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Diffstat (limited to 'ml/dlib/dlib/image_processing/setup_hashed_features_abstract.h')
| -rw-r--r-- | ml/dlib/dlib/image_processing/setup_hashed_features_abstract.h | 210 |
1 files changed, 210 insertions, 0 deletions
diff --git a/ml/dlib/dlib/image_processing/setup_hashed_features_abstract.h b/ml/dlib/dlib/image_processing/setup_hashed_features_abstract.h new file mode 100644 index 000000000..886411cd4 --- /dev/null +++ b/ml/dlib/dlib/image_processing/setup_hashed_features_abstract.h @@ -0,0 +1,210 @@ +// 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 <typename fe, typename hash> class feature_image + > + void setup_hashed_features ( + scan_image_pyramid<pyramid, feature_image<feature_extractor, projection_hash> >& 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 <typename fe, typename hash> class feature_image + > + void setup_hashed_features ( + scan_image_pyramid<pyramid, feature_image<feature_extractor, projection_hash> >& 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 <typename fe, typename hash> class feature_image + typename box_generator + > + void setup_hashed_features ( + scan_image_boxes<feature_image<feature_extractor, projection_hash>,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 <typename fe, typename hash> class feature_image + typename box_generator + > + void setup_hashed_features ( + scan_image_boxes<feature_image<feature_extractor, projection_hash>,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_ + + |