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Preallocate buffer and use byte for Luminance in SSIM.
PiperOrigin-RevId: 439855702
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@ -50,6 +50,9 @@ import java.nio.ByteBuffer;
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* images like MSE (mean squared error), but rather outputs the human perceptual difference. A
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* higher SSIM score signifies higher similarity, while a SSIM score of 1 means the two images are
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* exactly the same.
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*
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* <p>SSIM is traditionally computed with the luminance channel (Y), this class uses the luma
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* channel (Y') because the {@linkplain MediaCodec decoder} decodes to luma.
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*/
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public final class SsimHelper {
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@ -76,6 +79,8 @@ public final class SsimHelper {
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new VideoDecodingWrapper(context, expectedVideoPath, DEFAULT_COMPARISON_INTERVAL);
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VideoDecodingWrapper actualDecodingWrapper =
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new VideoDecodingWrapper(context, actualVideoPath, DEFAULT_COMPARISON_INTERVAL);
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@Nullable byte[] expectedLumaBuffer = null;
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@Nullable byte[] actualLumaBuffer = null;
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double accumulatedSsim = 0.0;
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int comparedImagesCount = 0;
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try {
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@ -90,13 +95,21 @@ public final class SsimHelper {
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int width = expectedImage.getWidth();
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int height = expectedImage.getHeight();
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assertThat(actualImage.getWidth()).isEqualTo(width);
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assertThat(actualImage.getHeight()).isEqualTo(height);
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if (expectedLumaBuffer == null || expectedLumaBuffer.length != width * height) {
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expectedLumaBuffer = new byte[width * height];
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}
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if (actualLumaBuffer == null || actualLumaBuffer.length != width * height) {
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actualLumaBuffer = new byte[width * height];
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}
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try {
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accumulatedSsim +=
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SsimCalculator.calculate(
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extractLumaChannelBuffer(expectedImage),
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extractLumaChannelBuffer(actualImage),
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extractLumaChannelBuffer(expectedImage, expectedLumaBuffer),
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extractLumaChannelBuffer(actualImage, actualLumaBuffer),
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/* offset= */ 0,
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/* stride= */ width,
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width,
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@ -116,11 +129,13 @@ public final class SsimHelper {
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}
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/**
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* Returns the buffer of the luma (Y) channel of the image.
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* Extracts, sets and returns the buffer of the luma (Y') channel of the image.
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*
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* @param image The {@link Image} in YUV format.
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* @param lumaChannelBuffer The buffer where the extracted luma values are stored.
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* @return The {@code lumaChannelBuffer} for convenience.
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*/
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private static int[] extractLumaChannelBuffer(Image image) {
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private static byte[] extractLumaChannelBuffer(Image image, byte[] lumaChannelBuffer) {
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// This method is invoked on the main thread.
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// `image` should contain YUV channels.
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Image.Plane[] imagePlanes = image.getPlanes();
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@ -131,7 +146,6 @@ public final class SsimHelper {
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int width = image.getWidth();
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int height = image.getHeight();
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ByteBuffer lumaByteBuffer = lumaPlane.getBuffer();
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int[] lumaChannelBuffer = new int[width * height];
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for (int y = 0; y < height; y++) {
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for (int x = 0; x < width; x++) {
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lumaChannelBuffer[y * width + x] = lumaByteBuffer.get(y * rowStride + x * pixelStride);
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@ -148,7 +162,7 @@ public final class SsimHelper {
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// Use ExoPlayer's 10ms timeout setting. In practise, the test durations from using timeouts of
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// 1/10/100ms don't differ significantly.
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private static final long DEQUEUE_TIMEOUT_US = 10_000;
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// SSIM should be calculated using the luma (Y) channel, thus using the YUV color space.
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// SSIM should be calculated using the luma (Y') channel, thus using the YUV color space.
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private static final int IMAGE_READER_COLOR_SPACE = ImageFormat.YUV_420_888;
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private static final int MEDIA_CODEC_COLOR_SPACE =
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MediaCodecInfo.CodecCapabilities.COLOR_FormatYUV420Flexible;
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@ -333,8 +347,8 @@ public final class SsimHelper {
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/**
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* Calculates the Structural Similarity Index (SSIM) between two images.
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*
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* @param expected The luminance channel (Y) bitmap of the expected image.
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* @param actual The luminance channel (Y) bitmap of the actual image.
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* @param expected The luma channel (Y) bitmap of the expected image.
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* @param actual The luma channel (Y) bitmap of the actual image.
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* @param offset The offset.
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* @param stride The stride of the bitmap.
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* @param width The image width in pixels.
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@ -342,7 +356,7 @@ public final class SsimHelper {
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* @return The SSIM score between the input images.
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*/
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public static double calculate(
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int[] expected, int[] actual, int offset, int stride, int width, int height) {
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byte[] expected, byte[] actual, int offset, int stride, int width, int height) {
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double totalSsim = 0;
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int windowsCount = 0;
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@ -398,7 +412,7 @@ public final class SsimHelper {
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/** Returns the means of the pixels in the two provided windows, in order. */
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private static double getMean(
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int[] pixels, int start, int stride, int windowWidth, int windowHeight) {
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byte[] pixels, int start, int stride, int windowWidth, int windowHeight) {
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double total = 0;
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for (int y = 0; y < windowHeight; y++) {
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for (int x = 0; x < windowWidth; x++) {
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@ -410,8 +424,8 @@ public final class SsimHelper {
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/** Returns the two variances and the covariance of the two windows. */
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private static double[] getVariancesAndCovariance(
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int[] pixelsX,
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int[] pixelsY,
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byte[] pixelsX,
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byte[] pixelsY,
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double meanX,
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double meanY,
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int start,
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