// Copyright (C) 2008 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#include <sstream>
#include <string>
#include <cstdlib>
#include <ctime>
#include <dlib/pixel.h>
#include <dlib/array2d.h>
#include <dlib/image_transforms.h>
#include <dlib/image_io.h>
#include <dlib/matrix.h>
#include <dlib/rand.h>
#include <dlib/compress_stream.h>
#include <dlib/base64.h>
#include "tester.h"
namespace
{
using namespace test;
using namespace dlib;
using namespace std;
logger dlog("test.image");
void image_test (
)
/*!
ensures
- runs tests on pixel objects and functions for compliance with the specs
!*/
{
print_spinner();
array2d<unsigned char> img1, img2;
img1.set_size(100,100);
assign_all_pixels(img1,7);
assign_image(img2, img1);
DLIB_TEST_MSG(img1.nr() == 100 && img1.nc() == 100 &&
img2.nr() == 100 && img2.nc() == 100,"");
for (long r = 0; r < img1.nr(); ++r)
{
for (long c = 0; c < img1.nc(); ++c)
{
DLIB_TEST(img1[r][c] == 7);
DLIB_TEST(img2[r][c] == 7);
}
}
img2.clear();
DLIB_TEST(img2.size() == 0);
DLIB_TEST(img2.nr() == 0);
DLIB_TEST(img2.nc() == 0);
assign_image(img2, mat(img1));
DLIB_TEST_MSG(img1.nr() == 100 && img1.nc() == 100 &&
img2.nr() == 100 && img2.nc() == 100,"");
for (long r = 0; r < img1.nr(); ++r)
{
for (long c = 0; c < img1.nc(); ++c)
{
DLIB_TEST(img1[r][c] == 7);
DLIB_TEST(img2[r][c] == 7);
}
}
threshold_image(img1, img2, 4);
for (long r = 0; r < img1.nr(); ++r)
{
for (long c = 0; c < img1.nc(); ++c)
{
DLIB_TEST(img1[r][c] == 7);
DLIB_TEST(img2[r][c] == on_pixel);
}
}
{
array2d<hsi_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].h = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].s = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].i = static_cast<unsigned char>(r*14 + c + 3);
}
}
ostringstream sout;
save_dng(img, sout);
istringstream sin(sout.str());
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].h == r*14 + c + 1);
DLIB_TEST(img[r][c].s == r*14 + c + 2);
DLIB_TEST(img[r][c].i == r*14 + c + 3);
}
}
}
{
array2d<rgb_alpha_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
img[r][c].alpha = static_cast<unsigned char>(r*14 + c + 4);
}
}
ostringstream sout;
save_dng(img, sout);
istringstream sin(sout.str());
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
DLIB_TEST(img[r][c].alpha == r*14 + c + 4);
}
}
}
#ifdef DLIB_PNG_SUPPORT
{
array2d<rgb_alpha_pixel> img;
array2d<rgb_pixel> img2, img3;
img.set_size(14,15);
img2.set_size(img.nr(),img.nc());
img3.set_size(img.nr(),img.nc());
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
img[r][c].alpha = static_cast<unsigned char>(r*14 + c + 4);
}
}
save_png(img, "test.png");
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_png(img, "test.png");
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
assign_all_pixels(img2, 255);
assign_all_pixels(img3, 0);
load_png(img2, "test.png");
assign_image(img3, img);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
DLIB_TEST(img[r][c].alpha == r*14 + c + 4);
DLIB_TEST(img2[r][c].red == img3[r][c].red);
DLIB_TEST(img2[r][c].green == img3[r][c].green);
DLIB_TEST(img2[r][c].blue == img3[r][c].blue);
}
}
}
#endif // DLIB_PNG_SUPPORT
{
array2d<rgb_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
}
}
ostringstream sout;
save_dng(img, sout);
save_bmp(img, sout);
save_dng(img, sout);
save_bmp(img, sout);
istringstream sin(sout.str());
for (int i = 0; i < 2; ++i)
{
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_bmp(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST_MSG(img[r][c].red == r*14 + c + 1, "got " << (int)img[r][c].red << " but expected " << r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
}
}
{
array2d<bgr_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
}
}
ostringstream sout;
save_dng(img, sout);
save_bmp(img, sout);
save_dng(img, sout);
save_bmp(img, sout);
istringstream sin(sout.str());
for (int i = 0; i < 2; ++i)
{
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_bmp(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST_MSG(img[r][c].red == r*14 + c + 1, "got " << (int)img[r][c].red << " but expected " << r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
}
}
#ifdef DLIB_PNG_SUPPORT
{
array2d<rgb_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
}
}
save_png(img, "test.png");
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_png(img, "test.png");
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
}
{
array2d<bgr_pixel> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c].red = static_cast<unsigned char>(r*14 + c + 1);
img[r][c].green = static_cast<unsigned char>(r*14 + c + 2);
img[r][c].blue = static_cast<unsigned char>(r*14 + c + 3);
}
}
save_png(img, "test.png");
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_png(img, "test.png");
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c].red == r*14 + c + 1);
DLIB_TEST(img[r][c].green == r*14 + c + 2);
DLIB_TEST(img[r][c].blue == r*14 + c + 3);
}
}
}
#endif // DLIB_PNG_SUPPORT
{
array2d<unsigned short> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c] = static_cast<unsigned short>(r*14 + c + 0xF0);
}
}
ostringstream sout;
save_dng(img, sout);
istringstream sin(sout.str());
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == r*14 + c + 0xF0);
}
}
}
#ifdef DLIB_PNG_SUPPORT
{
array2d<unsigned short> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c] = static_cast<unsigned short>(r*14 + c + 0xF0);
}
}
save_png(img, "test.png");
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_png(img, "test.png");
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == r*14 + c + 0xF0);
}
}
}
#endif // DLIB_PNG_SUPPORT
{
array2d<unsigned char> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c] = static_cast<unsigned char>(r*14 + c*111);
}
}
ostringstream sout;
save_dng(img, sout);
save_bmp(img, sout);
save_dng(img, sout);
save_bmp(img, sout);
istringstream sin(sout.str());
for (int i = 0; i < 2; ++i)
{
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == static_cast<unsigned char>(r*14 + c*111));
}
}
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_bmp(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == static_cast<unsigned char>(r*14 + c*111));
}
}
}
}
#ifdef DLIB_PNG_SUPPORT
{
array2d<unsigned char> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c] = static_cast<unsigned char>(r*14 + c);
}
}
save_png(img, "test.png");
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_png(img, "test.png");
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == r*14 + c);
}
}
}
#endif // DLIB_PNG_SUPPORT
{
// in this test we will only assign pixel values that can be
// represented with 8 bits even though we are using a wider pixel type.
array2d<unsigned short> img;
img.set_size(14,15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
img[r][c] = static_cast<unsigned char>(r*14 + c);
}
}
ostringstream sout;
save_dng(img, sout);
save_bmp(img, sout);
save_dng(img, sout);
save_bmp(img, sout);
istringstream sin(sout.str());
for (int i = 0; i < 2; ++i)
{
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_dng(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == r*14 + c);
}
}
img.clear();
DLIB_TEST(img.nr() == 0);
DLIB_TEST(img.nc() == 0);
load_bmp(img, sin);
DLIB_TEST(img.nr() == 14);
DLIB_TEST(img.nc() == 15);
for (long r = 0; r < 14; ++r)
{
for (long c = 0; c < 15; ++c)
{
DLIB_TEST(img[r][c] == r*14 + c);
}
}
}
}
{
array2d<unsigned short> img1;
array2d<unsigned char> img2;
img1.set_size(10,10);
assign_all_pixels(img1, 0);
img1[5][5] = 10000;
img1[7][7] = 10000;
equalize_histogram(img1, img2);
for (long r = 0; r < img1.nr(); ++r)
{
for (long c = 0; c < img2.nc(); ++c)
{
if ((r == 5 && c == 5) ||
(r == 7 && c == 7))
{
DLIB_TEST(img2[r][c] == 255);
}
else
{
DLIB_TEST(img2[r][c] == 0);
}
}
}
}
{
array2d<unsigned char> img;
img.set_size(10,10);
assign_all_pixels(img, 0);
assign_border_pixels(img, 2,2, 4);
DLIB_TEST(zeros_matrix<unsigned char>(6,6) == subm(mat(img), rectangle(2,2,7,7)));
DLIB_TEST(uniform_matrix<unsigned char>(1,10, 4) == rowm(mat(img), 0));
DLIB_TEST(uniform_matrix<unsigned char>(1,10, 4) == rowm(mat(img), 1));
DLIB_TEST(uniform_matrix<unsigned char>(1,10, 4) == rowm(mat(img), 8));
DLIB_TEST(uniform_matrix<unsigned char>(1,10, 4) == rowm(mat(img), 9));
DLIB_TEST(uniform_matrix<unsigned char>(10,1, 4) == colm(mat(img), 0));
DLIB_TEST(uniform_matrix<unsigned char>(10,1, 4) == colm(mat(img), 1));
DLIB_TEST(uniform_matrix<unsigned char>(10,1, 4) == colm(mat(img), 8));
DLIB_TEST(uniform_matrix<unsigned char>(10,1, 4) == colm(mat(img), 9));
assign_border_pixels(img, 7, 7, 5);
DLIB_TEST(uniform_matrix<unsigned char>(10,10, 5) == mat(img));
assign_border_pixels(img, 37, 47, 5);
DLIB_TEST(uniform_matrix<unsigned char>(10,10, 5) == mat(img));
}
{
array2d<unsigned char> img;
img.set_size(11,11);
assign_all_pixels(img, 0);
assign_border_pixels(img, 2,2, 4);
DLIB_TEST(zeros_matrix<unsigned char>(7,7) == subm(mat(img), rectangle(2,2,8,8)));
DLIB_TEST(uniform_matrix<unsigned char>(1,11, 4) == rowm(mat(img), 0));
DLIB_TEST(uniform_matrix<unsigned char>(1,11, 4) == rowm(mat(img), 1));
DLIB_TEST(uniform_matrix<unsigned char>(1,11, 4) == rowm(mat(img), 9));
DLIB_TEST(uniform_matrix<unsigned char>(1,11, 4) == rowm(mat(img), 10));
DLIB_TEST(uniform_matrix<unsigned char>(11,1, 4) == colm(mat(img), 0));
DLIB_TEST(uniform_matrix<unsigned char>(11,1, 4) == colm(mat(img), 1));
DLIB_TEST(uniform_matrix<unsigned char>(11,1, 4) == colm(mat(img), 9));
DLIB_TEST(uniform_matrix<unsigned char>(11,1, 4) == colm(mat(img), 10));
assign_border_pixels(img, 7, 7, 5);
DLIB_TEST(uniform_matrix<unsigned char>(11,11, 5) == mat(img));
assign_border_pixels(img, 70, 57, 5);
DLIB_TEST(uniform_matrix<unsigned char>(11,11, 5) == mat(img));
}
}
template <typename T, typename pixel_type>
void test_integral_image (
)
{
dlib::rand rnd;
array2d<pixel_type> img;
integral_image_generic<T> int_img;
int_img.load(img);
DLIB_TEST(int_img.nr() == 0);
DLIB_TEST(int_img.nc() == 0);
// make 5 random images
for (int i = 0; i < 5; ++i)
{
print_spinner();
img.set_size(rnd.get_random_16bit_number()%200+1, rnd.get_random_16bit_number()%200+1);
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = (int)rnd.get_random_8bit_number() - 100;
}
}
int_img.load(img);
DLIB_TEST(int_img.nr() == img.nr());
DLIB_TEST(int_img.nc() == img.nc());
// make 200 random rectangles
for (int j = 0; j < 500; ++j)
{
point p1(rnd.get_random_32bit_number()%img.nc(), rnd.get_random_32bit_number()%img.nr());
point p2(rnd.get_random_32bit_number()%img.nc(), rnd.get_random_32bit_number()%img.nr());
rectangle rect(p1,p2);
DLIB_TEST(int_img.get_sum_of_area(rect) == sum(subm(matrix_cast<T>(mat(img)), rect)));
rect = rectangle(p1,p1);
DLIB_TEST(int_img.get_sum_of_area(rect) == sum(subm(matrix_cast<T>(mat(img)), rect)));
}
}
}
void test_filtering2(int nr, int nc, dlib::rand& rnd)
{
print_spinner();
dlog << LINFO << "test_filtering2(): " << nr << " " << nc;
array2d<float> img(302,301);
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = rnd.get_random_gaussian();
}
}
matrix<float> filt = matrix_cast<float>(randm(nr,nc,rnd));
matrix<float> out = xcorr_same(mat(img),filt);
matrix<float> out2 = subm(conv(mat(img),flip(filt)), filt.nr()/2, filt.nc()/2, img.nr(), img.nc());
// make sure xcorr_same does exactly what the docs say it should.
DLIB_TEST(max(abs(out-out2)) < 1e-7);
// Now compare the filtering functions to xcorr_same to make sure everything does
// filtering in the same way.
array2d<float> imout(img.nr(), img.nc());
assign_all_pixels(imout, 10);
rectangle rect = spatially_filter_image(img, imout, filt);
border_enumerator be(get_rect(imout),rect);
while (be.move_next())
{
DLIB_TEST(imout[be.element().y()][be.element().x()] == 0);
}
DLIB_TEST_MSG(max(abs(subm(mat(imout),rect) - subm(out,rect))) < 1e-5, max(abs(subm(mat(imout),rect) - subm(out,rect))));
assign_all_pixels(imout, 10);
out = 10;
rect = spatially_filter_image(img, imout, filt,2,true,true);
be = border_enumerator(get_rect(imout),rect);
while (be.move_next())
{
DLIB_TEST(imout[be.element().y()][be.element().x()] == 10);
}
out += abs(xcorr_same(mat(img),filt)/2);
DLIB_TEST(max(abs(subm(mat(imout),rect) - subm(out,rect))) < 1e-7);
assign_all_pixels(imout, -10);
out = -10;
rect = spatially_filter_image(img, imout, filt,2,false,true);
be = border_enumerator(get_rect(imout),rect);
while (be.move_next())
{
DLIB_TEST(imout[be.element().y()][be.element().x()] == -10);
}
out += xcorr_same(mat(img),filt)/2;
DLIB_TEST_MSG(max(abs(subm(mat(imout),rect) - subm(out,rect))) < 1e-5, max(abs(subm(mat(imout),rect) - subm(out,rect))));
matrix<float> row_filt = matrix_cast<float>(randm(nc,1,rnd));
matrix<float> col_filt = matrix_cast<float>(randm(nr,1,rnd));
assign_all_pixels(imout, 10);
rect = spatially_filter_image_separable(img, imout, row_filt, col_filt);
out = xcorr_same(tmp(xcorr_same(mat(img),trans(row_filt))), col_filt);
DLIB_TEST_MSG(max(abs(subm(mat(imout),rect) - subm(out,rect))) < 1e-5, max(abs(subm(mat(imout),rect) - subm(out,rect))));
be = border_enumerator(get_rect(imout),rect);
while (be.move_next())
{
DLIB_TEST(imout[be.element().y()][be.element().x()] == 0);
}
assign_all_pixels(imout, 10);
out = 10;
rect = spatially_filter_image_separable(img, imout, row_filt, col_filt,2,true,true);
out += abs(xcorr_same(tmp(xcorr_same(mat(img),trans(row_filt))), col_filt)/2);
DLIB_TEST_MSG(max(abs(subm(mat(imout),rect) - subm(out,rect))) < 1e-7,
max(abs(subm(mat(imout),rect) - subm(out,rect))));
be = border_enumerator(get_rect(imout),rect);
while (be.move_next())
{
DLIB_TEST(imout[be.element().y()][be.element().x()] == 10);
}
}
template <typename T>
void test_filtering(bool use_abs, unsigned long scale )
{
print_spinner();
dlog << LINFO << "test_filtering(" << use_abs << "," << scale << ")";
array2d<T> img, img2, img3;
img.set_size(10,11);
assign_all_pixels(img, 10);
matrix<int,3,5> filter2;
filter2 = 1,1,1,1,1,
1,1,1,1,1,
1,1,1,1,1;
assign_all_pixels(img2,3);
rectangle brect = spatially_filter_image(img, img2, filter2);
DLIB_TEST(brect == shrink_rect(get_rect(img), filter2.nc()/2, filter2.nr()/2));
const rectangle rect(2,1,img.nc()-3,img.nr()-2);
for (long r = 0; r<img2.nr(); ++r)
{
for (long c = 0; c<img2.nc(); ++c)
{
if (rect.contains(c,r))
{
DLIB_TEST_MSG(img2[r][c] == 150, (int)img2[r][c]);
}
else
{
DLIB_TEST_MSG(img2[r][c] == 0,(int)img2[r][c]);
}
}
}
assign_all_pixels(img2,3);
assign_all_pixels(img3,3);
brect = spatially_filter_image(img, img2, filter2);
DLIB_TEST(brect == shrink_rect(get_rect(img), filter2.nc()/2, filter2.nr()/2));
matrix<int,1,5> row_filter;
matrix<int,1,3> col_filter;
row_filter = 1,1,1,1,1;
col_filter = 1,1,1;
spatially_filter_image_separable(img, img3, row_filter, col_filter);
DLIB_TEST(mat(img2) == mat(img3));
dlib::rand rnd;
for (int i = 0; i < 30; ++i)
{
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = rnd.get_random_8bit_number();
}
}
row_filter(0) = ((int)rnd.get_random_8bit_number() - 100)/10;
row_filter(1) = ((int)rnd.get_random_8bit_number() - 100)/10;
row_filter(2) = ((int)rnd.get_random_8bit_number() - 100)/10;
row_filter(3) = ((int)rnd.get_random_8bit_number() - 100)/10;
row_filter(4) = ((int)rnd.get_random_8bit_number() - 100)/10;
col_filter(0) = ((int)rnd.get_random_8bit_number() - 100)/10;
col_filter(1) = ((int)rnd.get_random_8bit_number() - 100)/10;
col_filter(2) = ((int)rnd.get_random_8bit_number() - 100)/10;
const matrix<int,3,5> filter = trans(col_filter)*row_filter;
assign_all_pixels(img2,3);
assign_all_pixels(img3,3);
// Just make sure both filtering methods give the same results.
rectangle brect1, brect2;
brect1 = spatially_filter_image(img, img2, filter, scale, use_abs);
brect2 = spatially_filter_image_separable(img, img3, row_filter, col_filter, scale, use_abs);
DLIB_TEST(mat(img2) == mat(img3));
DLIB_TEST(brect1 == shrink_rect(get_rect(img), filter.nc()/2, filter.nr()/2));
DLIB_TEST(brect1 == brect2);
}
{
array2d<int> img, img2;
img.set_size(3,4);
matrix<int> filter(3,3);
filter = 1;
assign_all_pixels(img,-1);
spatially_filter_image(img,img2,filter);
DLIB_TEST(img2[0][0] == 0);
DLIB_TEST(img2[0][1] == 0);
DLIB_TEST(img2[0][2] == 0);
DLIB_TEST(img2[0][3] == 0);
DLIB_TEST(img2[1][0] == 0);
DLIB_TEST(img2[1][1] == -9);
DLIB_TEST(img2[1][2] == -9);
DLIB_TEST(img2[1][3] == 0);
DLIB_TEST(img2[2][0] == 0);
DLIB_TEST(img2[2][1] == 0);
DLIB_TEST(img2[2][2] == 0);
DLIB_TEST(img2[2][3] == 0);
assign_all_pixels(img,-1);
spatially_filter_image(img,img2,filter,2,true);
DLIB_TEST(img2[0][0] == 0);
DLIB_TEST(img2[0][1] == 0);
DLIB_TEST(img2[0][2] == 0);
DLIB_TEST(img2[0][3] == 0);
DLIB_TEST(img2[1][0] == 0);
DLIB_TEST(img2[1][1] == 4);
DLIB_TEST(img2[1][2] == 4);
DLIB_TEST(img2[1][3] == 0);
DLIB_TEST(img2[2][0] == 0);
DLIB_TEST(img2[2][1] == 0);
DLIB_TEST(img2[2][2] == 0);
DLIB_TEST(img2[2][3] == 0);
matrix<int> rowf(3,1), colf(3,1);
rowf = 1;
colf = 1;
assign_all_pixels(img,-1);
spatially_filter_image_separable(img,img2,rowf,colf);
DLIB_TEST(img2[0][0] == 0);
DLIB_TEST(img2[0][1] == 0);
DLIB_TEST(img2[0][2] == 0);
DLIB_TEST(img2[0][3] == 0);
DLIB_TEST(img2[1][0] == 0);
DLIB_TEST(img2[1][1] == -9);
DLIB_TEST(img2[1][2] == -9);
DLIB_TEST(img2[1][3] == 0);
DLIB_TEST(img2[2][0] == 0);
DLIB_TEST(img2[2][1] == 0);
DLIB_TEST(img2[2][2] == 0);
DLIB_TEST(img2[2][3] == 0);
spatially_filter_image_separable(img,img2,rowf,colf,1,true);
DLIB_TEST(img2[0][0] == 0);
DLIB_TEST(img2[0][1] == 0);
DLIB_TEST(img2[0][2] == 0);
DLIB_TEST(img2[0][3] == 0);
DLIB_TEST(img2[1][0] == 0);
DLIB_TEST(img2[1][1] == 9);
DLIB_TEST(img2[1][2] == 9);
DLIB_TEST(img2[1][3] == 0);
DLIB_TEST(img2[2][0] == 0);
DLIB_TEST(img2[2][1] == 0);
DLIB_TEST(img2[2][2] == 0);
DLIB_TEST(img2[2][3] == 0);
assign_all_pixels(img2, 3);
spatially_filter_image_separable(img,img2,rowf,colf,1,true, true);
DLIB_TEST(img2[0][0] == 3);
DLIB_TEST(img2[0][1] == 3);
DLIB_TEST(img2[0][2] == 3);
DLIB_TEST(img2[0][3] == 3);
DLIB_TEST(img2[1][0] == 3);
DLIB_TEST_MSG(img2[1][1] == 9+3, img2[1][1] );
DLIB_TEST(img2[1][2] == 9+3);
DLIB_TEST(img2[1][3] == 3);
DLIB_TEST(img2[2][0] == 3);
DLIB_TEST(img2[2][1] == 3);
DLIB_TEST(img2[2][2] == 3);
DLIB_TEST(img2[2][3] == 3);
}
{
array2d<double> img, img2;
img.set_size(3,4);
matrix<double> filter(3,3);
filter = 1;
assign_all_pixels(img,-1);
spatially_filter_image(img,img2,filter,2);
DLIB_TEST(img2[0][0] == 0);
DLIB_TEST(img2[0][1] == 0);
DLIB_TEST(img2[0][2] == 0);
DLIB_TEST(img2[0][3] == 0);
DLIB_TEST(img2[1][0] == 0);
DLIB_TEST(std::abs(img2[1][1] - -4.5) < 1e-14);
DLIB_TEST(std::abs(img2[1][2] - -4.5) < 1e-14);
DLIB_TEST(img2[1][3] == 0);
DLIB_TEST(img2[2][0] == 0);
DLIB_TEST(img2[2][1] == 0);
DLIB_TEST(img2[2][2] == 0);
DLIB_TEST(img2[2][3] == 0);
}
{
array2d<double> img, img2;
img.set_size(3,4);
img2.set_size(3,4);
assign_all_pixels(img2, 8);
matrix<double> filter(3,3);
filter = 1;
assign_all_pixels(img,-1);
spatially_filter_image(img,img2,filter,2, false, true);
DLIB_TEST(img2[0][0] == 8);
DLIB_TEST(img2[0][1] == 8);
DLIB_TEST(img2[0][2] == 8);
DLIB_TEST(img2[0][3] == 8);
DLIB_TEST(img2[1][0] == 8);
DLIB_TEST(std::abs(img2[1][1] - -4.5 - 8) < 1e-14);
DLIB_TEST(std::abs(img2[1][2] - -4.5 - 8) < 1e-14);
DLIB_TEST(img2[1][3] == 8);
DLIB_TEST(img2[2][0] == 8);
DLIB_TEST(img2[2][1] == 8);
DLIB_TEST(img2[2][2] == 8);
DLIB_TEST(img2[2][3] == 8);
}
}
void test_zero_border_pixels(
)
{
array2d<unsigned char> img;
img.set_size(4,5);
assign_all_pixels(img, 1);
zero_border_pixels(img, 2,1);
DLIB_TEST(img[0][0] == 0);
DLIB_TEST(img[1][0] == 0);
DLIB_TEST(img[2][0] == 0);
DLIB_TEST(img[3][0] == 0);
DLIB_TEST(img[0][1] == 0);
DLIB_TEST(img[1][1] == 0);
DLIB_TEST(img[2][1] == 0);
DLIB_TEST(img[3][1] == 0);
DLIB_TEST(img[0][3] == 0);
DLIB_TEST(img[1][3] == 0);
DLIB_TEST(img[2][3] == 0);
DLIB_TEST(img[3][3] == 0);
DLIB_TEST(img[0][4] == 0);
DLIB_TEST(img[1][4] == 0);
DLIB_TEST(img[2][4] == 0);
DLIB_TEST(img[3][4] == 0);
DLIB_TEST(img[0][2] == 0);
DLIB_TEST(img[3][2] == 0);
DLIB_TEST(img[1][2] == 1);
DLIB_TEST(img[2][2] == 1);
rectangle rect = get_rect(img);
rect.left()+=2;
rect.top()+=1;
rect.right()-=2;
rect.bottom()-=1;
assign_all_pixels(img, 1);
zero_border_pixels(img, rect);
DLIB_TEST(img[0][0] == 0);
DLIB_TEST(img[1][0] == 0);
DLIB_TEST(img[2][0] == 0);
DLIB_TEST(img[3][0] == 0);
DLIB_TEST(img[0][1] == 0);
DLIB_TEST(img[1][1] == 0);
DLIB_TEST(img[2][1] == 0);
DLIB_TEST(img[3][1] == 0);
DLIB_TEST(img[0][3] == 0);
DLIB_TEST(img[1][3] == 0);
DLIB_TEST(img[2][3] == 0);
DLIB_TEST(img[3][3] == 0);
DLIB_TEST(img[0][4] == 0);
DLIB_TEST(img[1][4] == 0);
DLIB_TEST(img[2][4] == 0);
DLIB_TEST(img[3][4] == 0);
DLIB_TEST(img[0][2] == 0);
DLIB_TEST(img[3][2] == 0);
DLIB_TEST(img[1][2] == 1);
DLIB_TEST(img[2][2] == 1);
rect.right()+=1;
assign_all_pixels(img, 1);
zero_border_pixels(img, rect);
DLIB_TEST(img[0][0] == 0);
DLIB_TEST(img[1][0] == 0);
DLIB_TEST(img[2][0] == 0);
DLIB_TEST(img[3][0] == 0);
DLIB_TEST(img[0][1] == 0);
DLIB_TEST(img[1][1] == 0);
DLIB_TEST(img[2][1] == 0);
DLIB_TEST(img[3][1] == 0);
DLIB_TEST(img[0][3] == 0);
DLIB_TEST(img[1][3] == 1);
DLIB_TEST(img[2][3] == 1);
DLIB_TEST(img[3][3] == 0);
DLIB_TEST(img[0][4] == 0);
DLIB_TEST(img[1][4] == 0);
DLIB_TEST(img[2][4] == 0);
DLIB_TEST(img[3][4] == 0);
DLIB_TEST(img[0][2] == 0);
DLIB_TEST(img[3][2] == 0);
DLIB_TEST(img[1][2] == 1);
DLIB_TEST(img[2][2] == 1);
}
void test_label_connected_blobs()
{
array2d<unsigned char> img;
img.set_size(400,401);
assign_all_pixels(img,0);
rectangle rect1, rect2, rect3;
rect1 = centered_rect(99,120, 50,70);
rect2 = centered_rect(199,80, 34,68);
rect3 = centered_rect(249,180, 120,78);
fill_rect(img, rect1, 255);
fill_rect(img, rect2, 255);
fill_rect(img, rect3, 255);
array2d<unsigned char> labels;
unsigned long num;
num = label_connected_blobs(img,
zero_pixels_are_background(),
neighbors_8(),
connected_if_both_not_zero(),
labels);
DLIB_TEST(num == 4);
DLIB_TEST(labels.nr() == img.nr());
DLIB_TEST(labels.nc() == img.nc());
const unsigned char l1 = labels[rect1.top()][rect1.left()];
const unsigned char l2 = labels[rect2.top()][rect2.left()];
const unsigned char l3 = labels[rect3.top()][rect3.left()];
DLIB_TEST(l1 != 0 && l2 != 0 && l3 != 0);
DLIB_TEST(l1 != l2 && l1 != l3 && l2 != l3);
for (long r = 0; r < labels.nr(); ++r)
{
for (long c = 0; c < labels.nc(); ++c)
{
if (rect1.contains(c,r))
{
DLIB_TEST(labels[r][c] == l1);
}
else if (rect2.contains(c,r))
{
DLIB_TEST(labels[r][c] == l2);
}
else if (rect3.contains(c,r))
{
DLIB_TEST(labels[r][c] == l3);
}
else
{
DLIB_TEST(labels[r][c] == 0);
}
}
}
}
void test_label_connected_blobs2()
{
array2d<unsigned char> img;
img.set_size(400,401);
assign_all_pixels(img,0);
rectangle rect1, rect2, rect3;
rect1 = centered_rect(99,120, 50,70);
rect2 = centered_rect(199,80, 34,68);
rect3 = centered_rect(249,180, 120,78);
fill_rect(img, rect1, 255);
fill_rect(img, rect2, 253);
fill_rect(img, rect3, 255);
array2d<unsigned char> labels;
unsigned long num;
num = label_connected_blobs(img,
nothing_is_background(),
neighbors_4(),
connected_if_equal(),
labels);
DLIB_TEST(num == 5);
DLIB_TEST(labels.nr() == img.nr());
DLIB_TEST(labels.nc() == img.nc());
const unsigned char l0 = labels[0][0];
const unsigned char l1 = labels[rect1.top()][rect1.left()];
const unsigned char l2 = labels[rect2.top()][rect2.left()];
const unsigned char l3 = labels[rect3.top()][rect3.left()];
DLIB_TEST(l0 != 0 && l1 != 0 && l2 != 0 && l3 != 0);
DLIB_TEST(l1 != l2 && l1 != l3 && l2 != l3 &&
l0 != l1 && l0 != l2 && l0 != l3);
for (long r = 0; r < labels.nr(); ++r)
{
for (long c = 0; c < labels.nc(); ++c)
{
if (rect1.contains(c,r))
{
DLIB_TEST(labels[r][c] == l1);
}
else if (rect2.contains(c,r))
{
DLIB_TEST(labels[r][c] == l2);
}
else if (rect3.contains(c,r))
{
DLIB_TEST(labels[r][c] == l3);
}
else
{
DLIB_TEST(labels[r][c] == l0);
}
}
}
}
// ----------------------------------------------------------------------------------------
template <
typename in_image_type,
typename out_image_type
>
void downsample_image (
const unsigned long downsample,
const in_image_type& in_img,
out_image_type& out_img,
bool add_to
)
{
out_img.set_size((in_img.nr()+downsample-1)/downsample,
(in_img.nc()+downsample-1)/downsample);
for (long r = 0; r < out_img.nr(); ++r)
{
for (long c = 0; c < out_img.nc(); ++c)
{
if (add_to)
out_img[r][c] += in_img[r*downsample][c*downsample];
else
out_img[r][c] = in_img[r*downsample][c*downsample];
}
}
}
template <
typename in_image_type,
typename out_image_type,
typename EXP1,
typename EXP2,
typename T
>
void test_spatially_filter_image_separable_down_simple (
const unsigned long downsample,
const in_image_type& in_img,
out_image_type& out_img,
const matrix_exp<EXP1>& row_filter,
const matrix_exp<EXP2>& col_filter,
T scale,
bool use_abs = false,
bool add_to = false
)
{
out_image_type temp;
spatially_filter_image_separable(in_img, temp, row_filter, col_filter, scale, use_abs, false);
downsample_image(downsample, temp, out_img, add_to);
}
template <unsigned long downsample>
void test_downsampled_filtering_helper(long row_filt_size, long col_filt_size)
{
print_spinner();
dlog << LTRACE << "***********************************";
dlog << LTRACE << "downsample: " << downsample;
dlog << LTRACE << "row_filt_size: "<< row_filt_size;
dlog << LTRACE << "col_filt_size: "<< col_filt_size;
dlib::rand rnd;
array2d<int> out1, out2;
for (long nr = 0; nr < 3; ++nr)
{
for (long nc = 0; nc < 3; ++nc)
{
dlog << LTRACE << "nr: "<< nr;
dlog << LTRACE << "nc: "<< nc;
array2d<unsigned char> img(25+nr,25+nc);
for (int k = 0; k < 5; ++k)
{
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = rnd.get_random_8bit_number();
}
}
matrix<int,0,1> row_filter(row_filt_size);
matrix<int,0,1> col_filter(col_filt_size);
row_filter = matrix_cast<int>(10*randm(row_filt_size,1, rnd));
col_filter = matrix_cast<int>(10*randm(col_filt_size,1, rnd));
row_filter -= 3;
col_filter -= 3;
test_spatially_filter_image_separable_down_simple(downsample, img, out1, row_filter, col_filter,1 );
spatially_filter_image_separable_down(downsample, img, out2, row_filter, col_filter);
DLIB_TEST(get_rect(out1) == get_rect(out2));
DLIB_TEST(mat(out1) == mat(out2));
test_spatially_filter_image_separable_down_simple(downsample, img, out1, row_filter, col_filter,3, true, true );
spatially_filter_image_separable_down(downsample, img, out2, row_filter, col_filter, 3, true, true);
DLIB_TEST(get_rect(out1) == get_rect(out2));
DLIB_TEST(mat(out1) == mat(out2));
}
}
}
}
void test_downsampled_filtering()
{
test_downsampled_filtering_helper<1>(5,5);
test_downsampled_filtering_helper<2>(5,5);
test_downsampled_filtering_helper<3>(5,5);
test_downsampled_filtering_helper<1>(3,5);
test_downsampled_filtering_helper<2>(3,5);
test_downsampled_filtering_helper<3>(3,5);
test_downsampled_filtering_helper<1>(5,3);
test_downsampled_filtering_helper<2>(5,3);
test_downsampled_filtering_helper<3>(5,3);
test_downsampled_filtering_helper<1>(3,3);
test_downsampled_filtering_helper<2>(3,3);
test_downsampled_filtering_helper<3>(3,3);
test_downsampled_filtering_helper<1>(1,1);
test_downsampled_filtering_helper<2>(1,1);
test_downsampled_filtering_helper<3>(1,1);
}
// ----------------------------------------------------------------------------------------
template <typename T>
void test_segment_image()
{
print_spinner();
array2d<T> img(100,100);
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
if (c < 50 || r < 50)
assign_pixel(img[r][c], 0);
else
assign_pixel(img[r][c], 255);
}
}
array2d<unsigned long> out;
segment_image(img, out);
DLIB_TEST(get_rect(img) == get_rect(out));
const unsigned long v1 = out[0][0];
const unsigned long v2 = out[90][90];
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
if (c < 50 || r < 50)
{
DLIB_TEST(out[r][c] == v1);
}
else
{
DLIB_TEST(out[r][c] == v2);
}
}
}
}
// ----------------------------------------------------------------------------------------
template <typename T>
void test_dng_floats(double scale)
{
dlog << LINFO << "in test_dng_floats";
print_spinner();
array2d<T> img(100,101);
dlib::rand rnd;
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
T val = rnd.get_random_double()*scale;
img[r][c] = val;
// Lets the float_details object while we are here doing this stuff.
float_details temp = val;
T val2 = temp;
// for the same type we should exactly reproduce the value (unless
// it's long double and then maybe it's slightly different).
if (is_same_type<T,long double>::value)
{
DLIB_TEST(std::abs(val2-val) < scale*std::numeric_limits<T>::epsilon());
}
else
{
DLIB_TEST(val2 == val);
}
float valf = temp;
double vald = temp;
long double vall = temp;
DLIB_TEST(std::abs(valf-val) < scale*std::numeric_limits<float>::epsilon());
DLIB_TEST(std::abs(vald-val) < scale*std::numeric_limits<double>::epsilon());
DLIB_TEST(std::abs(vall-val) < scale*std::numeric_limits<long double>::epsilon());
}
}
ostringstream sout;
save_dng(img, sout);
istringstream sin;
array2d<float> img1;
array2d<double> img2;
array2d<long double> img3;
sin.clear(); sin.str(sout.str());
load_dng(img1, sin);
sin.clear(); sin.str(sout.str());
load_dng(img2, sin);
sin.clear(); sin.str(sout.str());
load_dng(img3, sin);
DLIB_TEST(img.nr() == img1.nr());
DLIB_TEST(img.nr() == img2.nr());
DLIB_TEST(img.nr() == img3.nr());
DLIB_TEST(img.nc() == img1.nc());
DLIB_TEST(img.nc() == img2.nc());
DLIB_TEST(img.nc() == img3.nc());
DLIB_TEST(max(abs(mat(img) - matrix_cast<T>(mat(img1)))) < scale*std::numeric_limits<float>::epsilon());
DLIB_TEST(max(abs(mat(img) - matrix_cast<T>(mat(img2)))) < scale*std::numeric_limits<double>::epsilon());
DLIB_TEST(max(abs(mat(img) - matrix_cast<T>(mat(img3)))) < scale*std::numeric_limits<long double>::epsilon());
}
void test_dng_float_int()
{
dlog << LINFO << "in test_dng_float_int";
print_spinner();
array2d<uint16> img;
assign_image(img, gaussian_randm(101,100)*10000);
ostringstream sout;
save_dng(img, sout);
istringstream sin(sout.str());
array2d<double> img2;
load_dng(img2, sin);
sout.clear(); sout.str("");
save_dng(img2, sout);
sin.clear(); sin.str(sout.str());
array2d<uint16> img3;
load_dng(img3, sin);
// this whole thing should have been totally lossless.
DLIB_TEST(mat(img) == mat(img3));
}
// ----------------------------------------------------------------------------------------
template <typename T>
void test_filtering_center (
dlib::rand& rnd
)
{
array2d<T> img(rnd.get_random_32bit_number()%100+1,
rnd.get_random_32bit_number()%100+1);
matrix<T> filt(rnd.get_random_32bit_number()%10+1,
rnd.get_random_32bit_number()%10+1);
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = rnd.get_random_32bit_number()%100;
}
}
for (long r = 0; r < filt.nr(); ++r)
{
for (long c = 0; c < filt.nc(); ++c)
{
filt(r,c) = rnd.get_random_32bit_number()%100;
}
}
array2d<T> out;
const rectangle area = spatially_filter_image(img, out, filt);
for (long r = 0; r < out.nr(); ++r)
{
for (long c = 0; c < out.nc(); ++c)
{
const rectangle rect = centered_rect(point(c,r), filt.nc(), filt.nr());
if (get_rect(out).contains(rect))
{
T val = sum(pointwise_multiply(filt, subm(mat(img),rect)));
DLIB_TEST_MSG(val == out[r][c],"err: " << val-out[r][c]);
DLIB_TEST(area.contains(point(c,r)));
}
else
{
DLIB_TEST(!area.contains(point(c,r)));
}
}
}
}
template <typename T>
void test_separable_filtering_center (
dlib::rand& rnd
)
{
array2d<T> img(rnd.get_random_32bit_number()%100+1,
rnd.get_random_32bit_number()%100+1);
matrix<T,1,0> row_filt(rnd.get_random_32bit_number()%10+1);
matrix<T,0,1> col_filt(rnd.get_random_32bit_number()%10+1);
for (long r = 0; r < img.nr(); ++r)
{
for (long c = 0; c < img.nc(); ++c)
{
img[r][c] = rnd.get_random_32bit_number()%10;
}
}
for (long r = 0; r < row_filt.size(); ++r)
{
row_filt(r) = rnd.get_random_32bit_number()%10;
}
for (long r = 0; r < col_filt.size(); ++r)
{
col_filt(r) = rnd.get_random_32bit_number()%10;
}
array2d<T> out;
const rectangle area = spatially_filter_image_separable(img, out, row_filt, col_filt);
for (long r = 0; r < out.nr(); ++r)
{
for (long c = 0; c < out.nc(); ++c)
{
const rectangle rect = centered_rect(point(c,r), row_filt.size(), col_filt.size());
if (get_rect(out).contains(rect))
{
T val = sum(pointwise_multiply(col_filt*row_filt, subm(mat(img),rect)));
DLIB_TEST_MSG(val == out[r][c],"err: " << val-out[r][c]);
DLIB_TEST(area.contains(point(c,r)));
}
else
{
DLIB_TEST(!area.contains(point(c,r)));
}
}
}
}
// ----------------------------------------------------------------------------------------
void run_hough_test()
{
array2d<unsigned char> img(300,300);
for (int k = -2; k <= 2; ++k)
{
print_spinner();
running_stats<double> rs;
array2d<int> himg;
hough_transform ht(200+k);
double angle1 = 0;
double angle2 = 0;
const int len = 90;
// Draw a bunch of random lines, hough transform them, then make sure the hough
// transform detects them accurately.
for (int i = 0; i < 500; ++i)
{
point cent = center(get_rect(img));
point arc = cent + point(len,0);
arc = rotate_point(cent, arc, angle1);
point l = arc + point(500,0);
point r = arc - point(500,0);
l = rotate_point(arc, l, angle2);
r = rotate_point(arc, r, angle2);
angle1 += pi/13;
angle2 += pi/40;
assign_all_pixels(img, 0);
draw_line(img, l, r, 255);
rectangle box = translate_rect(get_rect(ht),point(50,50));
ht(img, box, himg);
point p = max_point(mat(himg));
DLIB_TEST(himg[p.y()][p.x()] > 255*3);
l -= point(50,50);
r -= point(50,50);
std::pair<point,point> line = ht.get_line(p);
// make sure the best scoring hough point matches the line we drew.
double dist1 = distance_to_line(make_pair(l,r), line.first);
double dist2 = distance_to_line(make_pair(l,r), line.second);
//cout << "DIST1: " << dist1 << endl;
//cout << "DIST2: " << dist2 << endl;
rs.add(dist1);
rs.add(dist2);
DLIB_TEST(dist1 < 2.5);
DLIB_TEST(dist2 < 2.5);
}
//cout << "rs.mean(): " << rs.mean() << endl;
DLIB_TEST(rs.mean() < 0.7);
}
}
// ----------------------------------------------------------------------------------------
void test_extract_image_chips()
{
dlib::rand rnd;
// Make sure that cropping a white box out of a larger white image always produces an
// exact white box. This should catch any bad border effects from a messed up internal
// cropping.
for (int iter = 0; iter < 1000; ++iter)
{
print_spinner();
const long nr = rnd.get_random_32bit_number()%100 + 1;
const long nc = rnd.get_random_32bit_number()%100 + 1;
const long size = rnd.get_random_32bit_number()%10000 + 4;
const double angle = rnd.get_random_double() * pi;
matrix<int> img(501,501), chip;
img = 255;
chip_details details(centered_rect(center(get_rect(img)),nr,nc), size, angle);
extract_image_chip(img, details, chip);
DLIB_TEST_MSG(max(abs(chip-255))==0,"nr: " << nr << " nc: "<< nc << " size: " << size << " angle: " << angle
<< " error: " << max(abs(chip-255)) );
}
// So the same as above, but for an image with float values that are all the same to make
// sure noting funny happens for float images.
{
print_spinner();
const long nr = 53;
const long nc = 67;
const long size = 8*9;
const double angle = 30*pi/180;
matrix<float> img(501,501), chip;
img = 1234.5;
chip_details details(centered_rect(center(get_rect(img)),nr,nc), size, angle);
extract_image_chip(img, details, chip);
DLIB_TEST_MSG(max(abs(chip-1234.5))==0,"nr: " << nr << " nc: "<< nc << " size: " << size << " angle: " << angle
<< " error: " << max(abs(chip-255)) );
}
{
// Make sure that the interpolation in extract_image_chip() keeps stuff in the
// right places.
matrix<unsigned char> img(10,10), chip;
img = 0;
img(1,1) = 255;
img(8,8) = 255;
extract_image_chip(img, chip_details(get_rect(img), 9*9), chip);
DLIB_TEST(chip(1,1) == 195);
DLIB_TEST(chip(7,7) == 195);
chip(1,1) -= 195;
chip(7,7) -= 195;
DLIB_TEST(sum(matrix_cast<int>(chip)) == 0);
}
// Test the rotation ability of extract_image_chip(). Do this by drawing a line and
// then rotating it so it's horizontal. Check that it worked correctly by hough
// transforming it.
hough_transform ht(151);
matrix<unsigned char> img(300,300);
for (int iter = 0; iter < 1000; ++iter)
{
print_spinner();
img = 0;
const int len = 9000;
point cent = center(get_rect(img));
point l = cent + point(len,0);
point r = cent - point(len,0);
const double angle = rnd.get_random_double()*pi*3;
l = rotate_point(cent, l, angle);
r = rotate_point(cent, r, angle);
draw_line(img, l, r, 255);
const long wsize = rnd.get_random_32bit_number()%350 + 150;
matrix<unsigned char> temp;
chip_details details(centered_rect(center(get_rect(img)), wsize,wsize), chip_dims(ht.size(),ht.size()), angle);
extract_image_chip(img, details, temp);
matrix<long> tform;
ht(temp, get_rect(temp), tform);
std::pair<point,point> line = ht.get_line(max_point(tform));
DLIB_TEST_MSG(line.first.y() == line.second.y()," wsize: " << wsize);
DLIB_TEST(length(line.first-line.second) > 100);
DLIB_TEST(length((line.first+line.second)/2.0 - center(get_rect(temp))) <= 1);
}
}
// ----------------------------------------------------------------------------------------
template <
typename image_type
>
typename pixel_traits<typename image_traits<image_type>::pixel_type>::basic_pixel_type
simple_partition_pixels (
const image_type& img
)
{
matrix<unsigned long,1> hist;
get_histogram(img,hist);
auto average1 = [&](unsigned long thresh)
{
double accum = 0;
double cnt = 0;
for (unsigned long i = 0; i < thresh; ++i)
{
accum += hist(i)*i;
cnt += hist(i);
}
if (cnt != 0)
return accum/cnt;
else
return 0.0;
};
auto average2 = [&](unsigned long thresh)
{
double accum = 0;
double cnt = 0;
for (long i = thresh; i < hist.size(); ++i)
{
accum += hist(i)*i;
cnt += hist(i);
}
if (cnt != 0)
return accum/cnt;
else
return 0.0;
};
auto total_abs = [&](unsigned long thresh)
{
auto a = average1(thresh);
auto b = average2(thresh);
double score = 0;
for (long i = 0; i < hist.size(); ++i)
{
if (i < (long)thresh)
score += std::abs(a-i)*hist(i);
else
score += std::abs(b-i)*hist(i);
}
return score;
};
unsigned long thresh = 0;
double min_sad = total_abs(0);
for (long i = 1; i < hist.size(); ++i)
{
double sad = total_abs(i);
//cout << "TRUTH: i:" << i << " total: "<< total_abs(i) << endl;
if (sad <= min_sad)
{
//cout << "CHANGE TRUTH: i:" << i << " total: "<< total_abs(i)-min_sad << endl;
min_sad = sad;
thresh = i;
}
}
return thresh;
}
void test_partition_pixels()
{
matrix<unsigned char> img(4,7);
dlib::rand rnd;
for (int round = 0; round < 100; ++round)
{
print_spinner();
for (auto& p : img)
p = rnd.get_random_8bit_number();
DLIB_TEST(simple_partition_pixels(img) == partition_pixels(img));
unsigned char thresh;
impl::partition_pixels_float(img,thresh);
DLIB_TEST(simple_partition_pixels(img) == thresh);
matrix<float> fimg = matrix_cast<float>(img);
DLIB_TEST(simple_partition_pixels(img) == partition_pixels(fimg));
std::vector<unsigned char> tmp;
for (auto& v : img)
if (v >= thresh)
tmp.push_back(v);
matrix<unsigned char> img2 = mat(tmp);
unsigned char thresh2;
impl::partition_pixels_float(img,thresh, thresh2);
DLIB_TEST(simple_partition_pixels(img) == thresh);
DLIB_TEST(simple_partition_pixels(img2) == thresh2);
partition_pixels(img,thresh, thresh2);
DLIB_TEST(simple_partition_pixels(img) == thresh);
DLIB_TEST(simple_partition_pixels(img2) == thresh2);
std::vector<float> ftmp;
for (auto& v : fimg)
if (v >= thresh)
ftmp.push_back(v);
matrix<float> fimg2 = mat(ftmp);
float fthresh, fthresh2;
partition_pixels(fimg,fthresh, fthresh2);
DLIB_TEST(simple_partition_pixels(img) == fthresh);
DLIB_TEST(simple_partition_pixels(img2) == fthresh2);
}
img.set_size(245,123);
for (int round = 0; round < 100; ++round)
{
print_spinner();
for (auto& p : img)
p = rnd.get_random_8bit_number();
DLIB_TEST(simple_partition_pixels(img) == partition_pixels(img));
unsigned char thresh;
impl::partition_pixels_float(img,thresh);
DLIB_TEST(simple_partition_pixels(img) == thresh);
matrix<float> fimg = matrix_cast<float>(img);
DLIB_TEST(simple_partition_pixels(img) == partition_pixels(fimg));
std::vector<unsigned char> tmp;
for (auto& v : img)
if (v >= thresh)
tmp.push_back(v);
matrix<unsigned char> img2 = mat(tmp);
unsigned char thresh2;
impl::partition_pixels_float(img,thresh, thresh2);
DLIB_TEST(simple_partition_pixels(img) == thresh);
DLIB_TEST(simple_partition_pixels(img2) == thresh2);
partition_pixels(img,thresh, thresh2);
DLIB_TEST(simple_partition_pixels(img) == thresh);
DLIB_TEST(simple_partition_pixels(img2) == thresh2);
std::vector<float> ftmp;
for (auto& v : fimg)
if (v >= thresh)
ftmp.push_back(v);
matrix<float> fimg2 = mat(ftmp);
float fthresh, fthresh2;
partition_pixels(fimg,fthresh, fthresh2);
DLIB_TEST(simple_partition_pixels(img) == fthresh);
DLIB_TEST(simple_partition_pixels(img2) == fthresh2);
}
}
template<typename interpolation_type = interpolate_bilinear>
void test_resize_image_with_interpolation()
{
{
matrix<unsigned char> img_s(2, 2);
matrix<unsigned char> img_d(3, 3);
img_s(0, 0) = 0;
img_s(0, 1) = 100;
img_s(1, 0) = 100;
img_s(1, 1) = 100;
resize_image(img_s, img_d, interpolation_type());
DLIB_TEST((img_d(0, 0) == 0));
DLIB_TEST((img_d(0, 1) == 50));
DLIB_TEST((img_d(1, 2) == 100));
DLIB_TEST((img_d(2, 2) == 100));
}
{
matrix<rgb_pixel> img_s(2, 2);
matrix<rgb_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 10, 20, 30 };
img_s(1, 0) = { 10, 20, 30 };
img_s(1, 1) = { 10, 20, 30 };
resize_image(img_s, img_d, interpolation_type());
DLIB_TEST((img_d(0, 0) == rgb_pixel{ 0, 0, 0 }));
DLIB_TEST((img_d(0, 1) == rgb_pixel{ 5, 10, 15 }));
DLIB_TEST((img_d(1, 2) == rgb_pixel{ 10, 20, 30 }));
DLIB_TEST((img_d(2, 2) == rgb_pixel{ 10, 20, 30 }));
}
{
matrix<lab_pixel> img_s(2, 2);
matrix<lab_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 100, 20, 30 };
img_s(1, 0) = { 100, 20, 30 };
img_s(1, 1) = { 100, 20, 30 };
resize_image(img_s, img_d, interpolation_type());
DLIB_TEST((img_d(0, 0) == lab_pixel{ 0, 0, 0 }));
DLIB_TEST((img_d(0, 1) == lab_pixel{ 50, 10, 15 }));
DLIB_TEST((img_d(1, 2) == lab_pixel{ 100, 20, 30 }));
DLIB_TEST((img_d(2, 2) == lab_pixel{ 100, 20, 30 }));
}
}
void test_null_rotate_image_with_interpolation()
{
{
matrix<unsigned char> img_s(3, 3);
matrix<unsigned char> img_d;
img_s(0, 0) = 0;
img_s(0, 1) = 100;
img_s(0, 2) = 100;
img_s(1, 0) = 100;
img_s(1, 1) = 100;
img_s(1, 2) = 100;
img_s(2, 0) = 100;
img_s(2, 1) = 100;
img_s(2, 2) = 100;
rotate_image(img_s, img_d, 0, interpolate_bilinear());
DLIB_TEST((img_d(0, 0) == 0));
DLIB_TEST((img_d(0, 1) == 100));
DLIB_TEST((img_d(1, 0) == 100));
DLIB_TEST((img_d(1, 1) == 100));
}
{
matrix<rgb_pixel> img_s(3, 3);
matrix<rgb_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 10, 20, 30 };
img_s(0, 2) = { 10, 20, 30 };
img_s(1, 0) = { 10, 20, 30 };
img_s(1, 1) = { 10, 20, 30 };
img_s(1, 2) = { 10, 20, 30 };
img_s(2, 0) = { 10, 20, 30 };
img_s(2, 1) = { 10, 20, 30 };
img_s(2, 2) = { 10, 20, 30 };
rotate_image(img_s, img_d, 0, interpolate_bilinear());
DLIB_TEST((img_d(0, 0) == rgb_pixel{ 0, 0, 0 }));
DLIB_TEST((img_d(0, 1) == rgb_pixel{ 10, 20, 30 }));
DLIB_TEST((img_d(1, 0) == rgb_pixel{ 10, 20, 30 }));
DLIB_TEST((img_d(1, 1) == rgb_pixel{ 10, 20, 30 }));
}
{
matrix<lab_pixel> img_s(3, 3);
matrix<lab_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 100, 20, 30 };
img_s(0, 2) = { 100, 20, 30 };
img_s(1, 0) = { 100, 20, 30 };
img_s(1, 1) = { 100, 20, 30 };
img_s(1, 2) = { 100, 20, 30 };
img_s(2, 0) = { 100, 20, 30 };
img_s(2, 1) = { 100, 20, 30 };
img_s(2, 2) = { 100, 20, 30 };
rotate_image(img_s, img_d, 0, interpolate_bilinear());
DLIB_TEST((img_d(0, 0) == lab_pixel{ 0, 0, 0 }));
DLIB_TEST((img_d(0, 1) == lab_pixel{ 100, 20, 30 }));
DLIB_TEST((img_d(1, 0) == lab_pixel{ 100, 20, 30 }));
DLIB_TEST((img_d(1, 1) == lab_pixel{ 100, 20, 30 }));
}
}
void test_null_rotate_image_with_interpolation_quadratic()
{
{
matrix<unsigned char> img_s(3, 3);
matrix<unsigned char> img_d;
img_s(0, 0) = 0;
img_s(0, 1) = 100;
img_s(0, 2) = 100;
img_s(1, 0) = 100;
img_s(1, 1) = 100;
img_s(1, 2) = 100;
img_s(2, 0) = 100;
img_s(2, 1) = 100;
img_s(2, 2) = 100;
rotate_image(img_s, img_d, 0, interpolate_quadratic());
DLIB_TEST((img_d(1, 1) == 111));
}
{
matrix<rgb_pixel> img_s(3, 3);
matrix<rgb_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 10, 20, 30 };
img_s(0, 2) = { 10, 20, 30 };
img_s(1, 0) = { 10, 20, 30 };
img_s(1, 1) = { 10, 20, 30 };
img_s(1, 2) = { 10, 20, 30 };
img_s(2, 0) = { 10, 20, 30 };
img_s(2, 1) = { 10, 20, 30 };
img_s(2, 2) = { 10, 20, 30 };
rotate_image(img_s, img_d, 0, interpolate_quadratic());
DLIB_TEST((img_d(1, 1) == rgb_pixel{ 11, 22, 33 }));
}
{
matrix<lab_pixel> img_s(3, 3);
matrix<lab_pixel> img_d(3, 3);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 100, 20, 30 };
img_s(0, 2) = { 100, 20, 30 };
img_s(1, 0) = { 100, 20, 30 };
img_s(1, 1) = { 100, 20, 30 };
img_s(1, 2) = { 100, 20, 30 };
img_s(2, 0) = { 100, 20, 30 };
img_s(2, 1) = { 100, 20, 30 };
img_s(2, 2) = { 100, 20, 30 };
rotate_image(img_s, img_d, 0, interpolate_quadratic());
DLIB_TEST((img_d(1, 1) == lab_pixel{ 111, 22, 33 }));
}
}
void test_interpolate_bilinear()
{
{
matrix<unsigned char> img_s(2, 2);
img_s(0, 0) = 0;
img_s(0, 1) = 100;
img_s(1, 0) = 100;
img_s(1, 1) = 100;
const_image_view<matrix<unsigned char>> imgv(img_s);
unsigned char result;
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.0 }, result);
DLIB_TEST(result == 50);
}
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.5 }, result);
DLIB_TEST(result == 75);
}
}
{
matrix<rgb_pixel> img_s(2, 2);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 10, 20, 30 };
img_s(1, 0) = { 10, 20, 30 };
img_s(1, 1) = { 10, 20, 30 };
const_image_view<matrix<rgb_pixel>> imgv(img_s);
rgb_pixel result;
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.0 }, result);
DLIB_TEST(result.red == 5);
DLIB_TEST(result.green == 10);
DLIB_TEST(result.blue == 15);
}
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.5 }, result);
DLIB_TEST(result.red == 7);
DLIB_TEST(result.green == 15);
DLIB_TEST(result.blue == 22);
}
}
{
matrix<lab_pixel> img_s(2, 2);
img_s(0, 0) = { 0, 0, 0 };
img_s(0, 1) = { 100, 20, 30 };
img_s(1, 0) = { 100, 20, 30 };
img_s(1, 1) = { 100, 20, 30 };
const_image_view<matrix<lab_pixel>> imgv(img_s);
lab_pixel result;
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.0 }, result);
DLIB_TEST(result.l == 50);
DLIB_TEST(result.a == 10);
DLIB_TEST(result.b == 15);
}
{
interpolate_bilinear()(imgv, dlib::vector<double, 2>{ 0.5, 0.5 }, result);
DLIB_TEST(result.l == 75);
DLIB_TEST(result.a == 15);
DLIB_TEST(result.b == 22);
}
}
}
void test_letterbox_image()
{
print_spinner();
rgb_pixel black(0, 0, 0);
rgb_pixel white(255, 255, 255);
matrix<rgb_pixel> img_s(40, 60);
matrix<rgb_pixel> img_d;
assign_all_pixels(img_s, white);
const auto tform = letterbox_image(img_s, img_d, 30, interpolate_nearest_neighbor());
DLIB_TEST(tform.get_m() == identity_matrix<double>(2) * 0.5);
DLIB_TEST(tform.get_b() == dpoint(0, 5));
// manually generate the target image
matrix<rgb_pixel> img_t(30, 30);
assign_all_pixels(img_t, rgb_pixel(0, 0, 0));
matrix<rgb_pixel> img_w(20, 30);
assign_all_pixels(img_w, rgb_pixel(255, 255, 255));
rectangle r (0, 5, 30 - 1, 25 - 1);
auto si = sub_image(img_t, r);
assign_image(si, img_w);
DLIB_TEST(img_d == img_t);
}
void test_draw_string()
{
print_spinner();
matrix<rgb_pixel> image{48, 48};
assign_all_pixels(image, rgb_pixel{0, 0, 0});
draw_string(image, point{10, 15}, string{"cat"}, rgb_pixel{255, 255, 255});
matrix<rgb_pixel> result;
const std::string data{"gQgLudERwR0JqP9kUiitFNDYSO9rdZzdmeDmricAlM5f5RBqzTlaW6Lp704mTXJq/WXHTQ84wWnGAA=="};
ostringstream sout;
istringstream sin;
base64 base64_coder;
compress_stream::kernel_1ea compressor;
sin.str(data);
base64_coder.decode(sin, sout);
sin.clear();
sin.str(sout.str());
sout.clear();
sout.str("");
compressor.decompress(sin, sout);
sin.clear();
sin.str(sout.str());
deserialize(result, sin);
DLIB_TEST(image == result);
}
template <typename pixel_type>
double psnr(const matrix<pixel_type>& img1, const matrix<pixel_type>& img2)
{
DLIB_TEST(have_same_dimensions(img1, img2));
double mse = 0;
const long nk = width_step(img1) / img1.nc();
const long data_size = img1.size() * nk;
const bool has_alpha = nk == 4;
auto data1 = reinterpret_cast<const uint8_t*>(image_data(img1));
auto data2 = reinterpret_cast<const uint8_t*>(image_data(img2));
for (long i = 0; i < data_size; i += nk)
{
// We are using the default WebP settings, which means 'exact' is disabled.
// RGB values in transparent areas will be modified to improve compression.
// As a result, we skip matching transparent pixels.
if (has_alpha && data1[i + 3] == 0 && data2[i + 3] == 0)
continue;
for (long k = 0; k < nk; ++k)
mse += std::pow(static_cast<double>(data1[i + k]) - static_cast<double>(data2[i + k]), 2);
}
mse /= data_size;
return 20 * std::log10(pixel_traits<pixel_type>::max()) - 10 * std::log10(mse);
}
void test_webp()
{
#ifdef DLIB_WEBP_SUPPORT
print_spinner();
matrix<rgb_pixel> rgb_img, rgb_dec;
matrix<rgb_alpha_pixel> rgba_img, rgba_dec;
matrix<bgr_pixel> bgr_img, bgr_dec;
matrix<bgr_alpha_pixel> bgra_img, bgra_dec;
// this is a matrix<rgb_alpha_pixel> of the 32x32 dlib logo
const std::string data{
"gP79Jk3Zra0ocokRFuNsUUuZg4phoFDDKp9wTEPIHgX3GSQfaiwJIZGVecNTfibjcx8QxSZplz/p"
"st61fSu3N26BEzFl16L7kOsPiktkqJb7poGAXYngdkNPClBOWV0zV300nMmcpKoQ6e9IxLJ9ouJJ"
"++dwNeTNdQN6Ehhk7jdBM62XV1YzcehwRuApNugTjSozbTEqTSdrz1ftXP7rhgVLkWNrnZ2Cd+oF"
"qkIcZKWsnpz0K1JiFMz7J+d3S4aTQSWKH2qezLT/YKGfZsyT3pUCwwdYi/dF/EaUg7mhlRdk66wD"
"WYtoAFObeu85hQbU/uEVhwK6NBSUfLmwIQYtGw+Kr2qKaiTIS6wzcyIRUvI0sVSVeWBXNYPHq6z7"
"t6XcLG5ipOSvGDCUa5nXqnQ8tLKrRpewxvy6M8pzwmw3FqXt3oqq5umxi3MpU5PgU5dFuDor30G/"
"IJr+FtHDWBQHrHlZmbg/NNllK2d0D+fTPNfTYEmOaTdMO8av36523OJK8zXvKWqgPccgjchbIv8O"
"VfO3PwooK9XA23Bt4+nqMlQ9cs9FXmW/QyaoI5/996fShh/KFeup1dsF7VyLu5BDnGX+/t80SaAf"
"2MNPYJZs27klBwZs39u2Eyk37UKTZPK7YFQW+pbMhHInHswcV2TsQHMEA9RONwhkeR7O0JSJrryy"
"2gXvadc+oRqux0Zs1mpOn2f2BSfZnGDbKcgUwcDucI69J30NEKHlvnqZ+4tA3frIEuhZrub9IrHs"
"gQK7HCzJsWfKoF7/p/unykiAL5zh5chNToECkcNNHY9IkRn56bZ6iLv5TrQmWkknjAdP9fY50E1q"
"+asVnWv9DgrtXwJE0pZn/3tHA9CizwkfmF0zu/c0BBixXmi1Vh3E9pf3yVHQIfj96gLGBWTBkLQq"
"DoqWRialGKmH4hnLbNTBqc3lkisAAWdBsobZ5fB27waJbOnoI9LwR6TOohN9IYPR4cSIwStp8qhK"
"np+20vwmZNqPsoD9F9SOlfprkAmrHcP7rw/+yf5fMWps4qj3GuWAElkECI791I4aQsjMlL4aKPoJ"
"+ZAVIooYh1uQLQWNrgxAZRxydbgPAKUs+5pYgGT6Io+HH5piTiuSJowgkBUzA4fX2TmZOaCCLZql"
"d0UnsvoDQLnDhx+uIqzCDut4QDsMRH6j29i1+CnVv6Ye/AAD9GUNlSSIS5pX22gfd6YXrEQYayQH"
"mN72c8oHiw9zf6g/Xz0XCpkXi1ebiDlI21RnHuYw/ml9U0QWqUSk8kPAdUPL1QE7DB+/r1sf0A/+"
"IcJuiEXFvglVJpmfCewfvvtzEJHO1wLdK32mZ97CQvu9Er6zrc+bY5Gh9IOL+loqz8etxQE8I2bI"
"9+s0MTYZgHPZnqJK1NsFLHWGyUNzoRr63jkwQjdiJn1p/lbtzOa5TkhsOLzAR+jjb8Inueg32frv"
"xRHC2o92KkTqOomEmghgnGtdXl77vYTYMt/CUcbqGOAwiSQzw6jZtA5UTXI/6Fc14lMD3BBThbbm"
"KV9u+n5SN66r6hogiFiWUoU9gG20AaFCz4Lk2EqBRM+SnRaNoY/u1zIFRu/8JoghowDNB9hCQgqT"
"14AwF1TDGNTm1hgRtRX5lOrx8WgTXbwGl5YXHqN+oufn3m9FQ1dWxtqHH+dwNUD4MvEGIbNPauBA"
"+Fr4ozAJ8xBrovuVQjxfswoz/xkYPoRbWjhZuYi3vWqeCf6Pvp1+Ak3rd2cRV5HXAjksFE54eerP"
"Kst9eHlpTTEbe2pRs4V+nlZgPI0/lH0z5D8IRBriTX/kujcqwZAj5rDQQndhT4FYxEj7ldZuxC2D"
"yxenJ2goCV0x+UPjPxjRPCHb1EiIX7evPtyvr5UI2O48e7sixwA="
};
ostringstream sout;
istringstream sin;
base64 base64_coder;
compress_stream::kernel_1ea compressor;
sin.str(data);
base64_coder.decode(sin, sout);
sin.clear();
sin.str(sout.str());
sout.clear();
sout.str("");
compressor.decompress(sin, sout);
sin.clear();
sin.str(sout.str());
deserialize(rgba_img, sin);
for (auto quality : {75., 101.})
{
save_webp(rgba_img, "test_rgba.webp", quality);
load_webp(rgba_dec, "test_rgba.webp");
if (quality > 100)
DLIB_TEST(psnr(rgba_img, rgba_dec) == std::numeric_limits<double>::infinity());
else
DLIB_TEST(psnr(rgba_img, rgba_dec) > 30);
assign_image(bgra_img, rgba_img);
save_webp(bgra_img, "test_bgra.webp", quality);
load_webp(bgra_dec, "test_bgra.webp");
if (quality > 100)
DLIB_TEST(psnr(bgra_img, bgra_dec) == std::numeric_limits<double>::infinity());
else
DLIB_TEST(psnr(bgra_img, bgra_dec) > 30);
// Here we assign an image with an alpha channel to an image without an alpha channel.
// Since we are not using the exact mode in WebP, the PSNR will be quite low, since
// pixels in transparent areas will have different values.
assign_image(rgb_img, rgba_img);
save_webp(rgb_img, "test_rgb.webp", quality);
load_webp(rgb_dec, "test_rgb.webp");
if (quality > 100)
DLIB_TEST(psnr(rgb_img, rgb_dec) == std::numeric_limits<double>::infinity());
else
DLIB_TEST(psnr(rgb_img, rgb_dec) > 15);
assign_image(bgr_img, rgb_img);
save_webp(bgr_img, "test_bgr.webp", quality);
load_webp(bgr_dec, "test_bgr.webp");
if (quality > 100)
DLIB_TEST(psnr(bgr_img, bgr_dec) == std::numeric_limits<double>::infinity());
else
DLIB_TEST(psnr(bgr_img, bgr_dec) > 15);
}
#endif
}
// ----------------------------------------------------------------------------------------
class image_tester : public tester
{
public:
image_tester (
) :
tester ("test_image",
"Runs tests on the image processing objects and functions.")
{}
void perform_test (
)
{
image_test();
run_hough_test();
test_extract_image_chips();
test_integral_image<long, unsigned char>();
test_integral_image<double, int>();
test_integral_image<long, unsigned char>();
test_integral_image<double, float>();
test_zero_border_pixels();
test_filtering<unsigned char>(false,1);
test_filtering<unsigned char>(true,1);
test_filtering<unsigned char>(false,3);
test_filtering<unsigned char>(true,3);
test_filtering<int>(false,1);
test_filtering<int>(true,1);
test_filtering<int>(false,3);
test_filtering<int>(true,3);
test_label_connected_blobs();
test_label_connected_blobs2();
test_downsampled_filtering();
test_segment_image<unsigned char>();
test_segment_image<unsigned short>();
test_segment_image<double>();
test_segment_image<int>();
test_segment_image<rgb_pixel>();
test_segment_image<rgb_alpha_pixel>();
test_dng_floats<float>(1);
test_dng_floats<double>(1);
test_dng_floats<long double>(1);
test_dng_floats<float>(1e30);
test_dng_floats<double>(1e30);
test_dng_floats<long double>(1e30);
test_dng_float_int();
dlib::rand rnd;
for (int i = 0; i < 10; ++i)
{
// the spatial filtering stuff is the same as xcorr_same when the filter
// sizes are odd.
test_filtering2(3,3,rnd);
test_filtering2(5,5,rnd);
test_filtering2(7,7,rnd);
}
for (int i = 0; i < 100; ++i)
test_filtering_center<float>(rnd);
for (int i = 0; i < 100; ++i)
test_filtering_center<int>(rnd);
for (int i = 0; i < 100; ++i)
test_separable_filtering_center<int>(rnd);
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);
}
{
matrix<int> a(3,4);
array2d<unsigned char> b(3,4);
DLIB_TEST(have_same_dimensions(a,b));
}
{
matrix<int> a(4,4);
array2d<unsigned char> b(3,4);
DLIB_TEST(!have_same_dimensions(a,b));
static_assert(is_image_type<matrix<int>>::value, "should be true");
static_assert(!is_image_type<int>::value, "should be false");
}
test_partition_pixels();
test_resize_image_with_interpolation<interpolate_bilinear>();
test_null_rotate_image_with_interpolation();
test_null_rotate_image_with_interpolation_quadratic();
test_interpolate_bilinear();
test_letterbox_image();
test_draw_string();
test_webp();
}
} a;
}