third_party/opencv
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

add java wrappers to dnn module

Browse Source
This commit is contained in:
abratchik
2017-06-27 10:52:44 +04:00
parent e5aa213554
commit 8f7181429f
11 changed files with 347 additions and 32 deletions
Download Patch File Download Diff File Expand all files Collapse all files
modules/dnn/misc/java/filelist_common
+1
View File
@@ -0,0 +1 @@
misc/java/src/cpp/dnn_converters.hpp
modules/dnn/misc/java/gen_dict.json
+55
View File
@@ -0,0 +1,55 @@
{
"type_dict": {
"MatShape": {
"j_type": "MatOfInt",
"jn_type": "long",
"jni_type": "jlong",
"jni_var": "MatShape %(n)s",
"suffix": "J",
"v_type": "Mat",
"j_import": "org.opencv.core.MatOfInt"
},
"vector_MatShape": {
"j_type": "List<MatOfInt>",
"jn_type": "List<MatOfInt>",
"jni_type": "jobject",
"jni_var": "std::vector< MatShape > %(n)s",
"suffix": "Ljava_util_List",
"v_type": "vector_MatShape",
"j_import": "org.opencv.core.MatOfInt"
},
"vector_size_t": {
"j_type": "MatOfDouble",
"jn_type": "long",
"jni_type": "jlong",
"jni_var": "std::vector<size_t> %(n)s",
"suffix": "J",
"v_type": "Mat",
"j_import": "org.opencv.core.MatOfDouble"
},
"vector_Ptr_Layer": {
"j_type": "List<Layer>",
"jn_type": "List<Layer>",
"jni_type": "jobject",
"jni_var": "std::vector< Ptr<cv::dnn::Layer> > %(n)s",
"suffix": "Ljava_util_List",
"v_type": "vector_Layer",
"j_import": "org.opencv.dnn.Layer"
},
"LayerId": {
"j_type": "DictValue",
"jn_type": "long",
"jn_args": [
[
"__int64",
".getNativeObjAddr()"
]
],
"jni_name": "(*(cv::dnn::DictValue*)%(n)s_nativeObj)",
"jni_type": "jlong",
"suffix": "J",
"j_import": "org.opencv.dnn.DictValue"
}
}
}
modules/dnn/misc/java/src/cpp/dnn_converters.cpp
+94
View File
@@ -0,0 +1,94 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
// Author: abratchik
#include "dnn_converters.hpp"
void Mat_to_MatShape(cv::Mat& mat, MatShape& matshape)
{
matshape.clear();
CHECK_MAT(mat.type()==CV_32SC1 && mat.cols==1);
matshape = (MatShape) mat;
}
void MatShape_to_Mat(MatShape& matshape, cv::Mat& mat)
{
mat = cv::Mat(matshape, true);
}
void Mat_to_vector_size_t(cv::Mat& mat, std::vector<size_t>& v_size_t)
{
v_size_t.clear();
CHECK_MAT(mat.type()==CV_32SC1 && mat.cols==1);
v_size_t = (std::vector<size_t>) mat;
}
void vector_size_t_to_Mat(std::vector<size_t>& v_size_t, cv::Mat& mat)
{
mat = cv::Mat(v_size_t, true);
}
std::vector<MatShape> List_to_vector_MatShape(JNIEnv* env, jobject list)
{
static jclass juArrayList = ARRAYLIST(env);
jmethodID m_size = LIST_SIZE(env, juArrayList);
jmethodID m_get = LIST_GET(env, juArrayList);
static jclass jMatOfInt = MATOFINT(env);
jint len = env->CallIntMethod(list, m_size);
std::vector<MatShape> result;
result.reserve(len);
for (jint i=0; i<len; i++)
{
jobject element = static_cast<jobject>(env->CallObjectMethod(list, m_get, i));
cv::Mat& mat = *((cv::Mat*) GETNATIVEOBJ(env, jMatOfInt, element) );
MatShape matshape = (MatShape) mat;
result.push_back(matshape);
env->DeleteLocalRef(element);
}
return result;
}
jobject vector_Ptr_Layer_to_List(JNIEnv* env, std::vector<cv::Ptr<cv::dnn::Layer> >& vs)
{
static jclass juArrayList = ARRAYLIST(env);
static jmethodID m_create = CONSTRUCTOR(env, juArrayList);
jmethodID m_add = LIST_ADD(env, juArrayList);
static jclass jLayerClass = LAYER(env);
static jmethodID m_create_layer = LAYER_CONSTRUCTOR(env, jLayerClass);
jobject result = env->NewObject(juArrayList, m_create, vs.size());
for (std::vector< cv::Ptr<cv::dnn::Layer> >::iterator it = vs.begin(); it != vs.end(); ++it) {
jobject element = env->NewObject(jLayerClass, m_create_layer, (*it).get());
env->CallBooleanMethod(result, m_add, element);
env->DeleteLocalRef(element);
}
return result;
}
std::vector<cv::Ptr<cv::dnn::Layer> > List_to_vector_Ptr_Layer(JNIEnv* env, jobject list)
{
static jclass juArrayList = ARRAYLIST(env);
jmethodID m_size = LIST_SIZE(env, juArrayList);
jmethodID m_get = LIST_GET(env, juArrayList);
static jclass jLayerClass = LAYER(env);
jint len = env->CallIntMethod(list, m_size);
std::vector< cv::Ptr<cv::dnn::Layer> > result;
result.reserve(len);
for (jint i=0; i<len; i++)
{
jobject element = static_cast<jobject>(env->CallObjectMethod(list, m_get, i));
cv::Ptr<cv::dnn::Layer>* layer_ptr = (cv::Ptr<cv::dnn::Layer>*) GETNATIVEOBJ(env, jLayerClass, element) ;
cv::Ptr<cv::dnn::Layer> layer = *(layer_ptr);
result.push_back(layer);
env->DeleteLocalRef(element);
}
return result;
}
modules/dnn/misc/java/src/cpp/dnn_converters.hpp
+36
View File
@@ -0,0 +1,36 @@
// This file is part of OpenCV project.
// It is subject to the license terms in the LICENSE file found in the top-level directory
// of this distribution and at http://opencv.org/license.html
// Author: abratchik
#ifndef DNN_CONVERTERS_HPP
#define DNN_CONVERTERS_HPP
#include <jni.h>
#include "opencv2/java.hpp"
#include "opencv2/core.hpp"
#include "opencv2/dnn/dnn.hpp"
#define LAYER(ENV) static_cast<jclass>(ENV->NewGlobalRef(ENV->FindClass("org/opencv/dnn/Layer")))
#define LAYER_CONSTRUCTOR(ENV, CLS) ENV->GetMethodID(CLS, "<init>", "(J)V")
using namespace cv::dnn;
void Mat_to_MatShape(cv::Mat& mat, MatShape& matshape);
void MatShape_to_Mat(MatShape& matshape, cv::Mat& mat);
void Mat_to_vector_size_t(cv::Mat& mat, std::vector<size_t>& v_size_t);
void vector_size_t_to_Mat(std::vector<size_t>& v_size_t, cv::Mat& mat);
std::vector<MatShape> List_to_vector_MatShape(JNIEnv* env, jobject list);
jobject vector_Ptr_Layer_to_List(JNIEnv* env, std::vector<cv::Ptr<cv::dnn::Layer> >& vs);
std::vector<cv::Ptr<cv::dnn::Layer> > List_to_vector_Ptr_Layer(JNIEnv* env, jobject list);
#endif /* DNN_CONVERTERS_HPP */
modules/dnn/misc/java/test/DnnTensorFlowTest.java
+113
View File
@@ -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);
}
}