add java wrappers to dnn module

2017-06-27 10:52:44 +04:00
parent e5aa213554
commit 8f7181429f
11 changed files with 347 additions and 32 deletions
@@ -0,0 +1,113 @@
+package org.opencv.test.dnn;
+
+import java.io.File;
+import java.util.ArrayList;
+import java.util.List;
+import org.opencv.core.Core;
+import org.opencv.core.Mat;
+import org.opencv.core.Scalar;
+import org.opencv.core.Size;
+import org.opencv.dnn.DictValue;
+import org.opencv.dnn.Dnn;
+import org.opencv.dnn.Importer;
+import org.opencv.dnn.Layer;
+import org.opencv.dnn.Net;
+import org.opencv.imgcodecs.Imgcodecs;
+import org.opencv.imgproc.Imgproc;
+import org.opencv.test.OpenCVTestCase;
+
+public class DnnTensorFlowTest extends OpenCVTestCase {
+
+    private final static String ENV_OPENCV_DNN_TEST_DATA_PATH = "OPENCV_DNN_TEST_DATA_PATH";
+
+    private final static String ENV_OPENCV_TEST_DATA_PATH = "OPENCV_TEST_DATA_PATH";
+
+    String modelFileName = "";
+    String sourceImageFile = "";
+
+    Net net;
+
+    @Override
+    protected void setUp() throws Exception {
+        super.setUp();
+
+        String envDnnTestDataPath = System.getenv(ENV_OPENCV_DNN_TEST_DATA_PATH);
+
+        if(envDnnTestDataPath == null){
+            isTestCaseEnabled = false;
+            return;
+        }
+
+        File dnnTestDataPath = new File(envDnnTestDataPath);
+        modelFileName =  new File(dnnTestDataPath, "dnn/tensorflow_inception_graph.pb").toString();
+
+        String envTestDataPath = System.getenv(ENV_OPENCV_TEST_DATA_PATH);
+
+        if(envTestDataPath == null) throw new Exception(ENV_OPENCV_TEST_DATA_PATH + " has to be defined!");
+
+        File testDataPath = new File(envTestDataPath);
+
+        File f = new File(testDataPath, "dnn/space_shuttle.jpg");
+        sourceImageFile = f.toString();
+        if(!f.exists()) throw new Exception("Test image is missing: " + sourceImageFile);
+
+        net = new Net();
+        if(net.empty()) {
+            Importer importer = Dnn.createTensorflowImporter(modelFileName);
+            importer.populateNet(net);
+        }
+
+    }
+
+    public void testGetLayerTypes() {
+        List<String> layertypes = new ArrayList();
+        net.getLayerTypes(layertypes);
+
+        assertFalse("No layer types returned!", layertypes.isEmpty());
+    }
+
+    public void testGetLayer() {
+        List<String> layernames = net.getLayerNames();
+
+        assertFalse("Test net returned no layers!", layernames.isEmpty());
+
+        String testLayerName = layernames.get(0);
+
+        DictValue layerId = new DictValue(testLayerName);
+
+        assertEquals("DictValue did not return the string, which was used in constructor!", testLayerName, layerId.getStringValue());
+
+        Layer layer = net.getLayer(layerId);
+
+        assertEquals("Layer name does not match the expected value!", testLayerName, layer.get_name());
+
+    }
+
+    public void testTestNetForward() {
+        Mat rawImage = Imgcodecs.imread(sourceImageFile);
+
+        assertNotNull("Loading image from file failed!", rawImage);
+
+        Mat image = new Mat();
+        Imgproc.resize(rawImage, image, new Size(224,224));
+
+        Mat inputBlob = Dnn.blobFromImage(image);
+        assertNotNull("Converting image to blob failed!", inputBlob);
+
+        Mat inputBlobP = new Mat();
+        Core.subtract(inputBlob, new Scalar(117.0), inputBlobP);
+
+        net.setInput(inputBlobP, "input" );
+
+        Mat result = net.forward();
+
+        assertNotNull("Net returned no result!", result);
+
+        Core.MinMaxLocResult minmax = Core.minMaxLoc(result.reshape(1, 1));
+
+        assertTrue("No image recognized!", minmax.maxVal > 0.9);
+
+
+    }
+
+}