corect small errors in the example

src/main/java/io/bioimage/modelrunner/example/ExampleLoadTensorflow1Tensorflow2.java

@@ -56,7 +56,7 @@
  * 
  * It also requires the installation of a TF2 and a TF1 engine.
  * 
- * The example code downloads all the needed artifacts, thus excuting the whole
+ * The example code downloads all the needed artifacts, thus executing the whole
  * example might take some time.
  * 
  * @author Carlos Garcia Lopez de Haro
@@ -67,6 +67,20 @@ public class ExampleLoadTensorflow1Tensorflow2 {
 	private static final String ENGINES_DIR = new File(CWD, "engines").getAbsolutePath();
 	private static final String MODELS_DIR = new File(CWD, "models").getAbsolutePath();
 
+	/**
+	 * Run the test
+	 * @param <T>
+	 * 	type of the tensors
+	 * @param args
+	 * 	arguments of the main method
+	 * @throws LoadEngineException if there is any exception loading the engine
+	 * @throws Exception if there is any exception in the tests
+	 */
+	public static < T extends RealType< T > & NativeType< T > > void main(String[] args) throws LoadEngineException, Exception {
+		loadAndRunTf1();
+		loadAndRunTf2();
+	}
+
 	/**
 	 * Loads a TF2 model and runs it
 	 * @throws LoadEngineException if there is any error loading an engine
@@ -105,10 +119,10 @@ public static void loadAndRunTf2() throws LoadEngineException, Exception {
 		Model model = loadModel(modelFolder, null, engineInfo);
 		// Create an image that will be the backend of the Input Tensor
 		final ImgFactory< FloatType > imgFactory = new ArrayImgFactory<>( new FloatType() );
-		final Img< FloatType > img1 = imgFactory.create( 1, 512, 512, 1 );
+		final Img< FloatType > img1 = imgFactory.create( 1, 1, 3, 64, 64 );
 		// Create the input tensor with the nameand axes given by the rdf.yaml file
 		// and add it to the list of input tensors
-		Tensor<FloatType> inpTensor = Tensor.build("input", "bcyx", img1);
+		Tensor<FloatType> inpTensor = Tensor.build("input0", "bczyx", img1);
 		List<Tensor<?>> inputs = new ArrayList<Tensor<?>>();
 		inputs.add(inpTensor);
 
@@ -117,10 +131,13 @@ public static void loadAndRunTf2() throws LoadEngineException, Exception {
 		/// Regard that output tensors can be built empty without allocating memory
 		// or allocating memory by creating the tensor with a sample empty image, or by
 		// defining the dimensions and data type
-		final Img< FloatType > img2 = imgFactory.create( 1, 512, 512, 33 );
-		Tensor<FloatType> outTensor = Tensor.build("output", "bcyx", img2);
+		Tensor<FloatType> outTensor0 = Tensor.buildBlankTensor(
+				"output0", "bczyx", new long[] {1, 1, 3, 64, 64}, new FloatType());
+		final Img< FloatType > img2 = imgFactory.create( 1, 2, 3, 64, 64 );
+		Tensor<FloatType> outTensor1 = Tensor.build("output1", "bczyx", img2);
 		List<Tensor<?>> outputs = new ArrayList<Tensor<?>>();
-		outputs.add(outTensor);
+		outputs.add(outTensor0);
+		outputs.add(outTensor1);
 
 		// Run the model on the input tensors. THe output tensors 
 		// will be rewritten with the result of the execution
@@ -171,11 +188,11 @@ public static void loadAndRunTf1() throws LoadEngineException, Exception {
 		// Load the corresponding model, for Tensorflow the arg model_source is not needed
 		Model model = loadModel(modelFolder, null, engineInfo);
 		// Create an image that will be the backend of the Input Tensor
-		final ImgFactory< FloatType > imgFactory = new CellImgFactory<>( new FloatType(), 5 );
-		final Img< FloatType > img1 = imgFactory.create( 1, 512, 512, 1 );
+		final ImgFactory< FloatType > imgFactory = new ArrayImgFactory<>( new FloatType() );
+		final Img< FloatType > img1 = imgFactory.create( 1, 512, 512, 3 );
 		// Create the input tensor with the nameand axes given by the rdf.yaml file
 		// and add it to the list of input tensors
-		Tensor<FloatType> inpTensor = Tensor.build("input0", "bcyx", img1);
+		Tensor<FloatType> inpTensor = Tensor.build("input0", "byxc", img1);
 		List<Tensor<?>> inputs = new ArrayList<Tensor<?>>();
 		inputs.add(inpTensor);
 
@@ -184,8 +201,8 @@ public static void loadAndRunTf1() throws LoadEngineException, Exception {
 		/// Regard that output tensors can be built empty without allocating memory
 		// or allocating memory by creating the tensor with a sample empty image, or by
 		// defining the dimensions and data type
-		final Img< FloatType > img2 = imgFactory.create( 1, 512, 512, 1 );
-		Tensor<FloatType> outTensor = Tensor.build("output0", "bcyx", img2);
+		final Img< FloatType > img2 = imgFactory.create( 1, 512, 512, 33 );
+		Tensor<FloatType> outTensor = Tensor.build("output0", "byxc", img2);
 		List<Tensor<?>> outputs = new ArrayList<Tensor<?>>();
 		outputs.add(outTensor);
 
@@ -201,20 +218,6 @@ public static void loadAndRunTf1() throws LoadEngineException, Exception {
 		System.out.print("Success running Tensorflow 1!!");
 	}
 
-	/**
-	 * Run the test
-	 * @param <T>
-	 * 	type of the tensors
-	 * @param args
-	 * 	arguments of the main method
-	 * @throws LoadEngineException if there is any exception loading the engine
-	 * @throws Exception if there is any exception in the tests
-	 */
-	public static < T extends RealType< T > & NativeType< T > > void main(String[] args) throws LoadEngineException, Exception {
-		loadAndRunTf1();
-		loadAndRunTf2();
-	}
-
 	/**
 	 * Method that creates the {@link EngineInfo} object.
 	 * @param engine