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Diffstat (limited to 'third_party/jpeg-xl/lib/jxl/gradient_test.cc')
| -rw-r--r-- | third_party/jpeg-xl/lib/jxl/gradient_test.cc | 207 |
1 files changed, 207 insertions, 0 deletions
diff --git a/third_party/jpeg-xl/lib/jxl/gradient_test.cc b/third_party/jpeg-xl/lib/jxl/gradient_test.cc new file mode 100644 index 0000000000..282fe89f0a --- /dev/null +++ b/third_party/jpeg-xl/lib/jxl/gradient_test.cc @@ -0,0 +1,207 @@ +// 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 <math.h> +#include <stddef.h> +#include <stdint.h> + +#include <algorithm> +#include <array> +#include <utility> + +#include "lib/jxl/base/compiler_specific.h" +#include "lib/jxl/base/data_parallel.h" +#include "lib/jxl/base/override.h" +#include "lib/jxl/base/padded_bytes.h" +#include "lib/jxl/codec_in_out.h" +#include "lib/jxl/color_encoding_internal.h" +#include "lib/jxl/color_management.h" +#include "lib/jxl/common.h" +#include "lib/jxl/enc_cache.h" +#include "lib/jxl/enc_color_management.h" +#include "lib/jxl/enc_file.h" +#include "lib/jxl/enc_params.h" +#include "lib/jxl/image.h" +#include "lib/jxl/image_bundle.h" +#include "lib/jxl/image_ops.h" +#include "lib/jxl/test_utils.h" +#include "lib/jxl/testing.h" + +namespace jxl { + +struct AuxOut; + +namespace { + +// Returns distance of point p to line p0..p1, the result is signed and is not +// normalized. +double PointLineDist(double x0, double y0, double x1, double y1, double x, + double y) { + return (y1 - y0) * x - (x1 - x0) * y + x1 * y0 - y1 * x0; +} + +// Generates a test image with a gradient from one color to another. +// Angle in degrees, colors can be given in hex as 0xRRGGBB. The angle is the +// angle in which the change direction happens. +Image3F GenerateTestGradient(uint32_t color0, uint32_t color1, double angle, + size_t xsize, size_t ysize) { + Image3F image(xsize, ysize); + + double x0 = xsize / 2; + double y0 = ysize / 2; + double x1 = x0 + std::sin(angle / 360.0 * 2.0 * kPi); + double y1 = y0 + std::cos(angle / 360.0 * 2.0 * kPi); + + double maxdist = + std::max<double>(fabs(PointLineDist(x0, y0, x1, y1, 0, 0)), + fabs(PointLineDist(x0, y0, x1, y1, xsize, 0))); + + for (size_t c = 0; c < 3; ++c) { + float c0 = ((color0 >> (8 * (2 - c))) & 255); + float c1 = ((color1 >> (8 * (2 - c))) & 255); + for (size_t y = 0; y < ysize; ++y) { + float* row = image.PlaneRow(c, y); + for (size_t x = 0; x < xsize; ++x) { + double dist = PointLineDist(x0, y0, x1, y1, x, y); + double v = ((dist / maxdist) + 1.0) / 2.0; + float color = c0 * (1.0 - v) + c1 * v; + row[x] = color; + } + } + } + + return image; +} + +// Computes the max of the horizontal and vertical second derivative for each +// pixel, where second derivative means absolute value of difference of left +// delta and right delta (top/bottom for vertical direction). +// The radius over which the derivative is computed is only 1 pixel and it only +// checks two angles (hor and ver), but this approximation works well enough. +static ImageF Gradient2(const ImageF& image) { + size_t xsize = image.xsize(); + size_t ysize = image.ysize(); + ImageF image2(image.xsize(), image.ysize()); + for (size_t y = 1; y + 1 < ysize; y++) { + const auto* JXL_RESTRICT row0 = image.Row(y - 1); + const auto* JXL_RESTRICT row1 = image.Row(y); + const auto* JXL_RESTRICT row2 = image.Row(y + 1); + auto* row_out = image2.Row(y); + for (size_t x = 1; x + 1 < xsize; x++) { + float ddx = (row1[x] - row1[x - 1]) - (row1[x + 1] - row1[x]); + float ddy = (row1[x] - row0[x]) - (row2[x] - row1[x]); + row_out[x] = std::max(fabsf(ddx), fabsf(ddy)); + } + } + // Copy to the borders + if (ysize > 2) { + auto* JXL_RESTRICT row0 = image2.Row(0); + const auto* JXL_RESTRICT row1 = image2.Row(1); + const auto* JXL_RESTRICT row2 = image2.Row(ysize - 2); + auto* JXL_RESTRICT row3 = image2.Row(ysize - 1); + for (size_t x = 1; x + 1 < xsize; x++) { + row0[x] = row1[x]; + row3[x] = row2[x]; + } + } else { + const auto* row0_in = image.Row(0); + const auto* row1_in = image.Row(ysize - 1); + auto* row0_out = image2.Row(0); + auto* row1_out = image2.Row(ysize - 1); + for (size_t x = 1; x + 1 < xsize; x++) { + // Image too narrow, take first derivative instead + row0_out[x] = row1_out[x] = fabsf(row0_in[x] - row1_in[x]); + } + } + if (xsize > 2) { + for (size_t y = 0; y < ysize; y++) { + auto* row = image2.Row(y); + row[0] = row[1]; + row[xsize - 1] = row[xsize - 2]; + } + } else { + for (size_t y = 0; y < ysize; y++) { + const auto* JXL_RESTRICT row_in = image.Row(y); + auto* row_out = image2.Row(y); + // Image too narrow, take first derivative instead + row_out[0] = row_out[xsize - 1] = fabsf(row_in[0] - row_in[xsize - 1]); + } + } + return image2; +} + +static Image3F Gradient2(const Image3F& image) { + return Image3F(Gradient2(image.Plane(0)), Gradient2(image.Plane(1)), + Gradient2(image.Plane(2))); +} + +/* +Tests if roundtrip with jxl on a gradient image doesn't cause banding. +Only tests if use_gradient is true. Set to false for debugging to see the +distance values. +Angle in degrees, colors can be given in hex as 0xRRGGBB. +*/ +void TestGradient(ThreadPool* pool, uint32_t color0, uint32_t color1, + size_t xsize, size_t ysize, float angle, bool fast_mode, + float butteraugli_distance, bool use_gradient = true) { + CompressParams cparams; + cparams.butteraugli_distance = butteraugli_distance; + if (fast_mode) { + cparams.speed_tier = SpeedTier::kSquirrel; + } + Image3F gradient = GenerateTestGradient(color0, color1, angle, xsize, ysize); + + CodecInOut io; + io.metadata.m.SetUintSamples(8); + io.metadata.m.color_encoding = ColorEncoding::SRGB(); + io.SetFromImage(std::move(gradient), io.metadata.m.color_encoding); + + CodecInOut io2; + + PaddedBytes compressed; + AuxOut* aux_out = nullptr; + PassesEncoderState enc_state; + EXPECT_TRUE(EncodeFile(cparams, &io, &enc_state, &compressed, GetJxlCms(), + aux_out, pool)); + EXPECT_TRUE( + test::DecodeFile({}, Span<const uint8_t>(compressed), &io2, pool)); + EXPECT_TRUE( + io2.Main().TransformTo(io2.metadata.m.color_encoding, GetJxlCms(), pool)); + + if (use_gradient) { + // Test that the gradient map worked. For that, we take a second derivative + // of the image with Gradient2 to measure how linear the change is in x and + // y direction. For a well handled gradient, we expect max values around + // 0.1, while if there is noticeable banding, which means the gradient map + // failed, the values are around 0.5-1.0 (regardless of + // butteraugli_distance). + Image3F gradient2 = Gradient2(*io2.Main().color()); + + std::array<float, 3> image_max; + Image3Max(gradient2, &image_max); + + // TODO(jyrki): These values used to work with 0.2, 0.2, 0.2. + EXPECT_LE(image_max[0], 3.15); + EXPECT_LE(image_max[1], 1.72); + EXPECT_LE(image_max[2], 5.05); + } +} + +static constexpr bool fast_mode = true; + +TEST(GradientTest, SteepGradient) { + test::ThreadPoolForTests pool(8); + // Relatively steep gradients, colors from the sky of stp.png + TestGradient(&pool, 0xd99d58, 0x889ab1, 512, 512, 90, fast_mode, 3.0); +} + +TEST(GradientTest, SubtleGradient) { + test::ThreadPoolForTests pool(8); + // Very subtle gradient + TestGradient(&pool, 0xb89b7b, 0xa89b8d, 512, 512, 90, fast_mode, 4.0); +} + +} // namespace +} // namespace jxl |