Commit ad6c87b0 authored by Davis King's avatar Davis King

Merge github.com:davisking/dlib

parents 1ab34825 d4cbaecd
......@@ -21,3 +21,4 @@ a6c2b16111b8023dbded7299dcc7e6acd26671b8 v18.8
4de62892e10850e8f0205b4857cf48b31fd730c8 v18.9
5a14394843c04628990857e5db94ff6bc43c2da0 v18.10
dd8e950033d5026373acce9ed4b2ffb85908d3b5 v18.11
4e3941b13ca859f788853cfcef9973ac4b161e65 v18.12
......@@ -12,6 +12,9 @@ set(CMAKE_LEGACY_CYGWIN_WIN32 0) # Remove when CMake >= 2.8.4 is required
# Suppress cmake warnings about changes in new versions.
if(COMMAND cmake_policy)
cmake_policy(SET CMP0003 NEW)
if (POLICY CMP0054)
cmake_policy(SET CMP0054 NEW)
endif()
endif()
......
......@@ -20,10 +20,13 @@
# A list of various paths you need to search on windows since people install
# boost in a bunch of different places.
set(CMAKE_PREFIX_PATH ${CMAKE_PREFIX_PATH}
"C:/local/boost_1_*"
"C:/Program Files (x86)/boost/boost_1_*"
"C:/Program Files/boost/boost_1_*")
set(BOOST_LIBRARYDIR "C:/local/boost_1_*/lib32-msvc-*")
C:/local/boost_*
C:/Program\ Files\ \(x86\)/boost/boost_*
C:/Program\ Files/boost/boost_*
)
set(BOOST_LIBRARYDIR ${BOOST_LIBRARYDIR} $ENV{BOOST_LIBRARYDIR}
C:/local/boost_*/lib32-msvc-*
)
......@@ -32,8 +35,10 @@ set(BOOST_LIBRARYDIR "C:/local/boost_1_*/lib32-msvc-*")
#SET(Boost_USE_STATIC_RUNTIME OFF)
set(Boost_NO_BOOST_CMAKE ON)
set(BOOST_LIBRARYDIR /usr/lib/x86_64-linux-gnu/)
if (NOT WIN32)
set(BOOST_LIBRARYDIR ${BOOST_LIBRARYDIR} $ENV{BOOST_LIBRARYDIR}
/usr/lib/x86_64-linux-gnu/)
endif()
if (PYTHON3)
FIND_PACKAGE(Boost 1.41.0 COMPONENTS python-py34 REQUIRED)
FIND_PACKAGE(PythonLibs 3.4 REQUIRED)
......
......@@ -3,6 +3,9 @@ cmake_minimum_required(VERSION 2.6.4)
set(CMAKE_LEGACY_CYGWIN_WIN32 0) # Remove when CMake >= 2.8.4 is required
if (POLICY CMP0054)
cmake_policy(SET CMP0054 NEW)
endif()
# Don't add dlib if it's already been added to the cmake project
if (NOT TARGET dlib)
......
......@@ -315,10 +315,6 @@ namespace dlib
unsigned long num_parts (
) const
/*!
ensures
- returns the number of points in the shape
!*/
{
return initial_shape.size()/2;
}
......@@ -328,13 +324,6 @@ namespace dlib
const image_type& img,
const rectangle& rect
) const
/*!
ensures
- runs the tree regressor on the detection rect inside img and returns a
full_object_detection DET such that:
- DET.get_rect() == rect
- DET.num_parts() == num_parts()
!*/
{
using namespace impl;
matrix<float,0,1> current_shape = initial_shape;
......
......@@ -270,7 +270,7 @@ namespace dlib
of the box. So a padding of 0.5 would cause the algorithm to sample
pixels from a box that was 2x2, effectively multiplying the area pixels
are sampled from by 4. Similarly, setting the padding to -0.2 would
cause it to sample from a box 0.8x0.8 in size.
cause it to sample from a box 0.6x0.6 in size.
!*/
void set_feature_pool_region_padding (
......
......@@ -1621,7 +1621,7 @@ namespace dlib
}
// now make an image pyramid
dlib::array<image_type1> levels(max_depth);
dlib::array<image_type2> levels(max_depth);
if (levels.size() != 0)
pyr(img,levels[0]);
for (unsigned long i = 1; i < levels.size(); ++i)
......
......@@ -6,6 +6,7 @@
#include "../pixel.h"
#include "thresholding.h"
#include "morphological_operations_abstract.h"
#include "assign_image.h"
namespace dlib
{
......@@ -662,6 +663,182 @@ namespace dlib
}
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
namespace impl
{
template <typename image_type>
inline bool should_remove_pixel (
const image_type& img,
long r,
long c,
int iter
)
{
unsigned int p2 = img[r-1][c];
unsigned int p3 = img[r-1][c+1];
unsigned int p4 = img[r][c+1];
unsigned int p5 = img[r+1][c+1];
unsigned int p6 = img[r+1][c];
unsigned int p7 = img[r+1][c-1];
unsigned int p8 = img[r][c-1];
unsigned int p9 = img[r-1][c-1];
int A = (p2 == 0 && p3 == 255) + (p3 == 0 && p4 == 255) +
(p4 == 0 && p5 == 255) + (p5 == 0 && p6 == 255) +
(p6 == 0 && p7 == 255) + (p7 == 0 && p8 == 255) +
(p8 == 0 && p9 == 255) + (p9 == 0 && p2 == 255);
int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
int m1 = iter == 0 ? (p2 * p4 * p6) : (p2 * p4 * p8);
int m2 = iter == 0 ? (p4 * p6 * p8) : (p2 * p6 * p8);
// Decide if we should remove the pixel img[r][c].
return (A == 1 && (B >= 2*255 && B <= 6*255) && m1 == 0 && m2 == 0);
}
template <typename image_type>
inline void add_to_remove (
std::vector<point>& to_remove,
array2d<unsigned char>& marker,
const image_type& img,
long r,
long c,
int iter
)
{
if (marker[r][c]&&should_remove_pixel(img,r,c,iter))
{
to_remove.push_back(point(c,r));
marker[r][c] = 0;
}
}
template <typename image_type>
inline bool is_bw_border_pixel(
const image_type& img,
long r,
long c
)
{
unsigned int p2 = img[r-1][c];
unsigned int p3 = img[r-1][c+1];
unsigned int p4 = img[r][c+1];
unsigned int p5 = img[r+1][c+1];
unsigned int p6 = img[r+1][c];
unsigned int p7 = img[r+1][c-1];
unsigned int p8 = img[r][c-1];
unsigned int p9 = img[r-1][c-1];
int B = p2 + p3 + p4 + p5 + p6 + p7 + p8 + p9;
// If you are on but at least one of your neighbors isn't.
return B<8*255 && img[r][c];
}
inline void add_if(
std::vector<point>& to_check2,
const array2d<unsigned char>& marker,
long c,
long r
)
{
if (marker[r][c])
to_check2.push_back(point(c,r));
}
} // end namespace impl
// ----------------------------------------------------------------------------------------
template <
typename image_type
>
void skeleton(
image_type& img_
)
{
/*
The implementation of this function is based on the paper
"A fast parallel algorithm for thinning digital patterns” by T.Y. Zhang and C.Y. Suen.
and also the excellent discussion of it at:
http://opencv-code.com/quick-tips/implementation-of-thinning-algorithm-in-opencv/
*/
typedef typename image_traits<image_type>::pixel_type pixel_type;
// This function only works on grayscale images
COMPILE_TIME_ASSERT(pixel_traits<pixel_type>::grayscale);
using namespace impl;
// Note that it's important to zero the border for 2 reasons. First, it allows
// thinning to being at the border of the image. But more importantly, it causes
// the mask to have a border of 0 pixels as well which we use later to avoid
// indexing outside the image inside add_to_remove().
zero_border_pixels(img_,1,1);
image_view<image_type> img(img_);
// We use the marker to keep track of pixels we have committed to removing but
// haven't yet removed from img.
array2d<unsigned char> marker(img.nr(), img.nc());
assign_image(marker, img);
// Begin by making a list of the pixels on the borders of binary blobs.
std::vector<point> to_remove, to_check, to_check2;
for (int r = 1; r < img.nr()-1; r++)
{
for (int c = 1; c < img.nc()-1; c++)
{
if (is_bw_border_pixel(img, r, c))
{
to_check.push_back(point(c,r));
}
}
}
// Now start iteratively looking at the border pixels and removing them.
while(to_check.size() != 0)
{
for (int iter = 0; iter <= 1; ++iter)
{
// Check which pixels we should remove
to_remove.clear();
for (unsigned long i = 0; i < to_check.size(); ++i)
{
long r = to_check[i].y();
long c = to_check[i].x();
add_to_remove(to_remove, marker, img, r, c, iter);
}
for (unsigned long i = 0; i < to_check2.size(); ++i)
{
long r = to_check2[i].y();
long c = to_check2[i].x();
add_to_remove(to_remove, marker, img, r, c, iter);
}
// Now remove those pixels. Also add their neighbors into the "to check"
// pixel list for the next iteration.
for (unsigned long i = 0; i < to_remove.size(); ++i)
{
long r = to_remove[i].y();
long c = to_remove[i].x();
// remove the pixel
img[r][c] = 0;
add_if(to_check2, marker, c-1, r-1);
add_if(to_check2, marker, c, r-1);
add_if(to_check2, marker, c+1, r-1);
add_if(to_check2, marker, c-1, r);
add_if(to_check2, marker, c+1, r);
add_if(to_check2, marker, c-1, r+1);
add_if(to_check2, marker, c, r+1);
add_if(to_check2, marker, c+1, r+1);
}
}
to_check.clear();
to_check.swap(to_check2);
}
}
// ----------------------------------------------------------------------------------------
// ----------------------------------------------------------------------------------------
}
......
......@@ -283,6 +283,30 @@ namespace dlib
- calls binary_complement(img,img);
!*/
// ----------------------------------------------------------------------------------------
template <
typename image_type
>
void skeleton(
image_type& img
);
/*!
requires
- image_type is an object that implement the interface defined in
dlib/image_processing/generic_image.h
- img must contain a grayscale pixel type.
- all pixels in img are set to either on_pixel or off_pixel.
(i.e. it must be a binary image)
ensures
- This function computes the skeletonization of img and stores the result in
#img. That is, given a binary image, we progressively thin the binary blobs
(composed of on_pixel values) until only a single pixel wide skeleton of the
original blobs remains.
- #img.nc() == img.nc()
- #img.nr() == img.nr()
!*/
// ----------------------------------------------------------------------------------------
}
......
......@@ -1217,7 +1217,7 @@ namespace dlib
typename in_image_type,
typename out_image_type
>
void gaussian_blur (
rectangle gaussian_blur (
const in_image_type& in_img,
out_image_type& out_img,
double sigma = 1,
......@@ -1241,7 +1241,7 @@ namespace dlib
ptype scale = sum(filt);
scale = scale*scale;
spatially_filter_image_separable(in_img, out_img, filt, filt, scale);
return spatially_filter_image_separable(in_img, out_img, filt, filt, scale);
}
......
......@@ -353,7 +353,7 @@ namespace dlib
typename in_image_type,
typename out_image_type
>
void gaussian_blur (
rectangle gaussian_blur (
const in_image_type& in_img,
out_image_type& out_img,
double sigma = 1,
......@@ -384,6 +384,8 @@ namespace dlib
inside the image are set to zero.
- #out_img.nc() == in_img.nc()
- #out_img.nr() == in_img.nr()
- returns a rectangle which indicates what pixels in #out_img are considered
non-border pixels and therefore contain output from the filter.
!*/
// ----------------------------------------------------------------------------------------
......
# This file figured out where MATLAB is and then defines a macro, add_mex_function(name)
# This file figures out where MATLAB is and then defines a macro, add_mex_function(name)
# which when called instructs CMake to build a mex file from a file called name.cpp. Note
# that additional library dependencies can be added like this: add_mex_function(name lib1 dlib libetc).
# That is, just add more libraries after the name and they will be build into the mex file.
......
// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
#include "call_matlab.h"
#include "dlib/matrix.h"
......
// The contents of this file are in the public domain. See LICENSE_FOR_EXAMPLE_PROGRAMS.txt
#include "dlib/matrix.h"
using namespace dlib;
......
// Copyright (C) 2012 Massachusetts Institute of Technology, Lincoln Laboratory
// License: Boost Software License See LICENSE.txt for the full license.
// Authors: Davis E. King (davis@dlib.net)
/*
READ THIS FIRST
######
......
......@@ -1800,6 +1800,16 @@ namespace
for (int i = 0; i < 100; ++i)
test_separable_filtering_center<float>(rnd);
{
print_spinner();
matrix<unsigned char> img(40,80);
assign_all_pixels(img, 255);
skeleton(img);
DLIB_TEST(sum(matrix_cast<int>(mat(img)))/255 == 40);
draw_line(img, point(20,19), point(59,19), 00);
DLIB_TEST(sum(matrix_cast<int>(mat(img))) == 0);
}
}
} a;
......
......@@ -161,6 +161,7 @@
<item>suppress_non_maximum_edges</item>
<item>threshold_image</item>
<item>auto_threshold_image</item>
<item>hough_transform</item>
</section>
<section>
......@@ -175,6 +176,7 @@
<item>binary_union</item>
<item>binary_difference</item>
<item>binary_complement</item>
<item>skeleton</item>
</section>
<section>
......@@ -240,7 +242,6 @@
<item>zero_border_pixels</item>
<item>integral_image</item>
<item>integral_image_generic</item>
<item>hough_transform</item>
</section>
......@@ -274,6 +275,20 @@
</component>
<!-- ************************************************************************* -->
<component>
<name>skeleton</name>
<file>dlib/image_transforms.h</file>
<spec_file link="true">dlib/image_transforms/morphological_operations_abstract.h</spec_file>
<description>
This function computes the skeletonization of an image. That is,
given a binary image, we progressively thin the binary blobs
until only a single pixel wide skeleton of the original blobs
remains.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......
......@@ -216,6 +216,7 @@
<li><a href="other.html#serialize">Serialization support</a></li>
<li>Many <a href="other.html#memory_manager">memory manager</a> objects that implement
different memory pooling strategies</li>
<li>A tool that lets you easily <a href="other.html#MATLAB">call C++ from MATLAB</a></li>
</ul>
</li>
</ul>
......
......@@ -103,8 +103,9 @@
</section>
<section>
<name>Testing</name>
<name>Other</name>
<item>dlib_testing_suite</item>
<item>MATLAB</item>
</section>
</top>
......@@ -1008,6 +1009,21 @@
</component>
<!-- ************************************************************************* -->
<component>
<name>MATLAB</name>
<description>
dlib contains a tool that makes it easy to call C++ code from MATLAB. It's
documented in the examples in the dlib/matlab folder. In particular, the
<a href="dlib/matlab/example_mex_function.cpp.html">dlib/matlab/example_mex_function.cpp</a> and
<a href="dlib/matlab/example_mex_callback.cpp.html">dlib/matlab/example_mex_callback.cpp</a> examples.
You can also easily compile these files using CMake. See the instructions in the README file
in the dlib/matlab folder for further details.
</description>
</component>
<!-- ************************************************************************* -->
<component>
......
......@@ -12,12 +12,25 @@
<current>
New Features:
- Upgraded fft() and ifft() to support 2D matrices.
- Added hough_transform
- Added skeleton() for finding the skeletonization of a binary image.
- Added distance_to_line(), clip_line_to_rectangle(), min_point(), and max_point().
- Added a simple API for calling C++ from MATLAB.
Non-Backwards Compatible Changes:
Bug fixes:
- Fixed a compile time error that could happen when calling fft() for
certain input types.
- Fixed a compile time error that prevented auto_threshold_image() from
being used.
- Fixed name clashes with new version of Boost.
- Changed Python pickling code so it works with Python 3.
- Fixed CMake compile time error related to finding fftw.
Other:
- Made extract_image_chips() much faster when extracting unscaled image chips.
</current>
<!-- ************************************************************************************** -->
......
......@@ -676,6 +676,7 @@
<term file="metaprogramming.html" name="DLIB_CASSERT" include="dlib/assert.h"/>
<term file="metaprogramming.html" name="COMPILE_TIME_ASSERT" include="dlib/assert.h"/>
<term file="metaprogramming.html" name="DLIB_ASSERT_HAS_STANDARD_LAYOUT" include="dlib/assert.h"/>
<term file="other.html" name="MATLAB" />
<term file="other.html" name="TIME_THIS" include="dlib/time_this.h"/>
<term link="other.html#timing code blocks" name="print" include="dlib/timing.h"/>
<term file="other.html" name="timing code blocks" include="dlib/timing.h"/>
......@@ -1151,6 +1152,7 @@
<term file="containers.html" name="tuple" include="dlib/tuple.h"/>
<term file="dlib/type_safe_union/type_safe_union_kernel_abstract.h.html"
name="bad_type_safe_union_cast" include="dlib/type_safe_union.h"/>
<term file="containers.html" name="type_safe_union" include="dlib/type_safe_union.h"/>
<term file="containers.html" name="array2d" include="dlib/array2d.h"/>
......@@ -1287,6 +1289,7 @@
<term file="imaging.html" name="integral_image" include="dlib/image_transforms.h"/>
<term file="imaging.html" name="integral_image_generic" include="dlib/image_transforms.h"/>
<term file="imaging.html" name="hough_transform" include="dlib/image_transforms.h"/>
<term file="imaging.html" name="skeleton" include="dlib/image_transforms.h"/>
<term file="imaging.html" name="hessian_pyramid" include="dlib/image_keypoint.h"/>
<term file="imaging.html" name="compute_dominant_angle" include="dlib/image_keypoint.h"/>
<term file="imaging.html" name="draw_surf_points" include="dlib/image_keypoint/draw_surf_points.h"/>
......
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