diff options
Diffstat (limited to 'ml/dlib/dlib/image_transforms/segment_image_abstract.h')
| -rw-r--r-- | ml/dlib/dlib/image_transforms/segment_image_abstract.h | 126 |
1 files changed, 0 insertions, 126 deletions
diff --git a/ml/dlib/dlib/image_transforms/segment_image_abstract.h b/ml/dlib/dlib/image_transforms/segment_image_abstract.h deleted file mode 100644 index af1af46a1..000000000 --- a/ml/dlib/dlib/image_transforms/segment_image_abstract.h +++ /dev/null @@ -1,126 +0,0 @@ -// Copyright (C) 2011 Davis E. King (davis@dlib.net) -// License: Boost Software License See LICENSE.txt for the full license. -#undef DLIB_SEGMENT_ImAGE_ABSTRACT_Hh_ -#ifdef DLIB_SEGMENT_ImAGE_ABSTRACT_Hh_ - -#include <vector> -#include "../matrix.h" -#include "../image_processing/generic_image.h" - -namespace dlib -{ - -// ---------------------------------------------------------------------------------------- - - template < - typename in_image_type, - typename out_image_type - > - void segment_image ( - const in_image_type& in_img, - out_image_type& out_img, - const double k = 200, - const unsigned long min_size = 10 - ); - /*! - requires - - in_image_type == an image object that implements the interface defined in - dlib/image_processing/generic_image.h - - out_image_type == an image object that implements the interface defined in - dlib/image_processing/generic_image.h - - in_image_type can contain any pixel type with a pixel_traits specialization - or a dlib matrix object representing a row or column vector. - - out_image_type must contain an unsigned integer pixel type. - - is_same_object(in_img, out_img) == false - ensures - - Attempts to segment in_img into regions which have some visual consistency to - them. In particular, this function implements the algorithm described in the - paper: Efficient Graph-Based Image Segmentation by Felzenszwalb and Huttenlocher. - - #out_img.nr() == in_img.nr() - - #out_img.nc() == in_img.nc() - - for all valid r and c: - - #out_img[r][c] == an integer value indicating the identity of the segment - containing the pixel in_img[r][c]. - - The k parameter is a measure used to influence how large the segment regions - will be. Larger k generally results in larger segments being produced. For - a deeper discussion of the k parameter you should consult the above - referenced paper. - - min_size is a lower bound on the size of the output segments. That is, it is - guaranteed that all output segments will have at least min_size pixels in - them (unless the whole image contains fewer than min_size pixels, in this - case the entire image will be put into a single segment). - !*/ - -// ---------------------------------------------------------------------------------------- -// ---------------------------------------------------------------------------------------- -// ---------------------------------------------------------------------------------------- - - template < - typename in_image_type, - typename EXP - > - void find_candidate_object_locations ( - const in_image_type& in_img, - std::vector<rectangle>& rects, - const matrix_exp<EXP>& kvals = linspace(50, 200, 3), - const unsigned long min_size = 20, - const unsigned long max_merging_iterations = 50 - ); - /*! - requires - - in_image_type == an image object that implements the interface defined in - dlib/image_processing/generic_image.h - - is_vector(kvals) == true - - kvals.size() > 0 - ensures - - This function takes an input image and generates a set of candidate - rectangles which are expected to bound any objects in the image. It does - this by running a version of the segment_image() routine on the image and - then reports rectangles containing each of the segments as well as rectangles - containing unions of adjacent segments. The basic idea is described in the - paper: - Segmentation as Selective Search for Object Recognition by Koen E. A. van de Sande, et al. - Note that this function deviates from what is described in the paper slightly. - See the code for details. - - The basic segmentation is performed kvals.size() times, each time with the k - parameter (see segment_image() and the Felzenszwalb paper for details on k) - set to a different value from kvals. - - When doing the basic segmentations prior to any box merging, we discard all - rectangles that have an area < min_size. Therefore, all outputs and - subsequent merged rectangles are built out of rectangles that contain at - least min_size pixels. Note that setting min_size to a smaller value than - you might otherwise be interested in using can be useful since it allows a - larger number of possible merged boxes to be created. - - There are max_merging_iterations rounds of neighboring blob merging. - Therefore, this parameter has some effect on the number of output rectangles - you get, with larger values of the parameter giving more output rectangles. - - This function appends the output rectangles into #rects. This means that any - rectangles in rects before this function was called will still be in there - after it terminates. Note further that #rects will not contain any duplicate - rectangles. That is, for all valid i and j where i != j it will be true - that: - - #rects[i] != rects[j] - !*/ - -// ---------------------------------------------------------------------------------------- - - template < - typename alloc - > - void remove_duplicates ( - std::vector<rectangle,alloc>& rects - ); - /*! - ensures - - This function finds any duplicate rectangles in rects and removes the extra - instances. This way, the result is that rects contains only unique rectangle - instances. - !*/ - -// ---------------------------------------------------------------------------------------- - -} - -#endif // DLIB_SEGMENT_ImAGE_ABSTRACT_Hh_ - - |