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// Unit tests for FFTConvolutionEffect.
#include <epoxy/gl.h>
#include <math.h>
#include "effect_chain.h"
#include "gtest/gtest.h"
#include "image_format.h"
#include "test_util.h"
#include "fft_convolution_effect.h"
namespace movit {
TEST(FFTConvolutionEffectTest, Identity) {
const int size = 4;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float out_data[size * size];
for (int convolve_size = 1; convolve_size < 10; ++convolve_size) {
float kernel[convolve_size * convolve_size];
for (int i = 0; i < convolve_size * convolve_size; ++i) {
kernel[i] = 0.0f;
}
kernel[0] = 1.0f;
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_size, convolve_size);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
expect_equal(data, out_data, size, size, 0.02, 0.003);
}
}
TEST(FFTConvolutionEffectTest, Constant) {
const int size = 4, convolve_size = 17;
const float f = 7.0f;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float expected_data[size * size] = {
f * 0.1f, f * 1.1f, f * 2.1f, f * 3.1f,
f * 0.2f, f * 1.2f, f * 2.2f, f * 3.2f,
f * 0.3f, f * 1.3f, f * 2.3f, f * 3.3f,
f * 0.4f, f * 1.4f, f * 2.4f, f * 3.4f,
};
float out_data[size * size];
float kernel[convolve_size * convolve_size];
for (int i = 0; i < convolve_size * convolve_size; ++i) {
kernel[i] = 0.0f;
}
kernel[0] = f;
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_size, convolve_size);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
// Somewhat looser bounds due to the higher magnitude.
expect_equal(expected_data, out_data, size, size, f * 0.03, f * 0.004);
}
TEST(FFTConvolutionEffectTest, MoveRight) {
const int size = 4, convolve_size = 3;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float kernel[convolve_size * convolve_size] = {
0.0, 1.0, 0.0,
0.0, 0.0, 0.0,
0.0, 0.0, 0.0,
};
float expected_data[size * size] = {
0.1, 0.1, 1.1, 2.1,
0.2, 0.2, 1.2, 2.2,
0.3, 0.3, 1.3, 2.3,
0.4, 0.4, 1.4, 2.4,
};
float out_data[size * size];
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_size, convolve_size);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
expect_equal(expected_data, out_data, size, size, 0.02, 0.003);
}
TEST(FFTConvolutionEffectTest, MoveDown) {
const int size = 4, convolve_size = 3;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float kernel[convolve_size * convolve_size] = {
0.0, 0.0, 0.0,
1.0, 0.0, 0.0,
0.0, 0.0, 0.0,
};
float expected_data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
};
float out_data[size * size];
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_size, convolve_size);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
expect_equal(expected_data, out_data, size, size, 0.02, 0.003);
}
TEST(FFTConvolutionEffectTest, MergeWithLeft) {
const int size = 4, convolve_size = 3;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float kernel[convolve_size * convolve_size] = {
1.0, 1.0, 0.0,
0.0, 0.0, 0.0,
0.0, 0.0, 0.0,
};
float expected_data[size * size] = {
0.1 + 0.1, 0.1 + 1.1, 1.1 + 2.1, 2.1 + 3.1,
0.2 + 0.2, 0.2 + 1.2, 1.2 + 2.2, 2.2 + 3.2,
0.3 + 0.3, 0.3 + 1.3, 1.3 + 2.3, 2.3 + 3.3,
0.4 + 0.4, 0.4 + 1.4, 1.4 + 2.4, 2.4 + 3.4,
};
float out_data[size * size];
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_size, convolve_size);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
expect_equal(expected_data, out_data, size, size, 0.02, 0.003);
}
TEST(FFTConvolutionEffectTest, NegativeCoefficients) {
const int size = 4;
const int convolve_width = 3, convolve_height = 2;
float data[size * size] = {
0.1, 1.1, 2.1, 3.1,
0.2, 1.2, 2.2, 3.2,
0.3, 1.3, 2.3, 3.3,
0.4, 1.4, 2.4, 3.4,
};
float kernel[convolve_width * convolve_height] = {
1.0, 0.0, 0.0,
0.0, 0.0, -0.5,
};
float expected_data[size * size] = {
0.1 - 0.5 * 0.1, 1.1 - 0.5 * 0.1, 2.1 - 0.5 * 0.1, 3.1 - 0.5 * 1.1,
0.2 - 0.5 * 0.1, 1.2 - 0.5 * 0.1, 2.2 - 0.5 * 0.1, 3.2 - 0.5 * 1.1,
0.3 - 0.5 * 0.2, 1.3 - 0.5 * 0.2, 2.3 - 0.5 * 0.2, 3.3 - 0.5 * 1.2,
0.4 - 0.5 * 0.3, 1.4 - 0.5 * 0.3, 2.4 - 0.5 * 0.3, 3.4 - 0.5 * 1.3,
};
float out_data[size * size];
EffectChainTester tester(nullptr, size, size, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR);
tester.add_input(data, FORMAT_GRAYSCALE, COLORSPACE_sRGB, GAMMA_LINEAR, size, size);
FFTConvolutionEffect *fft_effect = new FFTConvolutionEffect(size, size, convolve_width, convolve_height);
tester.get_chain()->add_effect(fft_effect);
fft_effect->set_convolution_kernel(kernel);
tester.run(out_data, GL_RED, COLORSPACE_sRGB, GAMMA_LINEAR, OUTPUT_ALPHA_FORMAT_PREMULTIPLIED);
expect_equal(expected_data, out_data, size, size, 0.02, 0.003);
}
} // namespace movit
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