reduce the number.
         *
         *     param descriptorType The type of descriptors. Only CV_32F and CV_8U are supported.
         * return automatically generated
         */
        public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold, double edgeThreshold, double sigma, int descriptorType)
        {
            return(SIFT.__fromPtr__(features2d_SIFT_create_10(nfeatures, nOctaveLayers, contrastThreshold, edgeThreshold, sigma, descriptorType)));
        }
Beispiel #3
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 /**
  *     (measured in SIFT algorithm as the local contrast)
  *
  *     number of octaves is computed automatically from the image resolution.
  *
  *     (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
  *
  *     <b>Note:</b> The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
  *     nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
  *     this argument to 0.09.
  *
  *     is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
  *     filtered out (more features are retained).
  *
  *     is captured with a weak camera with soft lenses, you might want to reduce the number.
  * return automatically generated
  */
 public static SIFT create()
 {
     return(SIFT.__fromPtr__(features2d_SIFT_create_16()));
 }
Beispiel #4
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 /**
  * param nfeatures The number of best features to retain. The features are ranked by their scores
  *     (measured in SIFT algorithm as the local contrast)
  *
  *     number of octaves is computed automatically from the image resolution.
  *
  *     (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
  *
  *     <b>Note:</b> The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
  *     nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
  *     this argument to 0.09.
  *
  *     is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
  *     filtered out (more features are retained).
  *
  *     is captured with a weak camera with soft lenses, you might want to reduce the number.
  * return automatically generated
  */
 public static SIFT create(int nfeatures)
 {
     return(SIFT.__fromPtr__(features2d_SIFT_create_15(nfeatures)));
 }
Beispiel #5
0
 /**
  * param nfeatures The number of best features to retain. The features are ranked by their scores
  *     (measured in SIFT algorithm as the local contrast)
  *
  *     param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
  *     number of octaves is computed automatically from the image resolution.
  *
  *     (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
  *
  *     <b>Note:</b> The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
  *     nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
  *     this argument to 0.09.
  *
  *     is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
  *     filtered out (more features are retained).
  *
  *     is captured with a weak camera with soft lenses, you might want to reduce the number.
  * return automatically generated
  */
 public static SIFT create(int nfeatures, int nOctaveLayers)
 {
     return(SIFT.__fromPtr__(features2d_SIFT_create_14(nfeatures, nOctaveLayers)));
 }
Beispiel #6
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 /**
  * param nfeatures The number of best features to retain. The features are ranked by their scores
  *     (measured in SIFT algorithm as the local contrast)
  *
  *     param nOctaveLayers The number of layers in each octave. 3 is the value used in D. Lowe paper. The
  *     number of octaves is computed automatically from the image resolution.
  *
  *     param contrastThreshold The contrast threshold used to filter out weak features in semi-uniform
  *     (low-contrast) regions. The larger the threshold, the less features are produced by the detector.
  *
  *     <b>Note:</b> The contrast threshold will be divided by nOctaveLayers when the filtering is applied. When
  *     nOctaveLayers is set to default and if you want to use the value used in D. Lowe paper, 0.03, set
  *     this argument to 0.09.
  *
  *     is different from the contrastThreshold, i.e. the larger the edgeThreshold, the less features are
  *     filtered out (more features are retained).
  *
  *     is captured with a weak camera with soft lenses, you might want to reduce the number.
  * return automatically generated
  */
 public static SIFT create(int nfeatures, int nOctaveLayers, double contrastThreshold)
 {
     return(SIFT.__fromPtr__(features2d_SIFT_create_13(nfeatures, nOctaveLayers, contrastThreshold)));
 }
Beispiel #7
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 public SIFT(OpenCVForUnity.Features2dModule.SIFT nativeObj) : base(nativeObj)
 {
 }