blob: b17e74ad6854c2fbb5b74314dda6b799ddd56d97 [file] [log] [blame]
/*
* Copyright (c) 2018, Alliance for Open Media. All rights reserved
*
* This source code is subject to the terms of the BSD 2 Clause License and
* the Alliance for Open Media Patent License 1.0. If the BSD 2 Clause License
* was not distributed with this source code in the LICENSE file, you can
* obtain it at www.aomedia.org/license/software. If the Alliance for Open
* Media Patent License 1.0 was not distributed with this source code in the
* PATENTS file, you can obtain it at www.aomedia.org/license/patent.
*/
#include "aom_mem/aom_mem.h"
#include "av1/encoder/rdopt.h"
#include "third_party/googletest/src/googletest/include/gtest/gtest.h"
namespace {
class EdgeDetectBrightnessTest :
// Parameters are (brightness, width, height).
public ::testing::TestWithParam<::std::tuple<int, int, int>> {};
/** Get the (x, y) value from the input; if i or j is outside of the width
* or height, the nearest pixel value is returned.
*/
static uint8_t get_xy(const uint8_t *data, int w, int h, int i, int j) {
return data[AOMMAX(AOMMIN(i, w - 1), 0) + w * AOMMAX(AOMMIN(j, h - 1), 0)];
}
/** Given the image data, creates a new image with padded values, so an
* 8-tap filter can be convolved. The padded value is the same as the closest
* value in the image. Returns a pointer to the start of the image in the
* padded data. Must be freed with free_pad_8tap.
*/
uint8_t *pad_8tap_convolve(const uint8_t *data, int w, int h) {
// SIMD optimizations require the width to be a multiple of 8 and the height
// to be multiples of 4.
assert(w % 8 == 0);
assert(h % 4 == 0);
// For an 8-tap filter, we need to pad with 3 lines on top and on the left,
// and 4 lines on the right and bottom, for 7 extra lines.
const int pad_w = w + 7;
const int pad_h = h + 7;
uint8_t *dst = (uint8_t *)aom_memalign(32, pad_w * pad_h);
// Fill in the data from the original.
for (int j = 0; j < pad_h; ++j) {
for (int i = 0; i < pad_w; ++i) {
dst[i + j * pad_w] = get_xy(data, w, h, i - 3, j - 3);
}
}
return dst + (w + 7) * 3 + 3;
}
static void free_pad_8tap(uint8_t *padded, int width) {
aom_free(padded - (width + 7) * 3 - 3);
}
static int stride_8tap(int width) { return width + 7; }
TEST_P(EdgeDetectBrightnessTest, BlurUniformBrightness) {
// For varying levels of brightness, the algorithm should
// produce the same output.
int brightness, width, height;
std::tie(brightness, width, height) = GetParam();
uint8_t *orig = (uint8_t *)malloc(width * height);
for (int i = 0; i < width * height; ++i) {
orig[i] = brightness;
}
uint8_t *padded = pad_8tap_convolve(orig, width, height);
free(orig);
uint8_t *output = (uint8_t *)aom_memalign(32, width * height);
gaussian_blur(padded, stride_8tap(width), width, height, output);
for (int i = 0; i < width * height; ++i) {
ASSERT_EQ(brightness, output[i]);
}
free_pad_8tap(padded, width);
aom_free(output);
}
// No edges on a uniformly bright image.
TEST_P(EdgeDetectBrightnessTest, DetectUniformBrightness) {
int brightness, width, height;
std::tie(brightness, width, height) = GetParam();
uint8_t *orig = (uint8_t *)malloc(width * height);
for (int i = 0; i < width * height; ++i) {
orig[i] = brightness;
}
uint8_t *padded = pad_8tap_convolve(orig, width, height);
free(orig);
ASSERT_EQ(0, av1_edge_exists(padded, stride_8tap(width), width, height));
free_pad_8tap(padded, width);
}
INSTANTIATE_TEST_CASE_P(ImageBrightnessTests, EdgeDetectBrightnessTest,
::testing::Combine(
// Brightness
::testing::Values(0, 1, 2, 127, 128, 129, 254, 255),
// Width
::testing::Values(8, 16, 32),
// Height
::testing::Values(4, 8, 12, 32)));
class EdgeDetectImageTest :
// Parameters are (width, height).
public ::testing::TestWithParam<::std::tuple<int, int>> {};
// Generate images with black on one side and white on the other.
TEST_P(EdgeDetectImageTest, BlackWhite) {
int width, height;
std::tie(width, height) = GetParam();
uint8_t *orig = (uint8_t *)malloc(width * height);
for (int j = 0; j < height; ++j) {
for (int i = 0; i < width; ++i) {
if (i < width / 2) {
orig[i + j * width] = 0;
} else {
orig[i + j * width] = 255;
}
}
}
uint8_t *padded = pad_8tap_convolve(orig, width, height);
free(orig);
ASSERT_LE(556, av1_edge_exists(padded, stride_8tap(width), width, height));
free_pad_8tap(padded, width);
}
TEST(EdgeDetectImageTest, HardcodedBlurTest) {
// Randomly generated 8x4.
const uint8_t luma[32] = { 241, 147, 7, 90, 184, 103, 28, 186,
2, 248, 49, 242, 114, 146, 127, 22,
121, 228, 167, 108, 158, 174, 41, 168,
214, 99, 184, 109, 114, 247, 117, 119 };
uint8_t expected[] = { 161, 138, 119, 118, 123, 118, 113, 122, 143, 140, 134,
133, 134, 126, 116, 114, 147, 149, 145, 142, 143, 138,
126, 118, 164, 156, 148, 144, 148, 148, 138, 126 };
const int w = 8;
const int h = 4;
uint8_t *padded = pad_8tap_convolve(luma, w, h);
uint8_t *output = (uint8_t *)aom_memalign(32, w * h);
gaussian_blur(padded, stride_8tap(w), w, h, output);
for (int i = 0; i < w * h; ++i) {
ASSERT_EQ(expected[i], output[i]);
}
free_pad_8tap(padded, w);
aom_free(output);
}
INSTANTIATE_TEST_CASE_P(EdgeDetectImages, EdgeDetectImageTest,
::testing::Combine(
// Width
::testing::Values(8, 16, 32),
// Height
::testing::Values(4, 8, 12, 32)));
} // namespace