mirror of https://github.com/opencv/opencv.git
abratchik
7 years ago
parent
e5aa213554
commit
8f7181429f
11 changed files with 347 additions and 32 deletions
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misc/java/src/cpp/dnn_converters.hpp |
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{ |
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"type_dict": { |
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"MatShape": { |
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"j_type": "MatOfInt", |
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"jn_type": "long", |
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"jni_type": "jlong", |
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"jni_var": "MatShape %(n)s", |
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"suffix": "J", |
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"v_type": "Mat", |
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"j_import": "org.opencv.core.MatOfInt" |
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}, |
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"vector_MatShape": { |
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"j_type": "List<MatOfInt>", |
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"jn_type": "List<MatOfInt>", |
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"jni_type": "jobject", |
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"jni_var": "std::vector< MatShape > %(n)s", |
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"suffix": "Ljava_util_List", |
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"v_type": "vector_MatShape", |
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"j_import": "org.opencv.core.MatOfInt" |
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}, |
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"vector_size_t": { |
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"j_type": "MatOfDouble", |
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"jn_type": "long", |
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"jni_type": "jlong", |
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"jni_var": "std::vector<size_t> %(n)s", |
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"suffix": "J", |
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"v_type": "Mat", |
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"j_import": "org.opencv.core.MatOfDouble" |
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}, |
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"vector_Ptr_Layer": { |
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"j_type": "List<Layer>", |
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"jn_type": "List<Layer>", |
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"jni_type": "jobject", |
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"jni_var": "std::vector< Ptr<cv::dnn::Layer> > %(n)s", |
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"suffix": "Ljava_util_List", |
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"v_type": "vector_Layer", |
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"j_import": "org.opencv.dnn.Layer" |
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}, |
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"LayerId": { |
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"j_type": "DictValue", |
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"jn_type": "long", |
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"jn_args": [ |
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[ |
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"__int64", |
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".getNativeObjAddr()" |
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] |
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], |
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"jni_name": "(*(cv::dnn::DictValue*)%(n)s_nativeObj)", |
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"jni_type": "jlong", |
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"suffix": "J", |
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"j_import": "org.opencv.dnn.DictValue" |
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} |
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} |
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} |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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// Author: abratchik
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#include "dnn_converters.hpp" |
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void Mat_to_MatShape(cv::Mat& mat, MatShape& matshape) |
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{ |
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matshape.clear(); |
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CHECK_MAT(mat.type()==CV_32SC1 && mat.cols==1); |
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matshape = (MatShape) mat; |
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} |
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void MatShape_to_Mat(MatShape& matshape, cv::Mat& mat) |
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{ |
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mat = cv::Mat(matshape, true); |
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} |
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void Mat_to_vector_size_t(cv::Mat& mat, std::vector<size_t>& v_size_t) |
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{ |
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v_size_t.clear(); |
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CHECK_MAT(mat.type()==CV_32SC1 && mat.cols==1); |
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v_size_t = (std::vector<size_t>) mat; |
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} |
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void vector_size_t_to_Mat(std::vector<size_t>& v_size_t, cv::Mat& mat) |
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{ |
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mat = cv::Mat(v_size_t, true); |
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} |
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std::vector<MatShape> List_to_vector_MatShape(JNIEnv* env, jobject list) |
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{ |
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static jclass juArrayList = ARRAYLIST(env); |
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jmethodID m_size = LIST_SIZE(env, juArrayList); |
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jmethodID m_get = LIST_GET(env, juArrayList); |
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static jclass jMatOfInt = MATOFINT(env); |
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jint len = env->CallIntMethod(list, m_size); |
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std::vector<MatShape> result; |
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result.reserve(len); |
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for (jint i=0; i<len; i++) |
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{ |
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jobject element = static_cast<jobject>(env->CallObjectMethod(list, m_get, i)); |
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cv::Mat& mat = *((cv::Mat*) GETNATIVEOBJ(env, jMatOfInt, element) ); |
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MatShape matshape = (MatShape) mat; |
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result.push_back(matshape); |
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env->DeleteLocalRef(element); |
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} |
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return result; |
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} |
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jobject vector_Ptr_Layer_to_List(JNIEnv* env, std::vector<cv::Ptr<cv::dnn::Layer> >& vs) |
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{ |
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static jclass juArrayList = ARRAYLIST(env); |
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static jmethodID m_create = CONSTRUCTOR(env, juArrayList); |
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jmethodID m_add = LIST_ADD(env, juArrayList); |
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static jclass jLayerClass = LAYER(env); |
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static jmethodID m_create_layer = LAYER_CONSTRUCTOR(env, jLayerClass); |
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jobject result = env->NewObject(juArrayList, m_create, vs.size()); |
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for (std::vector< cv::Ptr<cv::dnn::Layer> >::iterator it = vs.begin(); it != vs.end(); ++it) { |
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jobject element = env->NewObject(jLayerClass, m_create_layer, (*it).get()); |
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env->CallBooleanMethod(result, m_add, element); |
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env->DeleteLocalRef(element); |
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} |
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return result; |
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} |
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std::vector<cv::Ptr<cv::dnn::Layer> > List_to_vector_Ptr_Layer(JNIEnv* env, jobject list) |
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{ |
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static jclass juArrayList = ARRAYLIST(env); |
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jmethodID m_size = LIST_SIZE(env, juArrayList); |
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jmethodID m_get = LIST_GET(env, juArrayList); |
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static jclass jLayerClass = LAYER(env); |
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jint len = env->CallIntMethod(list, m_size); |
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std::vector< cv::Ptr<cv::dnn::Layer> > result; |
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result.reserve(len); |
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for (jint i=0; i<len; i++) |
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{ |
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jobject element = static_cast<jobject>(env->CallObjectMethod(list, m_get, i)); |
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cv::Ptr<cv::dnn::Layer>* layer_ptr = (cv::Ptr<cv::dnn::Layer>*) GETNATIVEOBJ(env, jLayerClass, element) ; |
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cv::Ptr<cv::dnn::Layer> layer = *(layer_ptr); |
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result.push_back(layer); |
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env->DeleteLocalRef(element); |
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} |
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return result; |
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} |
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html
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// Author: abratchik
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#ifndef DNN_CONVERTERS_HPP |
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#define DNN_CONVERTERS_HPP |
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#include <jni.h> |
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#include "opencv2/java.hpp" |
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#include "opencv2/core.hpp" |
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#include "opencv2/dnn/dnn.hpp" |
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#define LAYER(ENV) static_cast<jclass>(ENV->NewGlobalRef(ENV->FindClass("org/opencv/dnn/Layer"))) |
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#define LAYER_CONSTRUCTOR(ENV, CLS) ENV->GetMethodID(CLS, "<init>", "(J)V") |
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using namespace cv::dnn; |
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void Mat_to_MatShape(cv::Mat& mat, MatShape& matshape); |
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void MatShape_to_Mat(MatShape& matshape, cv::Mat& mat); |
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void Mat_to_vector_size_t(cv::Mat& mat, std::vector<size_t>& v_size_t); |
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void vector_size_t_to_Mat(std::vector<size_t>& v_size_t, cv::Mat& mat); |
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std::vector<MatShape> List_to_vector_MatShape(JNIEnv* env, jobject list); |
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jobject vector_Ptr_Layer_to_List(JNIEnv* env, std::vector<cv::Ptr<cv::dnn::Layer> >& vs); |
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std::vector<cv::Ptr<cv::dnn::Layer> > List_to_vector_Ptr_Layer(JNIEnv* env, jobject list); |
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#endif /* DNN_CONVERTERS_HPP */ |
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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.Importer; |
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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 = new Net(); |
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if(net.empty()) { |
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Importer importer = Dnn.createTensorflowImporter(modelFileName); |
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importer.populateNet(net); |
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} |
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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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