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package org.opencv.test.dnn;
import java.io.File;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfInt;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfByte;
import org.opencv.core.Scalar;
import org.opencv.core.Size;
import org.opencv.dnn.DictValue;
import org.opencv.dnn.Dnn;
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;
/*
* regression test for #12324,
* testing various java.util.List invocations,
* which use the LIST_GET macro
*/
public class DnnListRegressionTest 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/grace_hopper_227.png");
sourceImageFile = f.toString();
if(!f.exists()) throw new Exception("Test image is missing: " + sourceImageFile);
net = Dnn.readNetFromTensorflow(modelFileName);
Mat image = Imgcodecs.imread(sourceImageFile);
assertNotNull("Loading image from file failed!", image);
Mat inputBlob = Dnn.blobFromImage(image, 1.0, new Size(224, 224), new Scalar(0), true, true);
assertNotNull("Converting image to blob failed!", inputBlob);
net.setInput(inputBlob, "input");
}
public void testSetInputsNames() {
List<String> inputs = new ArrayList();
inputs.add("input");
try {
net.setInputsNames(inputs);
} catch(Exception e) {
fail("Net setInputsNames failed: " + e.getMessage());
}
}
public void testForward() {
List<Mat> outs = new ArrayList();
List<String> outNames = new ArrayList();
outNames.add("softmax2");
try {
net.forward(outs,outNames);
} catch(Exception e) {
fail("Net forward failed: " + e.getMessage());
}
}
public void testGetMemoryConsumption() {
int layerId = 1;
List<MatOfInt> netInputShapes = new ArrayList();
netInputShapes.add(new MatOfInt(1, 3, 224, 224));
long[] weights=null;
long[] blobs=null;
try {
net.getMemoryConsumption(layerId, netInputShapes, weights, blobs);
} catch(Exception e) {
fail("Net getMemoryConsumption failed: " + e.getMessage());
}
}
public void testGetFLOPS() {
int layerId = 1;
List<MatOfInt> netInputShapes = new ArrayList();
netInputShapes.add(new MatOfInt(1, 3, 224, 224));
try {
net.getFLOPS(layerId, netInputShapes);
} catch(Exception e) {
fail("Net getFLOPS failed: " + e.getMessage());
}
}
}