diff --git a/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
index fb4977c44dfafca5a028527c9a4a1a7d1a4f3687..931abdc6021bc68e6965b4ac026eb0c0831136d4 100644
--- a/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
+++ b/src/main/java/org/bioimageanalysis/icy/tensorflow/v1/tensor/TensorBuilder.java
@@ -1,10 +1,21 @@
package org.bioimageanalysis.icy.tensorflow.v1.tensor;
+import java.nio.ByteBuffer;
+import java.nio.DoubleBuffer;
+import java.nio.FloatBuffer;
+import java.nio.IntBuffer;
+
+import org.bioimageanalysis.icy.deeplearning.tensor.RaiToArray;
import org.tensorflow.Tensor;
import org.tensorflow.types.UInt8;
import net.imglib2.RandomAccessibleInterval;
import net.imglib2.type.Type;
+import net.imglib2.type.numeric.integer.ByteType;
+import net.imglib2.type.numeric.integer.IntType;
+import net.imglib2.type.numeric.real.DoubleType;
+import net.imglib2.type.numeric.real.FloatType;
+import net.imglib2.util.Util;
/**
* A TensorFlow {@link Tensor} builder for {@link INDArray} and {@link org.bioimageanalysis.icy.deeplearning.tensor.Tensor} objects.
@@ -38,29 +49,29 @@ public final class TensorBuilder
/**
* Creates a {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
- * @param ndarray
+ * @param rai
* The NDArray to be converted.
* @return The tensor created from the sequence.
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- public static <T extends Type<T>> Tensor<?> build(RandomAccessibleInterval<T> ndarray)
+ public static <T extends Type<T>> Tensor<?> build(RandomAccessibleInterval<T> rai)
{
- if (ndarray.dataType() == DataType.INT8 || ndarray.dataType() == DataType.UINT8) {
- return buildByte(ndarray);
- } else if (ndarray.dataType() == DataType.INT32) {
- return buildInt(ndarray);
- } else if (ndarray.dataType() == DataType.FLOAT) {
- return buildFloat(ndarray);
- } else if (ndarray.dataType() == DataType.DOUBLE) {
- return buildDouble(ndarray);
+ if (Util.getTypeFromInterval(rai) instanceof ByteType) {
+ return buildByte((RandomAccessibleInterval<ByteType>) rai);
+ } else if (Util.getTypeFromInterval(rai) instanceof IntType) {
+ return buildInt((RandomAccessibleInterval<IntType>) rai);
+ } else if (Util.getTypeFromInterval(rai) instanceof FloatType) {
+ return buildFloat((RandomAccessibleInterval<FloatType>) rai);
+ } else if (Util.getTypeFromInterval(rai) instanceof DoubleType) {
+ return buildDouble((RandomAccessibleInterval<DoubleType>) rai);
} else {
- throw new IllegalArgumentException("The image has an unsupported type: " + ndarray.dataType().toString());
+ throw new IllegalArgumentException("The image has an unsupported type: " + Util.getTypeFromInterval(rai).getClass().toString());
}
}
/**
- * Creates a unsigned byte-typed {@link Tensor} based on the provided {@link INDArray} and the desired dimension order for the resulting tensor.
+ * Creates a unsigned byte-typed {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
* @param ndarray
* The sequence to be converted.
@@ -68,17 +79,16 @@ public final class TensorBuilder
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- private static Tensor<UInt8> buildByte(INDArray ndarray)
+ private static <T extends Type<T>> Tensor<UInt8> buildByte(RandomAccessibleInterval<ByteType> ndarray)
{
- if (ndarray.dataType() != DataType.INT8 && ndarray.dataType() != DataType.UINT8)
- throw new IllegalArgumentException("Image is not of byte type: " + ndarray.dataType().toString());
-
- Tensor<UInt8> tensor = Tensor.create(UInt8.class, ndarray.shape(), ndarray.data().asNio());
+ byte[] arr = RaiToArray.byteArray(ndarray);
+ ByteBuffer buff = ByteBuffer.wrap(arr);
+ Tensor<UInt8> tensor = Tensor.create(UInt8.class, ndarray.dimensionsAsLongArray(), buff);
return tensor;
}
/**
- * Creates a integer-typed {@link Tensor} based on the provided {@link INDArray} and the desired dimension order for the resulting tensor.
+ * Creates a integer-typed {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
* @param ndarray
* The sequence to be converted.
@@ -86,17 +96,16 @@ public final class TensorBuilder
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- private static Tensor<Integer> buildInt(INDArray ndarray)
+ private static <T extends Type<T>> Tensor<Integer> buildInt(RandomAccessibleInterval<IntType> ndarray)
{
- if (ndarray.dataType() != DataType.INT32)
- throw new IllegalArgumentException("Image is not of int type: " + ndarray.dataType().toString());
-
- Tensor<Integer> tensor = Tensor.create(ndarray.shape(), ndarray.data().asNioInt());
+ int[] arr = RaiToArray.intArray(ndarray);
+ IntBuffer buff = IntBuffer.wrap(arr);
+ Tensor<Integer> tensor = Tensor.create(ndarray.dimensionsAsLongArray(), buff);
return tensor;
}
/**
- * Creates a float-typed {@link Tensor} based on the provided {@link INDArray} and the desired dimension order for the resulting tensor.
+ * Creates a float-typed {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
* @param ndarray
* The sequence to be converted.
@@ -104,17 +113,16 @@ public final class TensorBuilder
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- private static Tensor<Float> buildFloat(INDArray ndarray)
+ private static <T extends Type<T>> Tensor<Float> buildFloat(RandomAccessibleInterval<FloatType> ndarray)
{
- if (ndarray.dataType() != DataType.FLOAT)
- throw new IllegalArgumentException("Image is not of float type: " + ndarray.dataType().toString());
-
- Tensor<Float> tensor = Tensor.create(ndarray.shape(), ndarray.data().asNioFloat());
+ float[] arr = RaiToArray.floatArray(ndarray);
+ FloatBuffer buff = FloatBuffer.wrap(arr);
+ Tensor<Float> tensor = Tensor.create(ndarray.dimensionsAsLongArray(), buff);
return tensor;
}
/**
- * Creates a double-typed {@link Tensor} based on the provided {@link INDArray} and the desired dimension order for the resulting tensor.
+ * Creates a double-typed {@link Tensor} based on the provided {@link RandomAccessibleInterval} and the desired dimension order for the resulting tensor.
*
* @param ndarray
* The ndarray to be converted.
@@ -122,12 +130,11 @@ public final class TensorBuilder
* @throws IllegalArgumentException
* If the ndarray type is not supported.
*/
- private static Tensor<Double> buildDouble(INDArray ndarray)
+ private static <T extends Type<T>> Tensor<Double> buildDouble(RandomAccessibleInterval<DoubleType> ndarray)
{
- if (ndarray.dataType() != DataType.DOUBLE)
- throw new IllegalArgumentException("Image is not of float type: " + ndarray.dataType().toString());
-
- Tensor<Double> tensor = Tensor.create(ndarray.shape(), ndarray.data().asNioDouble());
+ double[] arr = RaiToArray.doubleArray(ndarray);
+ DoubleBuffer buff = DoubleBuffer.wrap(arr);
+ Tensor<Double> tensor = Tensor.create(ndarray.dimensionsAsLongArray(), buff);
return tensor;
}
}