SIFT feature detector and descriptor extractor.  
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| AFAPI void | sift (features &feat, array &desc, const array &in, const unsigned n_layers=3, const float contrast_thr=0.04f, const float edge_thr=10.f, const float init_sigma=1.6f, const bool double_input=true, const float intensity_scale=0.00390625f, const float feature_ratio=0.05f) | 
|  | C++ Interface for SIFT feature detector and descriptor.  More... 
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| AFAPI void | gloh (features &feat, array &desc, const array &in, const unsigned n_layers=3, const float contrast_thr=0.04f, const float edge_thr=10.f, const float init_sigma=1.6f, const bool double_input=true, const float intensity_scale=0.00390625f, const float feature_ratio=0.05f) | 
|  | C++ Interface for SIFT feature detector and GLOH descriptor.  More... 
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| AFAPI af_err | af_sift (af_features *feat, af_array *desc, const af_array in, const unsigned n_layers, const float contrast_thr, const float edge_thr, const float init_sigma, const bool double_input, const float intensity_scale, const float feature_ratio) | 
|  | C++ Interface for SIFT feature detector and descriptor.  More... 
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| AFAPI af_err | af_gloh (af_features *feat, af_array *desc, const af_array in, const unsigned n_layers, const float contrast_thr, const float edge_thr, const float init_sigma, const bool double_input, const float intensity_scale, const float feature_ratio) | 
|  | C++ Interface for SIFT feature detector and GLOH descriptor.  More... 
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SIFT feature detector and descriptor extractor. 
Detects features and extract descriptors using the Scale Invariant Feature Transform (SIFT), by David Lowe.
Lowe, D. G., "Distinctive Image Features from Scale-Invariant Keypoints", International Journal of Computer Vision, 60, 2, pp. 91-110, 2004.
WARNING: The SIFT algorithm is patented by the University of British Columbia, before using it, make sure you have the appropriate permission to do so. 
      
        
          | AFAPI af_err af_gloh | ( | af_features * | feat, | 
        
          |  |  | af_array * | desc, | 
        
          |  |  | const af_array | in, | 
        
          |  |  | const unsigned | n_layers, | 
        
          |  |  | const float | contrast_thr, | 
        
          |  |  | const float | edge_thr, | 
        
          |  |  | const float | init_sigma, | 
        
          |  |  | const bool | double_input, | 
        
          |  |  | const float | intensity_scale, | 
        
          |  |  | const float | feature_ratio | 
        
          |  | ) |  |  | 
      
 
C++ Interface for SIFT feature detector and GLOH descriptor. 
- Parameters
- 
  
    | [out] | feat | af_features object composed of arrays for x and y coordinates, score, orientation and size of selected features |  | [out] | desc | Nx272 array containing extracted GLOH descriptors, where N is the number of features found by SIFT |  | [in] | in | array containing a grayscale image (color images are not supported) |  | [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |  | [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |  | [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |  | [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |  | [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |  | [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |  | [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |  
 
 
 
      
        
          | AFAPI af_err af_sift | ( | af_features * | feat, | 
        
          |  |  | af_array * | desc, | 
        
          |  |  | const af_array | in, | 
        
          |  |  | const unsigned | n_layers, | 
        
          |  |  | const float | contrast_thr, | 
        
          |  |  | const float | edge_thr, | 
        
          |  |  | const float | init_sigma, | 
        
          |  |  | const bool | double_input, | 
        
          |  |  | const float | intensity_scale, | 
        
          |  |  | const float | feature_ratio | 
        
          |  | ) |  |  | 
      
 
C++ Interface for SIFT feature detector and descriptor. 
- Parameters
- 
  
    | [out] | feat | af_features object composed of arrays for x and y coordinates, score, orientation and size of selected features |  | [out] | desc | Nx128 array containing extracted descriptors, where N is the number of features found by SIFT |  | [in] | in | array containing a grayscale image (color images are not supported) |  | [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |  | [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |  | [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |  | [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |  | [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |  | [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |  | [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |  
 
 
 
      
        
          | AFAPI void af::gloh | ( | features & | feat, | 
        
          |  |  | array & | desc, | 
        
          |  |  | const array & | in, | 
        
          |  |  | const unsigned | n_layers = 3, | 
        
          |  |  | const float | contrast_thr = 0.04f, | 
        
          |  |  | const float | edge_thr = 10.f, | 
        
          |  |  | const float | init_sigma = 1.6f, | 
        
          |  |  | const bool | double_input = true, | 
        
          |  |  | const float | intensity_scale = 0.00390625f, | 
        
          |  |  | const float | feature_ratio = 0.05f | 
        
          |  | ) |  |  | 
      
 
C++ Interface for SIFT feature detector and GLOH descriptor. 
- Parameters
- 
  
    | [out] | feat | features object composed of arrays for x and y coordinates, score, orientation and size of selected features |  | [out] | desc | Nx272 array containing extracted GLOH descriptors, where N is the number of features found by SIFT |  | [in] | in | array containing a grayscale image (color images are not supported) |  | [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |  | [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |  | [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |  | [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |  | [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |  | [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |  | [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |  
 
 
 
      
        
          | AFAPI void af::sift | ( | features & | feat, | 
        
          |  |  | array & | desc, | 
        
          |  |  | const array & | in, | 
        
          |  |  | const unsigned | n_layers = 3, | 
        
          |  |  | const float | contrast_thr = 0.04f, | 
        
          |  |  | const float | edge_thr = 10.f, | 
        
          |  |  | const float | init_sigma = 1.6f, | 
        
          |  |  | const bool | double_input = true, | 
        
          |  |  | const float | intensity_scale = 0.00390625f, | 
        
          |  |  | const float | feature_ratio = 0.05f | 
        
          |  | ) |  |  | 
      
 
C++ Interface for SIFT feature detector and descriptor. 
- Parameters
- 
  
    | [out] | feat | features object composed of arrays for x and y coordinates, score, orientation and size of selected features |  | [out] | desc | Nx128 array containing extracted descriptors, where N is the number of features found by SIFT |  | [in] | in | array containing a grayscale image (color images are not supported) |  | [in] | n_layers | number of layers per octave, the number of octaves is computed automatically according to the input image dimensions, the original SIFT paper suggests 3 |  | [in] | contrast_thr | threshold used to filter out features that have low contrast, the original SIFT paper suggests 0.04 |  | [in] | edge_thr | threshold used to filter out features that are too edge-like, the original SIFT paper suggests 10.0 |  | [in] | init_sigma | the sigma value used to filter the input image at the first octave, the original SIFT paper suggests 1.6 |  | [in] | double_input | if true, the input image dimensions will be doubled and the doubled image will be used for the first octave |  | [in] | intensity_scale | the inverse of the difference between the minimum and maximum grayscale intensity value, e.g.: if the ranges are 0-256, the proper intensity_scale value is 1/256, if the ranges are 0-1, the proper intensity-scale value is 1/1 |  | [in] | feature_ratio | maximum ratio of features to detect, the maximum number of features is calculated by feature_ratio * in.elements(). The maximum number of features is not based on the score, instead, features detected after the limit is reached are discarded |