/src/libjxl/lib/jxl/enc_comparator.cc
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1 | | // Copyright (c) the JPEG XL Project Authors. All rights reserved. |
2 | | // |
3 | | // Use of this source code is governed by a BSD-style |
4 | | // license that can be found in the LICENSE file. |
5 | | |
6 | | #include "lib/jxl/enc_comparator.h" |
7 | | |
8 | | #include <jxl/cms_interface.h> |
9 | | #include <jxl/memory_manager.h> |
10 | | |
11 | | #include <algorithm> |
12 | | #include <cstddef> |
13 | | #include <memory> |
14 | | |
15 | | #include "lib/jxl/base/common.h" |
16 | | #include "lib/jxl/base/compiler_specific.h" |
17 | | #include "lib/jxl/base/data_parallel.h" |
18 | | #include "lib/jxl/base/status.h" |
19 | | #include "lib/jxl/color_encoding_internal.h" |
20 | | #include "lib/jxl/enc_gamma_correct.h" |
21 | | #include "lib/jxl/enc_image_bundle.h" |
22 | | #include "lib/jxl/image.h" |
23 | | #include "lib/jxl/image_bundle.h" |
24 | | #include "lib/jxl/image_metadata.h" |
25 | | |
26 | | namespace jxl { |
27 | | namespace { |
28 | | |
29 | | // color is linear, but blending happens in gamma-compressed space using |
30 | | // (gamma-compressed) grayscale background color, alpha image represents |
31 | | // weights of the sRGB colors in the [0 .. (1 << bit_depth) - 1] interval, |
32 | | // output image is in linear space. |
33 | | void AlphaBlend(const Image3F& in, const size_t c, float background_linear, |
34 | 0 | const ImageF& alpha, Image3F* out) { |
35 | 0 | const float background = LinearToSrgb8Direct(background_linear); |
36 | |
|
37 | 0 | for (size_t y = 0; y < out->ysize(); ++y) { |
38 | 0 | const float* JXL_RESTRICT row_a = alpha.ConstRow(y); |
39 | 0 | const float* JXL_RESTRICT row_i = in.ConstPlaneRow(c, y); |
40 | 0 | float* JXL_RESTRICT row_o = out->PlaneRow(c, y); |
41 | 0 | for (size_t x = 0; x < out->xsize(); ++x) { |
42 | 0 | const float a = row_a[x]; |
43 | 0 | if (a <= 0.f) { |
44 | 0 | row_o[x] = background_linear; |
45 | 0 | } else if (a >= 1.f) { |
46 | 0 | row_o[x] = row_i[x]; |
47 | 0 | } else { |
48 | 0 | const float w_fg = a; |
49 | 0 | const float w_bg = 1.0f - w_fg; |
50 | 0 | const float fg = w_fg * LinearToSrgb8Direct(row_i[x]); |
51 | 0 | const float bg = w_bg * background; |
52 | 0 | row_o[x] = Srgb8ToLinearDirect(fg + bg); |
53 | 0 | } |
54 | 0 | } |
55 | 0 | } |
56 | 0 | } |
57 | | |
58 | 0 | void AlphaBlend(float background_linear, ImageBundle* io_linear_srgb) { |
59 | | // No alpha => all opaque. |
60 | 0 | if (!io_linear_srgb->HasAlpha()) return; |
61 | | |
62 | 0 | for (size_t c = 0; c < 3; ++c) { |
63 | 0 | AlphaBlend(*io_linear_srgb->color(), c, background_linear, |
64 | 0 | *io_linear_srgb->alpha(), io_linear_srgb->color()); |
65 | 0 | } |
66 | 0 | } |
67 | | |
68 | | Status ComputeScoreImpl(const ImageBundle& rgb0, const ImageBundle& rgb1, |
69 | 0 | Comparator* comparator, ImageF* distmap, float& score) { |
70 | 0 | JXL_RETURN_IF_ERROR(comparator->SetReferenceImage(rgb0)); |
71 | 0 | JXL_RETURN_IF_ERROR(comparator->CompareWith(rgb1, distmap, &score)); |
72 | 0 | return true; |
73 | 0 | } |
74 | | |
75 | | } // namespace |
76 | | |
77 | | Status ComputeScore(const ImageBundle& rgb0, const ImageBundle& rgb1, |
78 | | Comparator* comparator, const JxlCmsInterface& cms, |
79 | | float* score, ImageF* diffmap, ThreadPool* pool, |
80 | 0 | bool ignore_alpha) { |
81 | 0 | JxlMemoryManager* memory_manager = rgb0.memory_manager(); |
82 | | // Convert to linear sRGB (unless already in that space) |
83 | 0 | auto metadata0 = jxl::make_unique<ImageMetadata>(); |
84 | 0 | *metadata0 = *rgb0.metadata(); |
85 | 0 | auto store0 = jxl::make_unique<ImageBundle>(memory_manager, metadata0.get()); |
86 | 0 | const ImageBundle* linear_srgb0; |
87 | 0 | JXL_RETURN_IF_ERROR( |
88 | 0 | TransformIfNeeded(rgb0, ColorEncoding::LinearSRGB(rgb0.IsGray()), cms, |
89 | 0 | pool, store0.get(), &linear_srgb0)); |
90 | 0 | auto metadata1 = jxl::make_unique<ImageMetadata>(); |
91 | 0 | *metadata1 = *rgb1.metadata(); |
92 | 0 | auto store1 = jxl::make_unique<ImageBundle>(memory_manager, metadata1.get()); |
93 | 0 | const ImageBundle* linear_srgb1; |
94 | 0 | JXL_RETURN_IF_ERROR( |
95 | 0 | TransformIfNeeded(rgb1, ColorEncoding::LinearSRGB(rgb1.IsGray()), cms, |
96 | 0 | pool, store1.get(), &linear_srgb1)); |
97 | | |
98 | | // No alpha: skip blending, only need a single call to Butteraugli. |
99 | 0 | if (ignore_alpha || (!rgb0.HasAlpha() && !rgb1.HasAlpha())) { |
100 | 0 | JXL_RETURN_IF_ERROR(ComputeScoreImpl(*linear_srgb0, *linear_srgb1, |
101 | 0 | comparator, diffmap, *score)); |
102 | 0 | return true; |
103 | 0 | } |
104 | | |
105 | | // Blend on black and white backgrounds |
106 | | |
107 | 0 | ImageF diffmap_black; |
108 | 0 | float dist_black; |
109 | 0 | { |
110 | 0 | const float black = 0.0f; |
111 | 0 | JXL_ASSIGN_OR_RETURN(ImageBundle blended_black0, linear_srgb0->Copy()); |
112 | 0 | JXL_ASSIGN_OR_RETURN(ImageBundle blended_black1, linear_srgb1->Copy()); |
113 | 0 | AlphaBlend(black, &blended_black0); |
114 | 0 | AlphaBlend(black, &blended_black1); |
115 | 0 | JXL_RETURN_IF_ERROR(ComputeScoreImpl(blended_black0, blended_black1, |
116 | 0 | comparator, &diffmap_black, |
117 | 0 | dist_black)); |
118 | 0 | } |
119 | | |
120 | 0 | ImageF diffmap_white; |
121 | 0 | float dist_white; |
122 | 0 | { |
123 | 0 | const float white = 1.0f; |
124 | 0 | JXL_ASSIGN_OR_RETURN(ImageBundle blended_white0, linear_srgb0->Copy()); |
125 | 0 | JXL_ASSIGN_OR_RETURN(ImageBundle blended_white1, linear_srgb1->Copy()); |
126 | 0 | AlphaBlend(white, &blended_white0); |
127 | 0 | AlphaBlend(white, &blended_white1); |
128 | 0 | JXL_RETURN_IF_ERROR(ComputeScoreImpl(blended_white0, blended_white1, |
129 | 0 | comparator, &diffmap_white, |
130 | 0 | dist_white)); |
131 | 0 | } |
132 | | |
133 | | // diffmap and return values are the max of diffmap_black/white. |
134 | 0 | if (diffmap != nullptr) { |
135 | 0 | const size_t xsize = rgb0.xsize(); |
136 | 0 | const size_t ysize = rgb0.ysize(); |
137 | 0 | JXL_ASSIGN_OR_RETURN(*diffmap, |
138 | 0 | ImageF::Create(memory_manager, xsize, ysize)); |
139 | 0 | for (size_t y = 0; y < ysize; ++y) { |
140 | 0 | const float* JXL_RESTRICT row_black = diffmap_black.ConstRow(y); |
141 | 0 | const float* JXL_RESTRICT row_white = diffmap_white.ConstRow(y); |
142 | 0 | float* JXL_RESTRICT row_out = diffmap->Row(y); |
143 | 0 | for (size_t x = 0; x < xsize; ++x) { |
144 | 0 | row_out[x] = std::max(row_black[x], row_white[x]); |
145 | 0 | } |
146 | 0 | } |
147 | 0 | } |
148 | 0 | *score = std::max(dist_black, dist_white); |
149 | 0 | return true; |
150 | 0 | } |
151 | | |
152 | | } // namespace jxl |