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gainmapmath: directly sample gain maps at scale 1 #480

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17 changes: 17 additions & 0 deletions lib/src/gainmapmath.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -930,6 +930,13 @@ float sampleMap(uhdr_raw_image_t* map, float map_scale_factor, size_t x, size_t

float sampleMap(uhdr_raw_image_t* map, size_t map_scale_factor, size_t x, size_t y,
ShepardsIDW& weightTables) {
if (map_scale_factor == 1) {
const size_t map_x = std::min(x, static_cast<size_t>(map->w - 1));
const size_t map_y = std::min(y, static_cast<size_t>(map->h - 1));
uint8_t* data = reinterpret_cast<uint8_t*>(map->planes[UHDR_PLANE_Y]);
return mapUintToFloat(data[map_x + map_y * map->stride[UHDR_PLANE_Y]]);
}

// TODO: If map_scale_factor is guaranteed to be an integer power of 2, then optimize the
// following by computing log2(map_scale_factor) once and then using >> log2(map_scale_factor)
size_t x_lower = x / map_scale_factor;
Expand Down Expand Up @@ -1036,6 +1043,16 @@ Color sampleMap3Channel(uhdr_raw_image_t* map, float map_scale_factor, size_t x,

Color sampleMap3Channel(uhdr_raw_image_t* map, size_t map_scale_factor, size_t x, size_t y,
ShepardsIDW& weightTables, bool has_alpha) {
if (map_scale_factor == 1) {
const size_t map_x = std::min(x, static_cast<size_t>(map->w - 1));
const size_t map_y = std::min(y, static_cast<size_t>(map->h - 1));
const size_t factor = has_alpha ? 4 : 3;
uint8_t* data = reinterpret_cast<uint8_t*>(map->planes[UHDR_PLANE_PACKED]);
const size_t offset = (map_x + map_y * map->stride[UHDR_PLANE_PACKED]) * factor;
return {{{mapUintToFloat(data[offset]), mapUintToFloat(data[offset + 1]),
mapUintToFloat(data[offset + 2])}}};
}

// TODO: If map_scale_factor is guaranteed to be an integer power of 2, then optimize the
// following by computing log2(map_scale_factor) once and then using >> log2(map_scale_factor)
size_t x_lower = x / map_scale_factor;
Expand Down
99 changes: 99 additions & 0 deletions tests/gainmapmath_test.cpp
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Expand Up @@ -1817,6 +1817,105 @@ TEST_F(GainMapMathTest, SampleMap) {
}
}

TEST_F(GainMapMathTest, SampleMapScaleOneGrayUsesPaddedStrideAndClamps) {
constexpr size_t kWidth = 3;
constexpr size_t kHeight = 2;
constexpr size_t kStride = 5;
constexpr uint8_t kPadding = 0xa5;
const uint8_t values[] = {0, 1, 127, 128, 254, 255};
std::vector<uint8_t> storage(kStride * kHeight, kPadding);
for (size_t y = 0; y < kHeight; ++y) {
for (size_t x = 0; x < kWidth; ++x) {
storage[x + y * kStride] = values[x + y * kWidth];
}
}

uhdr_raw_image_t image{};
image.fmt = UHDR_IMG_FMT_8bppYCbCr400;
image.w = kWidth;
image.h = kHeight;
image.planes[UHDR_PLANE_Y] = storage.data();
image.stride[UHDR_PLANE_Y] = kStride;
ShepardsIDW weights(1);

const size_t coordinates[][4] = {
{0, 0, 0, 0}, {2, 0, 2, 0}, {0, 1, 0, 1},
{2, 1, 2, 1}, {3, 0, 2, 0}, {0, 2, 0, 1}, {3, 2, 2, 1},
};
for (const auto& coordinate : coordinates) {
const size_t x = coordinate[0];
const size_t y = coordinate[1];
const size_t expected_x = coordinate[2];
const size_t expected_y = coordinate[3];
const float expected = static_cast<float>(storage[expected_x + expected_y * kStride]) / 255.0f;
EXPECT_EQ(sampleMap(&image, size_t{1}, x, y, weights), expected);
}
}

TEST_F(GainMapMathTest, SampleMapScaleOneGrayPreservesEveryByteValue) {
constexpr size_t kWidth = 256;
constexpr size_t kStride = 260;
std::vector<uint8_t> storage(kStride, 0xa5);
for (size_t x = 0; x < kWidth; ++x) storage[x] = static_cast<uint8_t>(x);

uhdr_raw_image_t image{};
image.fmt = UHDR_IMG_FMT_8bppYCbCr400;
image.w = kWidth;
image.h = 1;
image.planes[UHDR_PLANE_Y] = storage.data();
image.stride[UHDR_PLANE_Y] = kStride;
ShepardsIDW weights(1);
for (size_t x = 0; x < kWidth; ++x) {
EXPECT_EQ(sampleMap(&image, size_t{1}, x, 0, weights),
static_cast<float>(x) / 255.0f);
}
}

TEST_F(GainMapMathTest, SampleMap3ChannelScaleOneUsesPaddedRgbAndRgbaStrides) {
constexpr size_t kWidth = 3;
constexpr size_t kHeight = 2;
constexpr size_t kStride = 5;
constexpr uint8_t kPadding = 0xa5;
const uint8_t values[] = {0, 1, 127, 128, 254, 255};
const bool alpha_modes[] = {false, true};
const size_t coordinates[][4] = {
{0, 0, 0, 0}, {2, 1, 2, 1}, {3, 0, 2, 0}, {0, 2, 0, 1}, {3, 2, 2, 1},
};

for (const bool has_alpha : alpha_modes) {
const size_t bytes_per_pixel = has_alpha ? 4 : 3;
std::vector<uint8_t> storage(kStride * kHeight * bytes_per_pixel, kPadding);
for (size_t y = 0; y < kHeight; ++y) {
for (size_t x = 0; x < kWidth; ++x) {
const size_t offset = (x + y * kStride) * bytes_per_pixel;
for (size_t channel = 0; channel < bytes_per_pixel; ++channel) {
storage[offset + channel] = channel == 3
? 0xe7
: values[(x + y * kWidth + channel) % 6];
}
}
}

uhdr_raw_image_t image{};
image.fmt = has_alpha ? UHDR_IMG_FMT_32bppRGBA8888 : UHDR_IMG_FMT_24bppRGB888;
image.w = kWidth;
image.h = kHeight;
image.planes[UHDR_PLANE_PACKED] = storage.data();
image.stride[UHDR_PLANE_PACKED] = kStride;
ShepardsIDW weights(1);

for (const auto& coordinate : coordinates) {
const size_t expected_offset =
(coordinate[2] + coordinate[3] * kStride) * bytes_per_pixel;
const Color actual =
sampleMap3Channel(&image, size_t{1}, coordinate[0], coordinate[1], weights, has_alpha);
EXPECT_EQ(actual.r, static_cast<float>(storage[expected_offset]) / 255.0f);
EXPECT_EQ(actual.g, static_cast<float>(storage[expected_offset + 1]) / 255.0f);
EXPECT_EQ(actual.b, static_cast<float>(storage[expected_offset + 2]) / 255.0f);
}
}
}

TEST_F(GainMapMathTest, ColorToRgba1010102) {
EXPECT_EQ(colorToRgba1010102(RgbBlack()), 0x3 << 30);
EXPECT_EQ(colorToRgba1010102(RgbWhite()), 0xFFFFFFFF);
Expand Down
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