// Copyright (c) the JPEG XL Project Authors. All rights reserved. // // Use of this source code is governed by a BSD-style // license that can be found in the LICENSE file. #include "lib/jxl/splines.h" #include "lib/extras/codec.h" #include "lib/jxl/base/printf_macros.h" #include "lib/jxl/enc_aux_out.h" #include "lib/jxl/enc_butteraugli_comparator.h" #include "lib/jxl/enc_color_management.h" #include "lib/jxl/enc_splines.h" #include "lib/jxl/image_test_utils.h" #include "lib/jxl/test_utils.h" #include "lib/jxl/testing.h" namespace jxl { std::ostream& operator<<(std::ostream& os, const Spline::Point& p) { return os << "(" << p.x << ", " << p.y << ")"; } std::ostream& operator<<(std::ostream& os, const Spline& spline) { return os << "(spline with " << spline.control_points.size() << " control points)"; } namespace { using ::testing::AllOf; using ::testing::Field; using ::testing::FloatNear; using ::testing::Pointwise; constexpr int kQuantizationAdjustment = 0; const ColorCorrelationMap* const cmap = new ColorCorrelationMap; const float kYToX = cmap->YtoXRatio(0); const float kYToB = cmap->YtoBRatio(0); constexpr float kTolerance = 0.003125; std::vector DequantizeSplines(const Splines& splines) { const auto& quantized_splines = splines.QuantizedSplines(); const auto& starting_points = splines.StartingPoints(); JXL_CHECK(quantized_splines.size() == starting_points.size()); std::vector dequantized; uint64_t total = 0; for (size_t i = 0; i < quantized_splines.size(); ++i) { dequantized.emplace_back(); JXL_CHECK(quantized_splines[i].Dequantize( starting_points[i], kQuantizationAdjustment, kYToX, kYToB, 2u << 30u, &total, dequantized.back())); } 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_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}}, }; std::vector quantized_splines; std::vector starting_points; for (const Spline& spline : spline_data) { quantized_splines.emplace_back(spline, kQuantizationAdjustment, kYToX, kYToB); starting_points.push_back(spline.control_points.front()); } Splines splines(kQuantizationAdjustment, std::move(quantized_splines), std::move(starting_points)); const std::vector quantized_spline_data = DequantizeSplines(splines); EXPECT_THAT(quantized_spline_data, Pointwise(ControlPointsMatch(), spline_data)); BitWriter writer; EncodeSplines(splines, &writer, kLayerSplines, HistogramParams(), nullptr); writer.ZeroPadToByte(); const size_t bits_written = writer.BitsWritten(); printf("Wrote %" PRIuS " bits of splines.\n", bits_written); BitReader reader(writer.GetSpan()); Splines decoded_splines; ASSERT_TRUE(decoded_splines.Decode(&reader, /*num_pixels=*/1000)); ASSERT_TRUE(reader.JumpToByteBoundary()); EXPECT_EQ(reader.TotalBitsConsumed(), bits_written); ASSERT_TRUE(reader.Close()); const std::vector decoded_spline_data = DequantizeSplines(decoded_splines); EXPECT_THAT(decoded_spline_data, Pointwise(SplinesMatch(), quantized_spline_data)); } #ifdef JXL_CRASH_ON_ERROR TEST(SplinesTest, DISABLED_TooManySplinesTest) { #else TEST(SplinesTest, TooManySplinesTest) { #endif // This is more than the limit for 1000 pixels. const size_t kNumSplines = 300; std::vector quantized_splines; std::vector starting_points; for (size_t i = 0; i < kNumSplines; i++) { 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}}, /*sigma_dct=*/{10.f, 0.f, 0.f, 2.f}}; quantized_splines.emplace_back(spline, kQuantizationAdjustment, kYToX, kYToB); starting_points.push_back(spline.control_points.front()); } Splines splines(kQuantizationAdjustment, std::move(quantized_splines), std::move(starting_points)); BitWriter writer; EncodeSplines(splines, &writer, kLayerSplines, HistogramParams(SpeedTier::kFalcon, 1), nullptr); writer.ZeroPadToByte(); // Re-read splines. BitReader reader(writer.GetSpan()); Splines decoded_splines; EXPECT_FALSE(decoded_splines.Decode(&reader, /*num_pixels=*/1000)); EXPECT_TRUE(reader.Close()); } #ifdef JXL_CRASH_ON_ERROR TEST(SplinesTest, DISABLED_DuplicatePoints) { #else TEST(SplinesTest, DuplicatePoints) { #endif std::vector 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}}; std::vector spline_data{spline}; std::vector quantized_splines; std::vector starting_points; for (const Spline& spline : spline_data) { quantized_splines.emplace_back(spline, kQuantizationAdjustment, kYToX, kYToB); starting_points.push_back(spline.control_points.front()); } Splines splines(kQuantizationAdjustment, std::move(quantized_splines), std::move(starting_points)); Image3F image(320, 320); ZeroFillImage(&image); EXPECT_FALSE( splines.InitializeDrawCache(image.xsize(), image.ysize(), *cmap)); } TEST(SplinesTest, Drawing) { CodecInOut io_expected; const PaddedBytes orig = jxl::test::ReadTestData("jxl/splines.pfm"); ASSERT_TRUE(SetFromBytes(Span(orig), &io_expected, /*pool=*/nullptr)); std::vector control_points{{9, 54}, {118, 159}, {97, 3}, {10, 40}, {150, 25}, {120, 300}}; // Use values that survive quant/decorellation roundtrip. const Spline spline{ control_points, /*color_dct=*/ {{0.4989345073699951171875000f, 0.4997999966144561767578125f}, {0.4772970676422119140625000f, 0.f, 0.5250000357627868652343750f}, {-0.0176776945590972900390625f, 0.4900000095367431640625000f, 0.5250000357627868652343750f}}, /*sigma_dct=*/ {0.9427147507667541503906250f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.f, 0.6665999889373779296875000f}}; std::vector spline_data = {spline}; std::vector quantized_splines; std::vector starting_points; for (const Spline& spline : spline_data) { quantized_splines.emplace_back(spline, kQuantizationAdjustment, kYToX, kYToB); starting_points.push_back(spline.control_points.front()); } Splines splines(kQuantizationAdjustment, std::move(quantized_splines), std::move(starting_points)); Image3F image(320, 320); ZeroFillImage(&image); ASSERT_TRUE(splines.InitializeDrawCache(image.xsize(), image.ysize(), *cmap)); splines.AddTo(&image, Rect(image), Rect(image)); CodecInOut io_actual; io_actual.SetFromImage(CopyImage(image), ColorEncoding::SRGB()); ASSERT_TRUE(io_actual.frames[0].TransformTo(io_expected.Main().c_current(), GetJxlCms())); JXL_ASSERT_OK(VerifyRelativeError( *io_expected.Main().color(), *io_actual.Main().color(), 1e-2f, 1e-1f, _)); } TEST(SplinesTest, ClearedEveryFrame) { CodecInOut io_expected; const PaddedBytes bytes_expected = jxl::test::ReadTestData("jxl/spline_on_first_frame.png"); ASSERT_TRUE(SetFromBytes(Span(bytes_expected), &io_expected, /*pool=*/nullptr)); CodecInOut io_actual; const PaddedBytes bytes_actual = jxl::test::ReadTestData("jxl/spline_on_first_frame.jxl"); ASSERT_TRUE( test::DecodeFile({}, Span(bytes_actual), &io_actual)); ASSERT_TRUE( io_actual.frames[0].TransformTo(ColorEncoding::SRGB(), GetJxlCms())); for (size_t c = 0; c < 3; ++c) { for (size_t y = 0; y < io_actual.ysize(); ++y) { float* const JXL_RESTRICT row = io_actual.Main().color()->PlaneRow(c, y); for (size_t x = 0; x < io_actual.xsize(); ++x) { row[x] = Clamp1(row[x], 0.f, 1.f); } } } JXL_ASSERT_OK(VerifyRelativeError( *io_expected.Main().color(), *io_actual.Main().color(), 1e-2f, 1e-1f, _)); } } // namespace jxl