switch uses of nth_channel_view to boost::gil::index_t

include/boost/gil/image_processing/adaptive_histogram_equalization.hpp

@@ -157,9 +157,9 @@ void non_overlapping_interpolated_clahe(
     using dst_channel_t    = typename channel_type<DstView>::type;
     using coord_t          = typename SrcView::x_coord_t;
 
-    std::size_t const channels = num_channels<SrcView>::value;
-    coord_t const width        = src_view.width();
-    coord_t const height       = src_view.height();
+    index_t const channels = num_channels<SrcView>::value;
+    coord_t const width    = src_view.width();
+    coord_t const height   = src_view.height();
 
     // Find control points
 
@@ -184,7 +184,7 @@ void non_overlapping_interpolated_clahe(
 
     copy_pixels(src_view, subimage_view(view(padded_img), top_left_x, top_left_y, width, height));
 
-    for (std::size_t k = 0; k < channels; k++)
+    for (index_t k = 0; k < channels; k++)
     {
         std::vector<histogram<source_channel_t>> prev_row(new_width / tile_width_x),
             next_row((new_width / tile_width_x));

include/boost/gil/image_processing/convolve.hpp

@@ -430,7 +430,7 @@ void convolve_2d(SrcView const& src_view, Kernel const& kernel, DstView const& d
         typename color_space_type<DstView>::type
     >::value, "Source and destination views must have pixels with the same color space");
 
-    for (std::size_t i = 0; i < src_view.num_channels(); i++)
+    for (index_t i = 0; i < src_view.num_channels(); i++)
     {
         detail::convolve_2d_impl(
             nth_channel_view(src_view, i),

include/boost/gil/image_processing/filter.hpp

@@ -124,7 +124,7 @@ void median_filter(SrcView const& src_view, DstView const& dst_view, std::size_t
             src_view.height()
         );
 
-    for (std::size_t channel = 0; channel < extended_view.num_channels(); channel++)
+    for (index_t channel = 0; channel < extended_view.num_channels(); channel++)
     {
         detail::filter_median_impl(
             nth_channel_view(extended_view, channel),

include/boost/gil/image_processing/histogram_equalization.hpp

@@ -117,13 +117,13 @@ void histogram_equalization(
     using dst_channel_t    = typename channel_type<DstView>::type;
     using coord_t          = typename SrcView::x_coord_t;
 
-    std::size_t const channels = num_channels<SrcView>::value;
-    coord_t const width        = src_view.width();
-    coord_t const height       = src_view.height();
-    std::size_t pixel_max      = (std::numeric_limits<dst_channel_t>::max)();
-    std::size_t pixel_min      = (std::numeric_limits<dst_channel_t>::min)();
+    index_t const channels = num_channels<SrcView>::value;
+    coord_t const width    = src_view.width();
+    coord_t const height   = src_view.height();
+    std::size_t pixel_max  = (std::numeric_limits<dst_channel_t>::max)();
+    std::size_t pixel_min  = (std::numeric_limits<dst_channel_t>::min)();
 
-    for (std::size_t i = 0; i < channels; i++)
+    for (index_t i = 0; i < channels; i++)
     {
         histogram<source_channel_t> h;
         fill_histogram(nth_channel_view(src_view, i), h, bin_width, false, false, mask, src_mask);

include/boost/gil/image_processing/histogram_matching.hpp

@@ -163,15 +163,15 @@ void histogram_matching(
     using dst_channel_t    = typename channel_type<DstView>::type;
     using coord_t          = typename SrcView::x_coord_t;
 
-    std::size_t const channels     = num_channels<SrcView>::value;
+    index_t const channels         = num_channels<SrcView>::value;
     coord_t const width            = src_view.width();
     coord_t const height           = src_view.height();
     source_channel_t src_pixel_min = (std::numeric_limits<source_channel_t>::min)();
     source_channel_t src_pixel_max = (std::numeric_limits<source_channel_t>::max)();
     ref_channel_t ref_pixel_min    = (std::numeric_limits<ref_channel_t>::min)();
     ref_channel_t ref_pixel_max    = (std::numeric_limits<ref_channel_t>::max)();
 
-    for (std::size_t i = 0; i < channels; i++)
+    for (index_t i = 0; i < channels; i++)
     {
         histogram<source_channel_t> src_histogram;
         histogram<ref_channel_t> ref_histogram;

include/boost/gil/image_processing/morphology.hpp

@@ -112,7 +112,7 @@ void morph(SrcView const& src_view, DstView const& dst_view, Kernel const& ker_m
 
     gil::image<typename DstView::value_type> intermediate_img(src_view.dimensions());
 
-    for (std::size_t i = 0; i < src_view.num_channels(); i++)
+    for (index_t i = 0; i < src_view.num_channels(); i++)
     {
         morph_impl(nth_channel_view(src_view, i), nth_channel_view(view(intermediate_img), i),
                    ker_mat, identifier);
@@ -153,7 +153,7 @@ void difference(SrcView const& src_view1, SrcView const& src_view2, DiffView con
     gil_function_requires<ColorSpacesCompatibleConcept<
         typename color_space_type<SrcView>::type, typename color_space_type<DiffView>::type>>();
 
-    for (std::size_t i = 0; i < src_view1.num_channels(); i++)
+    for (index_t i = 0; i < src_view1.num_channels(); i++)
     {
         difference_impl(nth_channel_view(src_view1, i), nth_channel_view(src_view2, i),
                         nth_channel_view(diff_view, i));

include/boost/gil/image_processing/threshold.hpp

@@ -337,7 +337,7 @@ void threshold_optimal
 {
     if (mode == threshold_optimal_value::otsu)
     {
-        for (std::size_t i = 0; i < src_view.num_channels(); i++)
+        for (index_t i = 0; i < src_view.num_channels(); i++)
         {
             detail::otsu_impl
                 (nth_channel_view(src_view, i), nth_channel_view(dst_view, i), direction);