+ downloading model from community

pom.xml

@@ -57,6 +57,11 @@
                 <artifactId>libtensorflow_jni_gpu</artifactId>
                 <version>1.10.0</version>
             </dependency>
+			<dependency>
+			    <groupId>org.apache.ant</groupId>
+			    <artifactId>ant-compress</artifactId>
+			    <version>1.5</version>
+			</dependency>
             <dependency>
                 <groupId>commons-configuration</groupId>
                 <artifactId>commons-configuration</artifactId>

src/main/java/TensorflowInferModel.java

@@ -3,10 +3,17 @@
  * SPDX-License-Identifier: GPL-3.0-or-later
  */
 
+import java.io.File;
+import java.io.IOException;
+import java.net.URL;
 import java.nio.FloatBuffer;
 import java.nio.IntBuffer;
+import java.nio.file.Files;
+import java.nio.file.Path;
+import java.nio.file.StandardCopyOption;
 import java.util.ArrayList;
 
+import org.apache.ant.compress.taskdefs.Unzip;
 import org.tensorflow.SavedModelBundle;
 import org.tensorflow.Tensor;
 
@@ -47,9 +54,12 @@ Sessions and Tensors
 
 public class TensorflowInferModel
 {
-
+	
+    final static String TRAINED_MODEL_URL = "https://community.elphel.com/files/quad-stereo/ml/trained_model_v1.0.zip";
+	
     final static String TRAINED_MODEL = "trained_model"; // /home/oleg/GIT/python3-imagej-tiff/data_sets/tf_data_5x5_main_13_heur/exportdir";
     final static String SERVING = "serve";
+    
     final int         tilesX, tilesY, num_tiles, num_layers;
     final int         corr_side, corr_side2;
 //    final long []     shape_corr2d;
@@ -68,6 +78,40 @@ long[] shape = new long[] {batch, imageSize};
 //    public
     final SavedModelBundle bundle;
 
+    // utils: download url
+    private static Path download(String sourceURL, String targetDirectory) throws IOException
+    {
+        URL url = new URL(sourceURL);
+        String fileName = sourceURL.substring(sourceURL.lastIndexOf('/') + 1, sourceURL.length());
+        Path targetPath = new File(targetDirectory + File.separator + fileName).toPath();
+        Files.copy(url.openStream(), targetPath, StandardCopyOption.REPLACE_EXISTING);
+
+        return targetPath;
+    }
+    
+    // utils: unpack zip to dir
+    private static boolean download_and_unpack(String sourceURL, String targetDirectory) {
+    	
+    	Path zipped_model = null;
+    	
+    	System.out.println("Downloading "+sourceURL+". Please, wait...");
+    	try {
+			zipped_model = download(sourceURL, targetDirectory);
+    	} catch (IOException e){
+    		e.printStackTrace();
+    		return false;
+    	}
+    	
+		Unzip unzipper = new Unzip();
+		unzipper.setSrc(zipped_model.toFile());
+		unzipper.setDest(new File(targetDirectory));
+		unzipper.execute();
+		
+		System.out.println(unzipper.getLocation());
+    	
+    	return true;
+    }
+    
     public TensorflowInferModel(int tilesX, int tilesY, int corr_side, int num_layers)
     {
     	this.tilesX = tilesX;
@@ -83,11 +127,26 @@ long[] shape = new long[] {batch, imageSize};
     	this.fb_tiles_stage2 =     IntBuffer.allocate(num_tiles );
     	this.fb_predicted =        FloatBuffer.allocate(num_tiles );
 
-    	String abs_model_path = getClass().getClassLoader().getResource(TRAINED_MODEL).getFile();
+    	//String resourceDir = System.getProperty("user.dir")+"/src/main/resources";
+    	// ./target/classes/
+    	String resourceDir = getClass().getClassLoader().getResource("").getFile();
+    	String abs_model_path = null;
+    	
+    	try {
+    		abs_model_path = getClass().getClassLoader().getResource(TRAINED_MODEL).getFile();
+    	} catch (java.lang.NullPointerException e) {
+    		//e.printStackTrace();
+    		download_and_unpack(TRAINED_MODEL_URL, resourceDir);
+    		// re-read
+    		abs_model_path = getClass().getClassLoader().getResource(TRAINED_MODEL).getFile();
+    		System.out.println("New downloaded path: "+abs_model_path);
+    	}
+    	
         System.out.println("TensorflowInferModel model path: "+abs_model_path);
+        
         // this will load graph/data and open a session that does not need to be closed until the program is closed
 ////        bundle = null;
-        bundle = SavedModelBundle.load(abs_model_path,SERVING);
+        bundle = SavedModelBundle.load(abs_model_path, SERVING);
 
 //    	Operation opr = bundle.graph().operation("rv_stage1_out");
     }