image.cpp

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/*
    Copyright 2005-2007 Adobe Systems Incorporated
   
    Use, modification and distribution are subject to the Boost Software License,
    Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
    http://www.boost.org/LICENSE_1_0.txt).

    See http://opensource.adobe.com/gil for most recent version including documentation.
*/
// image_test.cpp : 
//

#ifdef _MSC_VER
//#pragma warning(disable : 4244)     // conversion from 'gil::image<V,Alloc>::coord_t' to 'int', possible loss of data (visual studio compiler doesn't realize that the two types are the same)
#pragma warning(disable : 4503)     // decorated name length exceeded, name was truncated
#endif

#include <string>
#include <vector>
#include <ios>
#include <iostream>
#include <fstream>
#include <map>
#include <boost/lambda/lambda.hpp>
#include <boost/lambda/bind.hpp>
#include <boost/mpl/vector.hpp>
#include <boost/gil/extension/dynamic_image/dynamic_image_all.hpp>
#include <boost/crc.hpp>

using namespace boost::gil;
using namespace std;
using namespace boost;

extern rgb8c_planar_view_t sample_view;
void error_if(bool condition);


// When BOOST_GIL_GENERATE_REFERENCE_DATA is defined, the reference data is generated and saved.
// When it is undefined, regression tests are checked against it
//#define BOOST_GIL_GENERATE_REFERENCE_DATA

////////////////////////////////////////////////////
///
///  Some algorithms to use in testing
///
////////////////////////////////////////////////////

template <typename GrayView, typename R>
void gray_image_hist(const GrayView& img_view, R& hist) {
//    for_each_pixel(img_view,++lambda::var(hist)[lambda::_1]);
    for (typename GrayView::iterator it=img_view.begin(); it!=img_view.end(); ++it)
        ++hist[*it];
}

template <typename V, typename R>
void get_hist(const V& img_view, R& hist) {
    gray_image_hist(color_converted_view<gray8_pixel_t>(img_view), hist);
}

// testing custom color conversion
template <typename C1, typename C2>
struct my_color_converter_impl : public default_color_converter_impl<C1,C2> {};
template <typename C1>
struct my_color_converter_impl<C1,gray_t> {
    template <typename P1, typename P2>
    void operator()(const P1& src, P2& dst) const {
        default_color_converter_impl<C1,gray_t>()(src,dst);
        get_color(dst,gray_color_t())=channel_invert(get_color(dst,gray_color_t()));
    }
};

struct my_color_converter {
    template <typename SrcP,typename DstP>
    void operator()(const SrcP& src,DstP& dst) const { 
        typedef typename color_space_type<SrcP>::type src_cs_t;
        typedef typename color_space_type<DstP>::type dst_cs_t;
        my_color_converter_impl<src_cs_t,dst_cs_t>()(src,dst);
    }
};

// Models a Unary Function
template <typename P>   // Models PixelValueConcept
struct mandelbrot_fn {
    typedef point2<std::ptrdiff_t>    point_t;

    typedef mandelbrot_fn        const_t;
    typedef P                    value_type;
    typedef value_type           reference;
    typedef value_type           const_reference;
    typedef point_t              argument_type;
    typedef reference            result_type;
    BOOST_STATIC_CONSTANT(bool, is_mutable=false);

    value_type                    _in_color,_out_color;
    point_t                       _img_size;
    static const int MAX_ITER=100;        // max number of iterations

    mandelbrot_fn() {}
    mandelbrot_fn(const point_t& sz, const value_type& in_color, const value_type& out_color) : _in_color(in_color), _out_color(out_color), _img_size(sz) {}

    result_type operator()(const point_t& p) const {
        // normalize the coords to (-2..1, -1.5..1.5)
        // (actually make y -1.0..2 so it is asymmetric, so we can verify some view factory methods)
        double t=get_num_iter(point2<double>(p.x/(double)_img_size.x*3-2, p.y/(double)_img_size.y*3-1.0f));//1.5f));
        t=pow(t,0.2);

        value_type ret;
        for (int k=0; k<num_channels<P>::value; ++k)
            ret[k]=(typename channel_type<value_type>::type)(_in_color[k]*t + _out_color[k]*(1-t));
        return ret;
    }

private:
    double get_num_iter(const point2<double>& p) const {
        point2<double> Z(0,0);
        for (int i=0; i<MAX_ITER; ++i) {
            Z = point2<double>(Z.x*Z.x - Z.y*Z.y + p.x, 2*Z.x*Z.y + p.y);
            if (Z.x*Z.x + Z.y*Z.y > 4)
                return i/(double)MAX_ITER;
        }
        return 0;
    }
};

template <typename T>
void x_gradient(const T& src, const gray8s_view_t& dst) {
    for (int y=0; y<src.height(); ++y) {
        typename T::x_iterator src_it = src.row_begin(y);
        gray8s_view_t::x_iterator dst_it = dst.row_begin(y);

        for (int x=1; x<src.width()-1; ++x)
            dst_it[x] = (src_it[x+1] - src_it[x-1]) / 2;
    }
}

// A quick test whether a view is homogeneous

template <typename Pixel>
struct pixel_is_homogeneous : public mpl::true_ {};

template <typename P, typename C, typename L>
struct pixel_is_homogeneous<packed_pixel<P,C,L> > : public mpl::false_ {};

template <typename View>
struct view_is_homogeneous : public pixel_is_homogeneous<typename View::value_type> {};


////////////////////////////////////////////////////
///
///  Tests image view transformations and algorithms
///
////////////////////////////////////////////////////
class image_test {
public:
    virtual void initialize() {}
    virtual void finalize() {}
    virtual ~image_test() {}

    void run();
protected:
    virtual void check_view_impl(const rgb8c_view_t& view, const string& name)=0;
    template <typename View>
    void check_view(const View& img_view, const string& name) {
        rgb8_image_t rgb_img(img_view.dimensions());
        copy_and_convert_pixels(img_view,view(rgb_img));
        check_view_impl(const_view(rgb_img), name);
    }
private:
    template <typename Img> void basic_test(const string& prefix);
    template <typename View> void view_transformations_test(const View& img_view, const string& prefix);
    template <typename View> void homogeneous_view_transformations_test(const View& img_view, const string& prefix, mpl::true_);
    template <typename View> void homogeneous_view_transformations_test(const View& img_view, const string& prefix, mpl::false_) {}
    template <typename View> void histogram_test(const View& img_view, const string& prefix);
    void virtual_view_test();
    void packed_image_test();
    void dynamic_image_test();
    template <typename Img> void image_all_test(const string& prefix);
};


// testing image iterators, clone, fill, locators, color convert
template <typename Img>
void image_test::basic_test(const string& prefix) {
    typedef typename Img::view_t View;

    // make a 20x20 image
    Img img(typename View::point_t(20,20));
    const View& img_view=view(img);

    // fill it with red
    rgb8_pixel_t red8(255,0,0), green8(0,255,0), blue8(0,0,255), white8(255,255,255);
    typename View::value_type red,green,blue,white;
    color_convert(red8,red);
    default_color_converter()(red8,red);
    red=color_convert_deref_fn<rgb8_ref_t,typename Img::view_t::value_type>()(red8);

    color_convert(green8,green);
    color_convert(blue8,blue);
    color_convert(white8,white);
    fill(img_view.begin(),img_view.end(),red);

    color_convert(red8,img_view[0]);

    // pointer to first pixel of second row
    typename View::reference rt=img_view.at(0,0)[img_view.width()];
    typename View::x_iterator ptr=&rt;
    typename View::reference rt2=*(img_view.at(0,0)+img_view.width());
    typename View::x_iterator ptr2=&rt2;
    error_if(ptr!=ptr2);
    error_if(img_view.x_at(0,0)+10!=10+img_view.x_at(0,0));

    // draw a blue line along the diagonal
    typename View::xy_locator loc=img_view.xy_at(0,img_view.height()-1);
    for (int y=0; y<img_view.height(); ++y) {
        *loc=blue;
        ++loc.x();
        loc.y()--;
    }

    // draw a green dotted line along the main diagonal with step of 3
    loc=img_view.xy_at(img_view.width()-1,img_view.height()-1);
    while (loc.x()>=img_view.x_at(0,0)) {
        *loc=green;
        loc-=typename View::point_t(3,3);
    }

    // Clone and make every red pixel white
    Img imgWhite(img);
    for (typename View::iterator it=view(imgWhite).end(); (it-1)!=view(imgWhite).begin(); --it) {
        if (*(it-1)==red)
            *(it-1)=white;
    }

    check_view(img_view,prefix+"red_x");
    check_view(view(imgWhite),prefix+"white_x");
}

template <typename View>
void image_test::histogram_test(const View& img_view, const string& prefix) {
//  vector<int> histogram(255,0);
//  get_hist(cropped,histogram.begin());
    unsigned char histogram[256];
    fill(histogram,histogram+256,0);
    get_hist(img_view,histogram);
    gray8c_view_t hist_view=interleaved_view(256,1,(const gray8_pixel_t*)histogram,256);
    check_view(hist_view,prefix+"histogram");
}


template <typename View>
void image_test::view_transformations_test(const View& img_view, const string& prefix) {
    check_view(img_view,prefix+"original");

    check_view(subimage_view(img_view, iround(img_view.dimensions()/4), iround(img_view.dimensions()/2)),prefix+"cropped");
    check_view(color_converted_view<gray8_pixel_t>(img_view),prefix+"gray8");
    check_view(color_converted_view<gray8_pixel_t>(img_view,my_color_converter()),prefix+"my_gray8");
    check_view(transposed_view(img_view),prefix+"transpose");
    check_view(rotated180_view(img_view),prefix+"rot180");
    check_view(rotated90cw_view(img_view),prefix+"90cw");
    check_view(rotated90ccw_view(img_view),prefix+"90ccw");
    check_view(flipped_up_down_view(img_view),prefix+"flipped_ud");
    check_view(flipped_left_right_view(img_view),prefix+"flipped_lr");
    check_view(subsampled_view(img_view,typename View::point_t(2,1)),prefix+"subsampled");   
    check_view(kth_channel_view<0>(img_view),prefix+"0th_k_channel");
    homogeneous_view_transformations_test(img_view, prefix, view_is_homogeneous<View>());
}

template <typename View>
void image_test::homogeneous_view_transformations_test(const View& img_view, const string& prefix, mpl::true_) {
    check_view(nth_channel_view(img_view,0),prefix+"0th_n_channel");
}


void image_test::virtual_view_test() {
    typedef mandelbrot_fn<rgb8_pixel_t> deref_t;
    typedef deref_t::point_t            point_t;
    typedef virtual_2d_locator<deref_t,false> locator_t;
    typedef image_view<locator_t> my_virt_view_t;

    boost::function_requires<PixelLocatorConcept<locator_t> >();
    gil_function_requires<StepIteratorConcept<locator_t::x_iterator> >();

    point_t dims(200,200);
    my_virt_view_t mandel(dims, locator_t(point_t(0,0), point_t(1,1), deref_t(dims, rgb8_pixel_t(255,0,255), rgb8_pixel_t(0,255,0))));

    gray8s_image_t img(dims);
    fill_pixels(view(img),0);   // our x_gradient algorithm doesn't change the first & last column, so make sure they are 0
    x_gradient(color_converted_view<gray8_pixel_t>(mandel), view(img));
    check_view(color_converted_view<gray8_pixel_t>(const_view(img)), "mandelLuminosityGradient");

    view_transformations_test(mandel,"virtual_");
    histogram_test(mandel,"virtual_");
}

// Test alignment and packed images
void image_test::packed_image_test() {