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Open Source Computer Vision Library
https://opencv.org/
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107 lines
3.2 KiB
107 lines
3.2 KiB
package org.opencv.test.dnn; |
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import java.io.File; |
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import java.util.ArrayList; |
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import java.util.List; |
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import org.opencv.core.Core; |
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import org.opencv.core.Mat; |
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import org.opencv.core.Scalar; |
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import org.opencv.core.Size; |
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import org.opencv.dnn.DictValue; |
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import org.opencv.dnn.Dnn; |
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import org.opencv.dnn.Layer; |
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import org.opencv.dnn.Net; |
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import org.opencv.imgcodecs.Imgcodecs; |
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import org.opencv.imgproc.Imgproc; |
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import org.opencv.test.OpenCVTestCase; |
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public class DnnTensorFlowTest extends OpenCVTestCase { |
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private final static String ENV_OPENCV_DNN_TEST_DATA_PATH = "OPENCV_DNN_TEST_DATA_PATH"; |
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private final static String ENV_OPENCV_TEST_DATA_PATH = "OPENCV_TEST_DATA_PATH"; |
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String modelFileName = ""; |
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String sourceImageFile = ""; |
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Net net; |
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@Override |
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protected void setUp() throws Exception { |
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super.setUp(); |
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String envDnnTestDataPath = System.getenv(ENV_OPENCV_DNN_TEST_DATA_PATH); |
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if(envDnnTestDataPath == null){ |
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isTestCaseEnabled = false; |
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return; |
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} |
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File dnnTestDataPath = new File(envDnnTestDataPath); |
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modelFileName = new File(dnnTestDataPath, "dnn/tensorflow_inception_graph.pb").toString(); |
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String envTestDataPath = System.getenv(ENV_OPENCV_TEST_DATA_PATH); |
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if(envTestDataPath == null) throw new Exception(ENV_OPENCV_TEST_DATA_PATH + " has to be defined!"); |
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File testDataPath = new File(envTestDataPath); |
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File f = new File(testDataPath, "dnn/space_shuttle.jpg"); |
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sourceImageFile = f.toString(); |
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if(!f.exists()) throw new Exception("Test image is missing: " + sourceImageFile); |
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net = Dnn.readNetFromTensorflow(modelFileName); |
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} |
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public void testGetLayerTypes() { |
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List<String> layertypes = new ArrayList(); |
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net.getLayerTypes(layertypes); |
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assertFalse("No layer types returned!", layertypes.isEmpty()); |
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} |
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public void testGetLayer() { |
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List<String> layernames = net.getLayerNames(); |
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assertFalse("Test net returned no layers!", layernames.isEmpty()); |
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String testLayerName = layernames.get(0); |
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DictValue layerId = new DictValue(testLayerName); |
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assertEquals("DictValue did not return the string, which was used in constructor!", testLayerName, layerId.getStringValue()); |
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Layer layer = net.getLayer(layerId); |
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assertEquals("Layer name does not match the expected value!", testLayerName, layer.get_name()); |
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} |
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public void testTestNetForward() { |
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Mat rawImage = Imgcodecs.imread(sourceImageFile); |
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assertNotNull("Loading image from file failed!", rawImage); |
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Mat image = new Mat(); |
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Imgproc.resize(rawImage, image, new Size(224,224)); |
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Mat inputBlob = Dnn.blobFromImage(image); |
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assertNotNull("Converting image to blob failed!", inputBlob); |
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Mat inputBlobP = new Mat(); |
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Core.subtract(inputBlob, new Scalar(117.0), inputBlobP); |
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net.setInput(inputBlobP, "input" ); |
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Mat result = net.forward(); |
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assertNotNull("Net returned no result!", result); |
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Core.MinMaxLocResult minmax = Core.minMaxLoc(result.reshape(1, 1)); |
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assertTrue("No image recognized!", minmax.maxVal > 0.9); |
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} |
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}
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