Fixed Algorithm.save and other methods work in Java

pull/8524/head
Maksim Shabunin 8 years ago
parent bd786f3bea
commit 8b455e8bb3
  1. 4
      modules/java/generator/gen_java.py
  2. 42
      modules/ml/misc/java/test/MLTest.java

@ -1005,7 +1005,7 @@ class JavaWrapperGenerator(object):
type_dict["Ptr_"+name] = \
{ "j_type" : classinfo.jname,
"jn_type" : "long", "jn_args" : (("__int64", ".nativeObj"),),
"jni_name" : "Ptr<"+classinfo.fullName(isCPP=True)+">(("+classinfo.fullName(isCPP=True)+"*)%(n)s_nativeObj)", "jni_type" : "jlong",
"jni_name" : "*((Ptr<"+classinfo.fullName(isCPP=True)+">*)%(n)s_nativeObj)", "jni_type" : "jlong",
"suffix" : "J" }
logging.info('ok: class %s, name: %s, base: %s', classinfo, name, classinfo.base)
@ -1575,7 +1575,7 @@ JNIEXPORT void JNICALL Java_org_opencv_%(module)s_%(j_cls)s_delete
# if parents are smart (we hope) then children are!
# if not we believe the class is smart if it has "create" method
ci.smart = False
if ci.base:
if ci.base or ci.name == 'Algorithm':
ci.smart = True
else:
for fi in ci.methods:

@ -0,0 +1,42 @@
package org.opencv.test.ml;
import org.opencv.ml.Ml;
import org.opencv.ml.SVM;
import org.opencv.core.Mat;
import org.opencv.core.MatOfFloat;
import org.opencv.core.MatOfInt;
import org.opencv.core.CvType;
import org.opencv.test.OpenCVTestCase;
import org.opencv.test.OpenCVTestRunner;
public class MLTest extends OpenCVTestCase {
public void testSaveLoad() {
Mat samples = new MatOfFloat(new float[] {
5.1f, 3.5f, 1.4f, 0.2f,
4.9f, 3.0f, 1.4f, 0.2f,
4.7f, 3.2f, 1.3f, 0.2f,
4.6f, 3.1f, 1.5f, 0.2f,
5.0f, 3.6f, 1.4f, 0.2f,
7.0f, 3.2f, 4.7f, 1.4f,
6.4f, 3.2f, 4.5f, 1.5f,
6.9f, 3.1f, 4.9f, 1.5f,
5.5f, 2.3f, 4.0f, 1.3f,
6.5f, 2.8f, 4.6f, 1.5f
}).reshape(1, 10);
Mat responses = new MatOfInt(new int[] {
0, 0, 0, 0, 0, 1, 1, 1, 1, 1
}).reshape(1, 10);
SVM saved = SVM.create();
assertFalse(saved.isTrained());
saved.train(samples, Ml.ROW_SAMPLE, responses);
assertTrue(saved.isTrained());
String filename = OpenCVTestRunner.getTempFileName("yml");
saved.save(filename);
SVM loaded = SVM.load(filename);
assertTrue(saved.isTrained());
}
}
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