update JDLL version, leave responsability of creating the code for

encodings on SAM specific model

pom.xml

@@ -145,7 +145,7 @@
 
 		<!-- NB: Deploy releases to the SciJava Maven repository. -->
 		<releaseProfiles>sign,deploy-to-scijava</releaseProfiles>
-		<dl-modelrunner.version>0.5.5</dl-modelrunner.version>
+		<dl-modelrunner.version>0.5.8-SNAPSHOT</dl-modelrunner.version>
 	</properties>
 
 	<dependencies>

src/main/java/ai/nets/samj/models/AbstractSamJ.java

@@ -268,31 +268,6 @@ else if (task.status == TaskStatus.CRASHED)
 	protected <T extends RealType<T> & NativeType<T>> 
 	void sendImgLib2AsNp() {
 		createSHMArray((RandomAccessibleInterval<T>) this.img);
-		String code = "";
-		// This line wants to recreate the original numpy array. Should look like:
-		// input0_appose_shm = shared_memory.SharedMemory(name=input0)
-		// input0 = np.ndarray(size, dtype="float64", buffer=input0_appose_shm.buf).reshape([64, 64])
-		code += "im_shm = shared_memory.SharedMemory(name='"
-							+ shma.getNameForPython() + "', size=" + shma.getSize() 
-							+ ")" + System.lineSeparator();
-		int size = 1;
-		for (long l : targetDims) {size *= l;}
-		code += "im = np.ndarray(" + size + ", dtype='" + CommonUtils.getDataType(Util.getTypeFromInterval(shma.getSharedRAI())) 
-			  + "', buffer=im_shm.buf).reshape([";
-		for (long ll : targetDims)
-			code += ll + ", ";
-		code = code.substring(0, code.length() - 2);
-		code += "])" + System.lineSeparator();
-		code += "input_h = im.shape[1]" + System.lineSeparator();
-		code += "input_w = im.shape[0]" + System.lineSeparator();
-		code += "globals()['input_h'] = input_h" + System.lineSeparator();
-		code += "globals()['input_w'] = input_w" + System.lineSeparator();
-		code += "task.update(str(im.shape))" + System.lineSeparator();
-		code += "im = torch.from_numpy(np.transpose(im))" + System.lineSeparator();
-		code += "task.update('after ' + str(im.shape))" + System.lineSeparator();
-		code += "im_shm.unlink()" + System.lineSeparator();
-		//code += "box_shm.close()" + System.lineSeparator();
-		this.script += code;
 	}
 
 	private <T extends RealType<T> & NativeType<T>> void sendCropAsNp(long[] cropSize) {
@@ -318,7 +293,7 @@ else if (cropSize.length == 2)
 							+ ")" + System.lineSeparator();
 		int size = 1;
 		for (long l : targetDims) {size *= l;}
-		code += "im = np.ndarray(" + size + ", dtype='" + CommonUtils.getDataType(Util.getTypeFromInterval(crop)) + "', buffer=im_shm.buf).reshape([";
+		code += "im = np.ndarray(" + size + ", dtype='" + CommonUtils.getDataTypeFromRAI(crop) + "', buffer=im_shm.buf).reshape([";
 		for (long ll : targetDims)
 			code += ll + ", ";
 		code = code.substring(0, code.length() - 2);
@@ -637,7 +612,7 @@ List<Polygon> processMask(RandomAccessibleInterval<T> img, boolean returnAll)
 			throw new IllegalArgumentException("The provided mask should be a 2d image with just one channel of width "
 					+ this.shma.getOriginalShape()[1] + " and height " + this.shma.getOriginalShape()[0]);
 		}
-		SharedMemoryArray maskShma = SharedMemoryArray.buildSHMA(img);
+		SharedMemoryArray maskShma = SharedMemoryArray.createSHMAFromRAI(img, false, false);
 		try {
 			return processMask(maskShma, returnAll);
 		} catch (IOException | RuntimeException | InterruptedException ex) {

src/main/java/ai/nets/samj/models/EfficientSamJ.java

@@ -28,13 +28,15 @@
 import io.bioimage.modelrunner.apposed.appose.Service.Task;
 import io.bioimage.modelrunner.apposed.appose.Service.TaskStatus;
 import io.bioimage.modelrunner.tensor.shm.SharedMemoryArray;
+import io.bioimage.modelrunner.utils.CommonUtils;
 import net.imglib2.RandomAccessibleInterval;
 import net.imglib2.converter.RealTypeConverters;
 import net.imglib2.img.array.ArrayImgs;
 import net.imglib2.type.NativeType;
 import net.imglib2.type.numeric.RealType;
 import net.imglib2.type.numeric.integer.UnsignedByteType;
 import net.imglib2.type.numeric.real.FloatType;
+import net.imglib2.util.Cast;
 import net.imglib2.util.Intervals;
 import net.imglib2.view.IntervalView;
 import net.imglib2.view.Views;
@@ -196,7 +198,32 @@ else if (task.status == TaskStatus.CRASHED)
 
 	@Override
 	protected void createEncodeImageScript() {
-		this.script = ""
+		String code = "";
+		// This line wants to recreate the original numpy array. Should look like:
+		// input0_appose_shm = shared_memory.SharedMemory(name=input0)
+		// input0 = np.ndarray(size, dtype="float64", buffer=input0_appose_shm.buf).reshape([64, 64])
+		code += "im_shm = shared_memory.SharedMemory(name='"
+							+ shma.getNameForPython() + "', size=" + shma.getSize() 
+							+ ")" + System.lineSeparator();
+		int size = 1;
+		for (long l : targetDims) {size *= l;}
+		code += "im = np.ndarray(" + size + ", dtype='" + CommonUtils.getDataTypeFromRAI(Cast.unchecked(shma.getSharedRAI()))
+			  + "', buffer=im_shm.buf).reshape([";
+		for (long ll : targetDims)
+			code += ll + ", ";
+		code = code.substring(0, code.length() - 2);
+		code += "])" + System.lineSeparator();
+		code += "input_h = im.shape[1]" + System.lineSeparator();
+		code += "input_w = im.shape[0]" + System.lineSeparator();
+		code += "globals()['input_h'] = input_h" + System.lineSeparator();
+		code += "globals()['input_w'] = input_w" + System.lineSeparator();
+		code += "task.update(str(im.shape))" + System.lineSeparator();
+		code += "im = torch.from_numpy(np.transpose(im))" + System.lineSeparator();
+		code += "task.update('after ' + str(im.shape))" + System.lineSeparator();
+		code += "im_shm.unlink()" + System.lineSeparator();
+		//code += "box_shm.close()" + System.lineSeparator();
+		this.script += code;
+		this.script += ""
 				+ "task.update(str(im.shape))" + System.lineSeparator()
 				+ "aa = predictor.get_image_embeddings(im[None, ...])";
 	}
@@ -379,7 +406,7 @@ private <T extends RealType<T> & NativeType<T>> void checkImageIsFine(RandomAcce
 	protected <T extends RealType<T> & NativeType<T>> void createSHMArray(RandomAccessibleInterval<T> imShared) {
 		RandomAccessibleInterval<T> imageToBeSent = ImgLib2Utils.reescaleIfNeeded(imShared);
 		long[] dims = imageToBeSent.dimensionsAsLongArray();
-		shma = SharedMemoryArray.buildMemorySegmentForImage(new long[] {dims[0], dims[1], dims[2]}, new FloatType());
+		shma = SharedMemoryArray.create(new long[] {dims[0], dims[1], dims[2]}, new FloatType(), false, false);
 		adaptImageToModel(imageToBeSent, shma.getSharedRAI());
 	}
 }

src/main/java/ai/nets/samj/models/EfficientViTSamJ.java

@@ -33,12 +33,15 @@
 import io.bioimage.modelrunner.apposed.appose.Service.TaskStatus;
 
 import io.bioimage.modelrunner.tensor.shm.SharedMemoryArray;
+import io.bioimage.modelrunner.utils.CommonUtils;
 import net.imglib2.RandomAccessibleInterval;
 import net.imglib2.converter.RealTypeConverters;
 import net.imglib2.img.array.ArrayImgs;
 import net.imglib2.type.NativeType;
 import net.imglib2.type.numeric.RealType;
 import net.imglib2.type.numeric.integer.UnsignedByteType;
+import net.imglib2.type.numeric.real.FloatType;
+import net.imglib2.util.Cast;
 import net.imglib2.util.Intervals;
 import net.imglib2.view.IntervalView;
 import net.imglib2.view.Views;
@@ -304,7 +307,22 @@ protected <T extends RealType<T> & NativeType<T>> void setImageOfInterest(Random
 
 	@Override
 	protected void createEncodeImageScript() {
-		this.script += ""
+		script = "";
+		script += "im_shm = shared_memory.SharedMemory(name='"
+				+ shma.getNameForPython() + "', size=" + shma.getSize() 
+				+ ")" + System.lineSeparator();
+		int size = 1;
+		for (long l : targetDims) {size *= l;}
+		script += "im = np.ndarray(" + size + ", dtype='" + "', buffer=im_shm.buf).reshape([";
+		for (long ll : targetDims)
+			script += ll + ", ";
+		script = script.substring(0, script.length() - 2);
+		script += "])" + System.lineSeparator();
+		script += "im = np.transpose(im, (1, 0, 2))" + System.lineSeparator();
+		//code += "np.save('/home/carlos/git/aa.npy', im)" + System.lineSeparator();
+		script += "im_shm.unlink()" + System.lineSeparator();
+		//code += "box_shm.close()" + System.lineSeparator();
+		script += ""
 			+ "task.update(str(im.shape))" + System.lineSeparator()
 			+ "predictor.set_image(im)";
 	}
@@ -313,7 +331,7 @@ protected void createEncodeImageScript() {
 	protected <T extends RealType<T> & NativeType<T>> void createSHMArray(RandomAccessibleInterval<T> imShared) {
 		RandomAccessibleInterval<T> imageToBeSent = ImgLib2Utils.reescaleIfNeeded(imShared);
 		long[] dims = imageToBeSent.dimensionsAsLongArray();
-		shma = SharedMemoryArray.buildMemorySegmentForImage(new long[] {dims[0], dims[1], dims[2]}, new UnsignedByteType());
+		shma = SharedMemoryArray.create(new long[] {dims[0], dims[1], dims[2]}, new UnsignedByteType(), false, false);
 		adaptImageToModel(imageToBeSent, shma.getSharedRAI());
 	}