// Copyright (C) 2011 Davis E. King (davis@dlib.net) // License: Boost Software License See LICENSE.txt for the full license. #undef DLIB_SETUP_HAShED_FEATURES_ABSTRACT_Hh_ #ifdef DLIB_SETUP_HAShED_FEATURES_ABSTRACT_Hh_ #include "scan_image_pyramid_abstract.h" #include "scan_image_boxes_abstract.h" #include "../lsh/projection_hash_abstract.h" #include "../image_keypoint/hashed_feature_image_abstract.h" #include "../image_keypoint/binned_vector_feature_image_abstract.h" namespace dlib { // ---------------------------------------------------------------------------------------- class image_hash_construction_failure : public error { /*! WHAT THIS OBJECT REPRESENTS This is the exception object used by the routines in this file. !*/ }; // ---------------------------------------------------------------------------------------- template < typename image_scanner > void use_uniform_feature_weights ( image_scanner& scanner ); /*! requires - image_scanner should be either scan_image_pyramid or scan_image_boxes and should use the hashed_feature_image as its local feature extractor. ensures - #scanner.get_feature_extractor().uses_uniform_feature_weights() == true (i.e. Make the scanner's feature extractor use the uniform feature weighting scheme) !*/ // ---------------------------------------------------------------------------------------- template < typename image_scanner > void use_relative_feature_weights ( image_scanner& scanner ); /*! requires - image_scanner should be either scan_image_pyramid or scan_image_boxes and should use the hashed_feature_image as its local feature extractor. ensures - #scanner.get_feature_extractor().uses_uniform_feature_weights() == false (i.e. Make the scanner's feature extractor use the relative feature weighting scheme) !*/ // ---------------------------------------------------------------------------------------- template < typename image_array, typename pyramid, typename feature_extractor template class feature_image > void setup_hashed_features ( scan_image_pyramid >& scanner, const image_array& images, const feature_extractor& fe, int bits, unsigned long num_samples = 200000 ); /*! requires - 0 < bits <= 32 - num_samples > 1 - images.size() > 0 - it must be valid to pass images[0] into scanner.load(). (also, image_array must be an implementation of dlib/array/array_kernel_abstract.h) - feature_image == must be either hashed_feature_image, binned_vector_feature_image, or a type with a compatible interface. ensures - Creates a projection_hash suitable for hashing the feature vectors produced by fe and then configures scanner to use this hash function. - The hash function will map vectors into integers in the range [0, pow(2,bits)) - The hash function will be setup so that it hashes a random sample of num_samples vectors from fe such that each bin ends up with roughly the same number of elements in it. throws - image_hash_construction_failure This exception is thrown if there is a problem creating the projection_hash. This should only happen the images are so small they contain less than 2 feature vectors. !*/ // ---------------------------------------------------------------------------------------- template < typename image_array, typename pyramid, typename feature_extractor template class feature_image > void setup_hashed_features ( scan_image_pyramid >& scanner, const image_array& images, int bits, unsigned long num_samples = 200000 ); /*! requires - 0 < bits <= 32 - num_samples > 1 - images.size() > 0 - it must be valid to pass images[0] into scanner.load(). (also, image_array must be an implementation of dlib/array/array_kernel_abstract.h) - feature_image == must be either hashed_feature_image, binned_vector_feature_image, or a type with a compatible interface. ensures - performs: setup_hashed_features(scanner, images, feature_extractor(), bits, num_samples) throws - image_hash_construction_failure This exception is thrown if there is a problem creating the projection_hash. This should only happen the images are so small they contain less than 2 feature vectors. !*/ // ---------------------------------------------------------------------------------------- // ---------------------------------------------------------------------------------------- // ---------------------------------------------------------------------------------------- // ---------------------------------------------------------------------------------------- template < typename image_array, typename feature_extractor, template class feature_image typename box_generator > void setup_hashed_features ( scan_image_boxes,box_generator>& scanner, const image_array& images, const feature_extractor& fe, int bits, unsigned long num_samples = 200000 ); /*! requires - 0 < bits <= 32 - num_samples > 1 - images.size() > 0 - it must be valid to pass images[0] into scanner.load(). (also, image_array must be an implementation of dlib/array/array_kernel_abstract.h) - feature_image == must be either hashed_feature_image, binned_vector_feature_image, or a type with a compatible interface. ensures - Creates a projection_hash suitable for hashing the feature vectors produced by fe and then configures scanner to use this hash function. - The hash function will map vectors into integers in the range [0, pow(2,bits)) - The hash function will be setup so that it hashes a random sample of num_samples vectors from fe such that each bin ends up with roughly the same number of elements in it. throws - image_hash_construction_failure This exception is thrown if there is a problem creating the projection_hash. This should only happen the images are so small they contain less than 2 feature vectors. !*/ // ---------------------------------------------------------------------------------------- template < typename image_array, typename feature_extractor, template class feature_image typename box_generator > void setup_hashed_features ( scan_image_boxes,box_generator>& scanner, const image_array& images, int bits, unsigned long num_samples = 200000 ); /*! requires - 0 < bits <= 32 - num_samples > 1 - images.size() > 0 - it must be valid to pass images[0] into scanner.load(). (also, image_array must be an implementation of dlib/array/array_kernel_abstract.h) - feature_image == must be either hashed_feature_image, binned_vector_feature_image, or a type with a compatible interface. ensures - performs: setup_hashed_features(scanner, images, feature_extractor(), bits, num_samples) throws - image_hash_construction_failure This exception is thrown if there is a problem creating the projection_hash. This should only happen the images are so small they contain less than 2 feature vectors. !*/ // ---------------------------------------------------------------------------------------- } #endif // DLIB_SETUP_HAShED_FEATURES_ABSTRACT_Hh_