dlib C++ Library - setup_hashed_features_abstract.h

// 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_