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-rw-r--r--third_party/jpeg-xl/lib/jxl/splines_test.cc256
1 files changed, 116 insertions, 140 deletions
diff --git a/third_party/jpeg-xl/lib/jxl/splines_test.cc b/third_party/jpeg-xl/lib/jxl/splines_test.cc
index d812545a37..83cc524234 100644
--- a/third_party/jpeg-xl/lib/jxl/splines_test.cc
+++ b/third_party/jpeg-xl/lib/jxl/splines_test.cc
@@ -23,7 +23,6 @@
#include "lib/jxl/chroma_from_luma.h"
#include "lib/jxl/enc_aux_out.h"
#include "lib/jxl/enc_bit_writer.h"
-#include "lib/jxl/enc_params.h"
#include "lib/jxl/enc_splines.h"
#include "lib/jxl/image.h"
#include "lib/jxl/image_ops.h"
@@ -45,10 +44,6 @@ std::ostream& operator<<(std::ostream& os, const Spline& spline) {
namespace {
using test::ReadTestData;
-using ::testing::AllOf;
-using ::testing::Field;
-using ::testing::FloatNear;
-using ::testing::Pointwise;
constexpr int kQuantizationAdjustment = 0;
const ColorCorrelationMap* const cmap = new ColorCorrelationMap;
@@ -73,127 +68,75 @@ std::vector<Spline> DequantizeSplines(const Splines& splines) {
return dequantized;
}
-MATCHER(ControlPointIs, "") {
- const Spline::Point& actual = std::get<0>(arg);
- const Spline::Point& expected = std::get<1>(arg);
- return testing::ExplainMatchResult(
- AllOf(Field(&Spline::Point::x, FloatNear(expected.x, kTolerance)),
- Field(&Spline::Point::y, FloatNear(expected.y, kTolerance))),
- actual, result_listener);
-}
-
-MATCHER(ControlPointsMatch, "") {
- const Spline& actual = std::get<0>(arg);
- const Spline& expected = std::get<1>(arg);
- return testing::ExplainMatchResult(
- Field(&Spline::control_points,
- Pointwise(ControlPointIs(), expected.control_points)),
- actual, result_listener);
-}
-
-MATCHER(SplinesMatch, "") {
- const Spline& actual = std::get<0>(arg);
- const Spline& expected = std::get<1>(arg);
- if (!testing::ExplainMatchResult(ControlPointsMatch(), arg,
- result_listener)) {
- return false;
- }
- for (int i = 0; i < 3; ++i) {
- size_t color_dct_size =
- sizeof(expected.color_dct[i]) / sizeof(expected.color_dct[i][0]);
- for (size_t j = 0; j < color_dct_size; j++) {
- testing::StringMatchResultListener color_dct_listener;
- if (!testing::ExplainMatchResult(
- FloatNear(expected.color_dct[i][j], kTolerance),
- actual.color_dct[i][j], &color_dct_listener)) {
- *result_listener << ", where color_dct[" << i << "][" << j
- << "] don't match, " << color_dct_listener.str();
- return false;
- }
- }
- }
- size_t sigma_dct_size =
- sizeof(expected.sigma_dct) / sizeof(expected.sigma_dct[0]);
- for (size_t i = 0; i < sigma_dct_size; i++) {
- testing::StringMatchResultListener sigma_listener;
- if (!testing::ExplainMatchResult(
- FloatNear(expected.sigma_dct[i], kTolerance), actual.sigma_dct[i],
- &sigma_listener)) {
- *result_listener << ", where sigma_dct[" << i << "] don't match, "
- << sigma_listener.str();
- return false;
- }
- }
- return true;
-}
-
} // namespace
TEST(SplinesTest, Serialization) {
- std::vector<Spline> spline_data = {
- {/*control_points=*/{
- {109, 54}, {218, 159}, {80, 3}, {110, 274}, {94, 185}, {17, 277}},
- /*color_dct=*/
- {{36.3, 39.7, 23.2, 67.5, 4.4, 71.5, 62.3, 32.3, 92.2, 10.1, 10.8,
- 9.2, 6.1, 10.5, 79.1, 7, 24.6, 90.8, 5.5, 84, 43.8, 49,
- 33.5, 78.9, 54.5, 77.9, 62.1, 51.4, 36.4, 14.3, 83.7, 35.4},
- {9.4, 53.4, 9.5, 74.9, 72.7, 26.7, 7.9, 0.9, 84.9, 23.2, 26.5,
- 31.1, 91, 11.7, 74.1, 39.3, 23.7, 82.5, 4.8, 2.7, 61.2, 96.4,
- 13.7, 66.7, 62.9, 82.4, 5.9, 98.7, 21.5, 7.9, 51.7, 63.1},
- {48, 39.3, 6.9, 26.3, 33.3, 6.2, 1.7, 98.9, 59.9, 59.6, 95,
- 61.3, 82.7, 53, 6.1, 30.4, 34.7, 96.9, 93.4, 17, 38.8, 80.8,
- 63, 18.6, 43.6, 32.3, 61, 20.2, 24.3, 28.3, 69.1, 62.4}},
- /*sigma_dct=*/{32.7, 21.5, 44.4, 1.8, 45.8, 90.6, 29.3, 59.2,
- 23.7, 85.2, 84.8, 27.2, 42.1, 84.1, 50.6, 17.6,
- 93.7, 4.9, 2.6, 69.8, 94.9, 52, 24.3, 18.8,
- 12.1, 95.7, 28.5, 81.4, 89.9, 31.4, 74.8, 52}},
- {/*control_points=*/{{172, 309},
- {196, 277},
- {42, 238},
- {114, 350},
- {307, 290},
- {316, 269},
- {124, 66},
- {233, 267}},
- /*color_dct=*/
- {{15, 28.9, 22, 6.6, 41.8, 83, 8.6, 56.8, 68.9, 9.7, 5.4,
- 19.8, 70.8, 90, 52.5, 65.2, 7.8, 23.5, 26.4, 72.2, 64.7, 87.1,
- 1.3, 67.5, 46, 68.4, 65.4, 35.5, 29.1, 13, 41.6, 23.9},
- {47.7, 79.4, 62.7, 29.1, 96.8, 18.5, 17.6, 15.2, 80.5, 56, 96.2,
- 59.9, 26.7, 96.1, 92.3, 42.1, 35.8, 54, 23.2, 55, 76, 35.8,
- 58.4, 88.7, 2.4, 78.1, 95.6, 27.5, 6.6, 78.5, 24.1, 69.8},
- {43.8, 96.5, 0.9, 95.1, 49.1, 71.2, 25.1, 33.6, 75.2, 95, 82.1,
- 19.7, 10.5, 44.9, 50, 93.3, 83.5, 99.5, 64.6, 54, 3.5, 99.7,
- 45.3, 82.1, 22.4, 37.9, 60, 32.2, 12.6, 4.6, 65.5, 96.4}},
- /*sigma_dct=*/{72.5, 2.6, 41.7, 2.2, 39.7, 79.1, 69.6, 19.9,
- 92.3, 71.5, 41.9, 62.1, 30, 49.4, 70.3, 45.3,
- 62.5, 47.2, 46.7, 41.2, 90.8, 46.8, 91.2, 55,
- 8.1, 69.6, 25.4, 84.7, 61.7, 27.6, 3.7, 46.9}},
- {/*control_points=*/{{100, 186},
- {257, 97},
- {170, 49},
- {25, 169},
- {309, 104},
- {232, 237},
- {385, 101},
- {122, 168},
- {26, 300},
- {390, 88}},
- /*color_dct=*/
- {{16.9, 64.8, 4.2, 10.6, 23.5, 17, 79.3, 5.7, 60.4, 16.6, 94.9,
- 63.7, 87.6, 10.5, 3.8, 61.1, 22.9, 81.9, 80.4, 40.5, 45.9, 25.4,
- 39.8, 30, 50.2, 90.4, 27.9, 93.7, 65.1, 48.2, 22.3, 43.9},
- {24.9, 66, 3.5, 90.2, 97.1, 15.8, 35.6, 0.6, 68, 39.6, 24.4,
- 85.9, 57.7, 77.6, 47.5, 67.9, 4.3, 5.4, 91.2, 58.5, 0.1, 52.2,
- 3.5, 47.8, 63.2, 43.5, 85.8, 35.8, 50.2, 35.9, 19.2, 48.2},
- {82.8, 44.9, 76.4, 39.5, 94.1, 14.3, 89.8, 10, 10.5, 74.5, 56.3,
- 65.8, 7.8, 23.3, 52.8, 99.3, 56.8, 46, 76.7, 13.5, 67, 22.4,
- 29.9, 43.3, 70.3, 26, 74.3, 53.9, 62, 19.1, 49.3, 46.7}},
- /*sigma_dct=*/{83.5, 1.7, 25.1, 18.7, 46.5, 75.3, 28, 62.3,
- 50.3, 23.3, 85.6, 96, 45.8, 33.1, 33.4, 52.9,
- 26.3, 58.5, 19.6, 70, 92.6, 22.5, 57, 21.6,
- 76.8, 87.5, 22.9, 66.3, 35.7, 35.6, 56.8, 67.2}},
- };
+ Spline spline1{
+ /*control_points=*/{
+ {109, 54}, {218, 159}, {80, 3}, {110, 274}, {94, 185}, {17, 277}},
+ /*color_dct=*/
+ {Dct32{36.3, 39.7, 23.2, 67.5, 4.4, 71.5, 62.3, 32.3, 92.2, 10.1, 10.8,
+ 9.2, 6.1, 10.5, 79.1, 7, 24.6, 90.8, 5.5, 84, 43.8, 49,
+ 33.5, 78.9, 54.5, 77.9, 62.1, 51.4, 36.4, 14.3, 83.7, 35.4},
+ Dct32{9.4, 53.4, 9.5, 74.9, 72.7, 26.7, 7.9, 0.9, 84.9, 23.2, 26.5,
+ 31.1, 91, 11.7, 74.1, 39.3, 23.7, 82.5, 4.8, 2.7, 61.2, 96.4,
+ 13.7, 66.7, 62.9, 82.4, 5.9, 98.7, 21.5, 7.9, 51.7, 63.1},
+ Dct32{48, 39.3, 6.9, 26.3, 33.3, 6.2, 1.7, 98.9, 59.9, 59.6, 95,
+ 61.3, 82.7, 53, 6.1, 30.4, 34.7, 96.9, 93.4, 17, 38.8, 80.8,
+ 63, 18.6, 43.6, 32.3, 61, 20.2, 24.3, 28.3, 69.1, 62.4}},
+ /*sigma_dct=*/{32.7, 21.5, 44.4, 1.8, 45.8, 90.6, 29.3, 59.2,
+ 23.7, 85.2, 84.8, 27.2, 42.1, 84.1, 50.6, 17.6,
+ 93.7, 4.9, 2.6, 69.8, 94.9, 52, 24.3, 18.8,
+ 12.1, 95.7, 28.5, 81.4, 89.9, 31.4, 74.8, 52}};
+ Spline spline2{
+ /*control_points=*/{{172, 309},
+ {196, 277},
+ {42, 238},
+ {114, 350},
+ {307, 290},
+ {316, 269},
+ {124, 66},
+ {233, 267}},
+ /*color_dct=*/
+ {Dct32{15, 28.9, 22, 6.6, 41.8, 83, 8.6, 56.8, 68.9, 9.7, 5.4,
+ 19.8, 70.8, 90, 52.5, 65.2, 7.8, 23.5, 26.4, 72.2, 64.7, 87.1,
+ 1.3, 67.5, 46, 68.4, 65.4, 35.5, 29.1, 13, 41.6, 23.9},
+ Dct32{47.7, 79.4, 62.7, 29.1, 96.8, 18.5, 17.6, 15.2, 80.5, 56, 96.2,
+ 59.9, 26.7, 96.1, 92.3, 42.1, 35.8, 54, 23.2, 55, 76, 35.8,
+ 58.4, 88.7, 2.4, 78.1, 95.6, 27.5, 6.6, 78.5, 24.1, 69.8},
+ Dct32{43.8, 96.5, 0.9, 95.1, 49.1, 71.2, 25.1, 33.6, 75.2, 95, 82.1,
+ 19.7, 10.5, 44.9, 50, 93.3, 83.5, 99.5, 64.6, 54, 3.5, 99.7,
+ 45.3, 82.1, 22.4, 37.9, 60, 32.2, 12.6, 4.6, 65.5, 96.4}},
+ /*sigma_dct=*/{72.5, 2.6, 41.7, 2.2, 39.7, 79.1, 69.6, 19.9,
+ 92.3, 71.5, 41.9, 62.1, 30, 49.4, 70.3, 45.3,
+ 62.5, 47.2, 46.7, 41.2, 90.8, 46.8, 91.2, 55,
+ 8.1, 69.6, 25.4, 84.7, 61.7, 27.6, 3.7, 46.9}};
+ Spline spline3{
+ /*control_points=*/{{100, 186},
+ {257, 97},
+ {170, 49},
+ {25, 169},
+ {309, 104},
+ {232, 237},
+ {385, 101},
+ {122, 168},
+ {26, 300},
+ {390, 88}},
+ /*color_dct=*/
+ {Dct32{16.9, 64.8, 4.2, 10.6, 23.5, 17, 79.3, 5.7, 60.4, 16.6, 94.9,
+ 63.7, 87.6, 10.5, 3.8, 61.1, 22.9, 81.9, 80.4, 40.5, 45.9, 25.4,
+ 39.8, 30, 50.2, 90.4, 27.9, 93.7, 65.1, 48.2, 22.3, 43.9},
+ Dct32{24.9, 66, 3.5, 90.2, 97.1, 15.8, 35.6, 0.6, 68, 39.6, 24.4,
+ 85.9, 57.7, 77.6, 47.5, 67.9, 4.3, 5.4, 91.2, 58.5, 0.1, 52.2,
+ 3.5, 47.8, 63.2, 43.5, 85.8, 35.8, 50.2, 35.9, 19.2, 48.2},
+ Dct32{82.8, 44.9, 76.4, 39.5, 94.1, 14.3, 89.8, 10, 10.5, 74.5, 56.3,
+ 65.8, 7.8, 23.3, 52.8, 99.3, 56.8, 46, 76.7, 13.5, 67, 22.4,
+ 29.9, 43.3, 70.3, 26, 74.3, 53.9, 62, 19.1, 49.3, 46.7}},
+ /*sigma_dct=*/{83.5, 1.7, 25.1, 18.7, 46.5, 75.3, 28, 62.3,
+ 50.3, 23.3, 85.6, 96, 45.8, 33.1, 33.4, 52.9,
+ 26.3, 58.5, 19.6, 70, 92.6, 22.5, 57, 21.6,
+ 76.8, 87.5, 22.9, 66.3, 35.7, 35.6, 56.8, 67.2}};
+ std::vector<Spline> spline_data{spline1, spline2, spline3};
std::vector<QuantizedSpline> quantized_splines;
std::vector<Spline::Point> starting_points;
@@ -206,8 +149,20 @@ TEST(SplinesTest, Serialization) {
Splines splines(kQuantizationAdjustment, std::move(quantized_splines),
std::move(starting_points));
const std::vector<Spline> quantized_spline_data = DequantizeSplines(splines);
- EXPECT_THAT(quantized_spline_data,
- Pointwise(ControlPointsMatch(), spline_data));
+ EXPECT_EQ(quantized_spline_data.size(), spline_data.size());
+ for (size_t i = 0; i < quantized_spline_data.size(); ++i) {
+ const Spline& actual = quantized_spline_data[i];
+ const Spline& expected = spline_data[i];
+ const auto& actual_points = actual.control_points;
+ const auto& expected_points = expected.control_points;
+ EXPECT_EQ(actual_points.size(), expected_points.size());
+ for (size_t j = 0; j < actual_points.size(); ++j) {
+ EXPECT_NEAR(actual_points[j].x, expected_points[j].x, kTolerance)
+ << "spline " << i << " point " << j;
+ EXPECT_NEAR(actual_points[j].y, expected_points[j].y, kTolerance)
+ << "spline " << i << " point " << j;
+ }
+ }
BitWriter writer;
EncodeSplines(splines, &writer, kLayerSplines, HistogramParams(), nullptr);
@@ -225,8 +180,28 @@ TEST(SplinesTest, Serialization) {
const std::vector<Spline> decoded_spline_data =
DequantizeSplines(decoded_splines);
- EXPECT_THAT(decoded_spline_data,
- Pointwise(SplinesMatch(), quantized_spline_data));
+
+ EXPECT_EQ(decoded_spline_data.size(), quantized_spline_data.size());
+ for (size_t i = 0; i < decoded_spline_data.size(); ++i) {
+ const Spline& actual = decoded_spline_data[i];
+ const Spline& expected = quantized_spline_data[i];
+ const auto& actual_points = actual.control_points;
+ const auto& expected_points = expected.control_points;
+ EXPECT_EQ(actual_points.size(), expected_points.size());
+ for (size_t j = 0; j < actual_points.size(); ++j) {
+ EXPECT_NEAR(actual_points[j].x, expected_points[j].x, kTolerance)
+ << "spline " << i << " point " << j;
+ EXPECT_NEAR(actual_points[j].y, expected_points[j].y, kTolerance)
+ << "spline " << i << " point " << j;
+ }
+
+ const auto& actual_color_dct = actual.color_dct;
+ const auto& expected_color_dct = expected.color_dct;
+ for (size_t j = 0; j < actual_color_dct.size(); ++j) {
+ EXPECT_ARRAY_NEAR(actual_color_dct[j], expected_color_dct[j], kTolerance);
+ }
+ EXPECT_ARRAY_NEAR(actual.sigma_dct, expected.sigma_dct, kTolerance);
+ }
}
#ifdef JXL_CRASH_ON_ERROR
@@ -240,10 +215,10 @@ TEST(SplinesTest, TooManySplinesTest) {
std::vector<QuantizedSpline> quantized_splines;
std::vector<Spline::Point> starting_points;
for (size_t i = 0; i < kNumSplines; i++) {
- Spline spline = {
+ Spline spline{
/*control_points=*/{{1.f + i, 2}, {10.f + i, 25}, {30.f + i, 300}},
/*color_dct=*/
- {{1.f, 0.2f, 0.1f}, {35.7f, 10.3f}, {35.7f, 7.8f}},
+ {Dct32{1.f, 0.2f, 0.1f}, Dct32{35.7f, 10.3f}, Dct32{35.7f, 7.8f}},
/*sigma_dct=*/{10.f, 0.f, 0.f, 2.f}};
quantized_splines.emplace_back(spline, kQuantizationAdjustment, kYToX,
kYToB);
@@ -271,10 +246,11 @@ TEST(SplinesTest, DuplicatePoints) {
std::vector<Spline::Point> control_points{
{9, 54}, {118, 159}, {97, 3}, // Repeated.
{97, 3}, {10, 40}, {150, 25}, {120, 300}};
- Spline spline{control_points,
- /*color_dct=*/
- {{1.f, 0.2f, 0.1f}, {35.7f, 10.3f}, {35.7f, 7.8f}},
- /*sigma_dct=*/{10.f, 0.f, 0.f, 2.f}};
+ Spline spline{
+ control_points,
+ /*color_dct=*/
+ {Dct32{1.f, 0.2f, 0.1f}, Dct32{35.7f, 10.3f}, Dct32{35.7f, 7.8f}},
+ /*sigma_dct=*/{10.f, 0.f, 0.f, 2.f}};
std::vector<Spline> spline_data{spline};
std::vector<QuantizedSpline> quantized_splines;
std::vector<Spline::Point> starting_points;
@@ -286,7 +262,7 @@ TEST(SplinesTest, DuplicatePoints) {
Splines splines(kQuantizationAdjustment, std::move(quantized_splines),
std::move(starting_points));
- Image3F image(320, 320);
+ JXL_ASSIGN_OR_DIE(Image3F image, Image3F::Create(320, 320));
ZeroFillImage(&image);
EXPECT_FALSE(
splines.InitializeDrawCache(image.xsize(), image.ysize(), *cmap));
@@ -304,10 +280,10 @@ TEST(SplinesTest, Drawing) {
const Spline spline{
control_points,
/*color_dct=*/
- {{0.4989345073699951171875000f, 0.4997999966144561767578125f},
- {0.4772970676422119140625000f, 0.f, 0.5250000357627868652343750f},
- {-0.0176776945590972900390625f, 0.4900000095367431640625000f,
- 0.5250000357627868652343750f}},
+ {Dct32{0.4989345073699951171875000f, 0.4997999966144561767578125f},
+ Dct32{0.4772970676422119140625000f, 0.f, 0.5250000357627868652343750f},
+ Dct32{-0.0176776945590972900390625f, 0.4900000095367431640625000f,
+ 0.5250000357627868652343750f}},
/*sigma_dct=*/
{0.9427147507667541503906250f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f,
0.6665999889373779296875000f}};
@@ -322,13 +298,13 @@ TEST(SplinesTest, Drawing) {
Splines splines(kQuantizationAdjustment, std::move(quantized_splines),
std::move(starting_points));
- Image3F image(320, 320);
+ JXL_ASSIGN_OR_DIE(Image3F image, Image3F::Create(320, 320));
ZeroFillImage(&image);
ASSERT_TRUE(splines.InitializeDrawCache(image.xsize(), image.ysize(), *cmap));
splines.AddTo(&image, Rect(image), Rect(image));
CodecInOut io_actual;
- Image3F image2(320, 320);
+ JXL_ASSIGN_OR_DIE(Image3F image2, Image3F::Create(320, 320));
CopyImageTo(image, &image2);
io_actual.SetFromImage(std::move(image2), ColorEncoding::SRGB());
ASSERT_TRUE(io_actual.frames[0].TransformTo(io_expected.Main().c_current(),
generated by cgit v1.2.3 (git 2.39.1) at 2024-11-12 18:27:03 +0000