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The following commit(s) were added to refs/heads/main by this push:
new 027ec5209c [SYSTEMDS-3545] Image Mirror Linearized
027ec5209c is described below
commit 027ec5209ca17d469417cbc98ce028e5043fea89
Author: baristerzioglu <[email protected]>
AuthorDate: Fri Sep 8 12:53:15 2023 +0200
[SYSTEMDS-3545] Image Mirror Linearized
This commit adds an linearized version of Mirror,
A future commit have to change the mirror operation to
use the Transform operation, since mirror can be translated
into an transform operation.
LDE Project SoSe 2023
Closes #1903
---
scripts/builtin/img_mirror_linearized.dml | 78 ++++++++++++++
.../java/org/apache/sysds/common/Builtins.java | 1 +
.../builtin/part1/BuiltinImageBrightnessTest.java | 36 +++----
.../part1/BuiltinImageMirrorLinearizedTest.java | 118 +++++++++++++++++++++
.../functions/builtin/image_mirror_linearized.dml | 43 ++++++++
5 files changed, 257 insertions(+), 19 deletions(-)
diff --git a/scripts/builtin/img_mirror_linearized.dml
b/scripts/builtin/img_mirror_linearized.dml
new file mode 100644
index 0000000000..08b3fe539f
--- /dev/null
+++ b/scripts/builtin/img_mirror_linearized.dml
@@ -0,0 +1,78 @@
+#-------------------------------------------------------------
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+#-------------------------------------------------------------
+
+# This function has the same functionality with img_mirror but it handles
multiple images at
+# the same time. Each row of the input and output matrix represents a
linearized image/matrix
+# It flips an image on the X (horizontal) or Y (vertical) axis.
+# INPUT:
+#
-----------------------------------------------------------------------------------------
+# img_matrix Input matrix/image (every row represents a linearized
matrix/image)
+# horizontal_axis flip either in X or Y axis
+# original_rows number of rows in the original 2-D images
+# original_cols number of cols in the original 2-D images
+#
-----------------------------------------------------------------------------------------
+#
+# OUTPUT:
+#
-----------------------------------------------------------------------------------------
+# R Output matrix/image (every row represents a linearized
matrix/image)
+#
-----------------------------------------------------------------------------------------
+
+m_img_mirror_linearized = function(matrix[double] img_matrix, Boolean
horizontal_axis,
+Integer original_rows, Integer original_cols) return (matrix[double] R) {
+ n = ncol(img_matrix);
+ R = matrix(0, rows=nrow(img_matrix), cols=n);
+ rows = original_rows;
+ cols = original_cols;
+
+ if (horizontal_axis) {
+ parfor (i in seq(1, (rows %/% 2) * cols, cols),check=0) {
+ start = i;
+ end = i + cols - 1;
+ mirrorStart = (n - end) + 1;
+ mirrorEnd = (n - start) + 1;
+ R[, start:end] = img_matrix[, mirrorStart:mirrorEnd];
+ R[, mirrorStart:mirrorEnd] = img_matrix[, start:end];
+ }
+ if (rows %% 2 == 1) {
+ midStart = ((rows %/% 2)) * cols + 1;
+ midEnd = midStart + cols - 1;
+ R[, midStart:midEnd] = img_matrix[, midStart:midEnd];
+ }
+ }
+ else {
+ offset = 1;
+ while (offset <= n) {
+ end = min(n, offset + cols - 1);
+ reversed_sub_matrix = matrix(0, rows=nrow(img_matrix), cols=cols);
+ idx = 1;
+ for (j in offset:end) {
+ reversed_sub_matrix[, cols - idx + 1] = img_matrix[, j];
+ idx = idx + 1;
+ }
+ R[, offset:end] = reversed_sub_matrix;
+ offset = end + 1;
+ }
+ }
+}
+
+
+
+
diff --git a/src/main/java/org/apache/sysds/common/Builtins.java
b/src/main/java/org/apache/sysds/common/Builtins.java
index fa6ddfc4eb..426fefc71c 100644
--- a/src/main/java/org/apache/sysds/common/Builtins.java
+++ b/src/main/java/org/apache/sysds/common/Builtins.java
@@ -155,6 +155,7 @@ public enum Builtins {
HYPERBAND("hyperband", true),
IFELSE("ifelse", false),
IMG_MIRROR("img_mirror", true),
+ IMG_MIRROR_LINEARIZED("img_mirror_linearized", true),
IMG_BRIGHTNESS("img_brightness", true),
IMG_BRIGHTNESS_LINEARIZED("img_brightness_linearized", true),
IMG_CROP("img_crop", true),
diff --git
a/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageBrightnessTest.java
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageBrightnessTest.java
index 4713c18b96..5d200c05d7 100644
---
a/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageBrightnessTest.java
+++
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageBrightnessTest.java
@@ -29,8 +29,7 @@ import org.apache.sysds.test.TestUtils;
import java.util.HashMap;
-public class BuiltinImageBrightnessTest extends AutomatedTestBase
-{
+public class BuiltinImageBrightnessTest extends AutomatedTestBase {
private final static String TEST_NAME = "image_brightness";
private final static String TEST_DIR = "functions/builtin/";
private static final String TEST_CLASS_DIR = TEST_DIR +
BuiltinImageBrightnessTest.class.getSimpleName() + "/";
@@ -43,54 +42,53 @@ public class BuiltinImageBrightnessTest extends
AutomatedTestBase
@Override
public void setUp() {
- addTestConfiguration(TEST_NAME,new
TestConfiguration(TEST_CLASS_DIR, TEST_NAME,new String[]{"B"}));
+ addTestConfiguration(TEST_NAME, new
TestConfiguration(TEST_CLASS_DIR, TEST_NAME, new String[] {"B"}));
}
@Test
- public void testImageBrightnessMatrixDenseCP()
{runImageBrightnessTest(false, ExecType.CP);
+ public void testImageBrightnessMatrixDenseCP() {
+ runImageBrightnessTest(false, ExecType.CP);
}
@Test
- public void testImageBrightnessMatrixSparseCP()
{runImageBrightnessTest(true, ExecType.CP);
+ public void testImageBrightnessMatrixSparseCP() {
+ runImageBrightnessTest(true, ExecType.CP);
}
@Test
- public void testImageBrightnessMatrixDenseSP()
{runImageBrightnessTest(false, ExecType.SPARK);
+ public void testImageBrightnessMatrixDenseSP() {
+ runImageBrightnessTest(false, ExecType.SPARK);
}
@Test
- public void testImageBrightnessMatrixSparseSP()
{runImageBrightnessTest(false,ExecType.SPARK);
+ public void testImageBrightnessMatrixSparseSP() {
+ runImageBrightnessTest(false, ExecType.SPARK);
}
- private void runImageBrightnessTest(boolean sparse, ExecType instType)
- {
+ private void runImageBrightnessTest(boolean sparse, ExecType instType) {
ExecMode platformOld = setExecMode(instType);
-
- try
- {
+
+ try {
loadTestConfiguration(getTestConfiguration(TEST_NAME));
double sparsity = sparse ? spSparse : spDense;
String HOME = SCRIPT_DIR + TEST_DIR;
fullDMLScriptName = HOME + TEST_NAME + ".dml";
- programArgs = new String[]{"-nvargs",
- "in_file=" + input("A"),
- "out_file=" + output("B"),
- };
+ programArgs = new String[] {"-nvargs", "in_file=" +
input("A"), "out_file=" + output("B"),};
fullRScriptName = HOME + TEST_NAME + ".R";
rCmd = "Rscript" + " " + fullRScriptName + " " +
inputDir() + " " + expectedDir();
- //generate actual dataset
+ // generate actual dataset
double[][] A = getRandomMatrix(rows, cols, 0, 255,
sparsity, 7);
writeInputMatrixWithMTD("A", A, true);
runTest(true, false, null, -1);
runRScript(true);
- //compare matrices
+ // compare matrices
HashMap<MatrixValue.CellIndex, Double> dmlfile =
readDMLMatrixFromOutputDir("B");
- HashMap<MatrixValue.CellIndex, Double> rfile =
readRMatrixFromExpectedDir("B");
+ HashMap<MatrixValue.CellIndex, Double> rfile =
readRMatrixFromExpectedDir("B");
TestUtils.compareMatrices(dmlfile, rfile, eps,
"Stat-DML", "Stat-R");
}
diff --git
a/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageMirrorLinearizedTest.java
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageMirrorLinearizedTest.java
new file mode 100644
index 0000000000..c53bde9580
--- /dev/null
+++
b/src/test/java/org/apache/sysds/test/functions/builtin/part1/BuiltinImageMirrorLinearizedTest.java
@@ -0,0 +1,118 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * distributed with this work for additional information
+ * regarding copyright ownership. The ASF licenses this file
+ * to you under the Apache License, Version 2.0 (the
+ * "License"); you may not use this file except in compliance
+ * with the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing,
+ * software distributed under the License is distributed on an
+ * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+ * KIND, either express or implied. See the License for the
+ * specific language governing permissions and limitations
+ * under the License.
+ */
+package org.apache.sysds.test.functions.builtin.part1;
+
+import java.util.Arrays;
+import java.util.Collection;
+import java.util.HashMap;
+
+import org.apache.sysds.common.Types.ExecMode;
+import org.apache.sysds.common.Types.ExecType;
+import org.apache.sysds.runtime.matrix.data.MatrixValue;
+import org.apache.sysds.test.AutomatedTestBase;
+import org.apache.sysds.test.TestConfiguration;
+import org.apache.sysds.test.TestUtils;
+import org.junit.Ignore;
+import org.junit.Test;
+import org.junit.runner.RunWith;
+import org.junit.runners.Parameterized;
+
+@RunWith(Parameterized.class)
[email protected]
+public class BuiltinImageMirrorLinearizedTest extends AutomatedTestBase {
+
+ private final static String TEST_NAME_LINEARIZED =
"image_mirror_linearized";
+ private final static String TEST_DIR = "functions/builtin/";
+ private final static String TEST_CLASS_DIR = TEST_DIR +
BuiltinImageMirrorLinearizedTest.class.getSimpleName() + "/";
+ private final static double eps = 1e-10;
+ private final static double spSparse = 0.05;
+ private final static double spDense = 0.5;
+
+ @Parameterized.Parameter()
+ public int img_rows;
+ @Parameterized.Parameter(1)
+ public int img_cols;
+ @Parameterized.Parameter(2)
+ public int rows; // number of images
+ public int cols; // Initialized based on img_rows * img_cols
+
+ @Parameterized.Parameters
+ public static Collection<Object[]> data() {
+ return Arrays.asList(new Object[][] {{12, 12, 4}, {13, 11, 5},
{64, 64, 32}, {256, 256, 5}, {256, 253, 5},
+ {1024, 1024, 5}, {1024, 1048, 5}});
+ }
+
+ @Override
+ public void setUp() {
+ cols = img_rows * img_cols;
+ addTestConfiguration(TEST_NAME_LINEARIZED,
+ new TestConfiguration(TEST_CLASS_DIR,
TEST_NAME_LINEARIZED, new String[] {"B_x", "B_y"}));
+ }
+
+ @Test
+ public void testImageMirrorLinearized() {
+ runImageMirrorLinearizedTest(false, ExecType.CP);
+ }
+
+ @Test
+ public void testImageMirrorLinearizedSparse() {
+ runImageMirrorLinearizedTest(true, ExecType.CP);
+ }
+
+ @Test
+ @Ignore
+ public void testImageMirrorLinearizedSP() {
+ runImageMirrorLinearizedTest(false, ExecType.SPARK);
+ }
+
+ private void runImageMirrorLinearizedTest(boolean sparse, ExecType
instType) {
+ ExecMode platformOld = setExecMode(instType);
+ disableOutAndExpectedDeletion();
+
+ try {
+
loadTestConfiguration(getTestConfiguration(TEST_NAME_LINEARIZED));
+
+ double sparsity = sparse ? spSparse : spDense;
+ String HOME = SCRIPT_DIR + TEST_DIR;
+
+ fullDMLScriptName = HOME + TEST_NAME_LINEARIZED +
".dml";
+ programArgs = new String[] {"-nvargs", "in_file=" +
input("A"), "x_out_reshape_file=" + output("B_x_reshape"),
+ "y_out_reshape_file=" + output("B_y_reshape"),
"x_out_file=" + output("B_x"), "y_out_file=" + output("B_y"),
+ "img_rows=" + img_rows, "img_cols=" + img_cols};
+
+ double[][] A = getRandomMatrix(rows, cols, 0, 255,
sparsity, 7);
+ writeInputMatrixWithMTD("A", A, true);
+
+ runTest(true, false, null, -1);
+
+ HashMap<MatrixValue.CellIndex, Double>
dmlfileLinearizedX = readDMLMatrixFromOutputDir("B_x");
+ HashMap<MatrixValue.CellIndex, Double>
dmlfileLinearizedY = readDMLMatrixFromOutputDir("B_y");
+
+ HashMap<MatrixValue.CellIndex, Double> dmlfileX =
readDMLMatrixFromOutputDir("B_x_reshape");
+ HashMap<MatrixValue.CellIndex, Double> dmlfileY =
readDMLMatrixFromOutputDir("B_y_reshape");
+
+ TestUtils.compareMatrices(dmlfileLinearizedX, dmlfileX,
eps, "Stat-DML-LinearizedX", "Stat-DML-X");
+ TestUtils.compareMatrices(dmlfileLinearizedY, dmlfileY,
eps, "Stat-DML-LinearizedY", "Stat-DML-Y");
+
+ }
+ finally {
+ rtplatform = platformOld;
+ }
+ }
+}
diff --git a/src/test/scripts/functions/builtin/image_mirror_linearized.dml
b/src/test/scripts/functions/builtin/image_mirror_linearized.dml
new file mode 100644
index 0000000000..3501cade9d
--- /dev/null
+++ b/src/test/scripts/functions/builtin/image_mirror_linearized.dml
@@ -0,0 +1,43 @@
+#-------------------------------------------------------------
+#
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+#
+#-------------------------------------------------------------
+
+input_batched = read($in_file);
+num_images = nrow(input_batched);
+m_batched = ncol(input_batched);
+img_rows = $img_rows;
+img_cols = $img_cols;
+img_out_flattened_x = matrix(0, rows=num_images, cols=m_batched);
+img_out_flattened_y = matrix(0, rows=num_images, cols=m_batched);
+input_matrix = matrix(input_batched, rows=num_images, cols=m_batched);
+for(i in 1:num_images) {
+ image_i = matrix(input_matrix[i,], rows=img_rows, cols=img_cols);
+ img_out_x = img_mirror(image_i, TRUE);
+ img_out_y = img_mirror(image_i, FALSE);
+ img_out_flattened_x[i,] = matrix(img_out_x, rows=1, cols=m_batched);
+ img_out_flattened_y[i,] = matrix(img_out_y, rows=1, cols=m_batched);
+}
+write(img_out_flattened_x, $x_out_reshape_file);
+write(img_out_flattened_y, $y_out_reshape_file);
+imgs = matrix(input_batched, rows=num_images, cols=m_batched);
+img_out_x_linearized = img_mirror_linearized(imgs, TRUE, img_rows, img_cols);
+img_out_y_linearized = img_mirror_linearized(imgs, FALSE, img_rows, img_cols);
+write(img_out_x_linearized, $x_out_file);
+write(img_out_y_linearized, $y_out_file);
