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https://github.com/opencv/opencv.git
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Java API: added class pointer ret type support, CV_EXPORTS_AS(x) support for classes, vector<T> as ret type support, randu/randn params type changed to double
This commit is contained in:
Andrey Pavlenko
parent
d0176d69f2
commit
96ca253a00
@ -454,8 +454,8 @@ JNIEXPORT jdoubleArray JNICALL Java_org_opencv_core_Core_n_1getTextSize
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# { class : { func : {arg_name : ctype} } }
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func_arg_fix = {
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'' : {
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'randu' : { 'low' : 'Scalar', 'high' : 'Scalar', },
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'randn' : { 'mean' : 'Scalar', 'stddev' : 'Scalar', },
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'randu' : { 'low' : 'double', 'high' : 'double', },
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'randn' : { 'mean' : 'double', 'stddev' : 'double', },
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'inRange' : { 'lowerb' : 'Scalar', 'upperb' : 'Scalar', },
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'goodFeaturesToTrack' : { 'corners' : 'vector_Point' },
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}, # '', i.e. empty class
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@ -486,6 +486,7 @@ class ClassInfo(object):
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self.private_consts = []
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self.imports = set()
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self.props= []
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self.jname = self.name
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for m in decl[2]:
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if m.startswith("="):
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self.jname = m[1:]
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@ -569,6 +570,7 @@ class JavaWrapperGenerator(object):
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self.skipped_func_list = []
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def add_class_code_stream(self, class_name):
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jname = self.classes[class_name].jname
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self.java_code[class_name] = { "j_code" : StringIO(), "jn_code" : StringIO(), }
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if class_name != self.Module:
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self.java_code[class_name]["j_code"].write("""
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@ -581,12 +583,12 @@ $imports
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// C++: class %(c)s
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//javadoc: %(c)s
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public class %(c)s {
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public class %(jc)s {
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protected final long nativeObj;
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protected %(c)s(long addr) { nativeObj = addr; }
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protected %(jc)s(long addr) { nativeObj = addr; }
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""" % { 'm' : self.module, 'c' : class_name } )
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""" % { 'm' : self.module, 'c' : class_name, 'jc' : jname } )
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else: # class_name == self.Module
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self.java_code[class_name]["j_code"].write("""
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@ -597,8 +599,8 @@ package org.opencv.%(m)s;
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$imports
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public class %(c)s {
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""" % { 'm' : self.module, 'c' : class_name } )
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public class %(jc)s {
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""" % { 'm' : self.module, 'jc' : jname } )
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self.java_code[class_name]["jn_code"].write("""
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//
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@ -613,37 +615,43 @@ public class %(c)s {
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classinfo = ClassInfo(decl)
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if classinfo.name in class_ignore_list:
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return
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if classinfo.name in self.classes:
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name = classinfo.name
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if name in self.classes:
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print "Generator error: class %s (%s) is duplicated" % \
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(classinfo.name, classinfo.cname)
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(name, classinfo.cname)
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return
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self.classes[classinfo.name] = classinfo
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if classinfo.name in type_dict:
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print "Duplicated class: " + classinfo.name
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self.classes[name] = classinfo
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if name in type_dict:
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print "Duplicated class: " + name
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return
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type_dict[classinfo.name] = \
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{ "j_type" : classinfo.name,
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type_dict[name] = \
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{ "j_type" : classinfo.jname,
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"jn_type" : "long", "jn_args" : (("__int64", ".nativeObj"),),
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"jni_name" : "(*("+classinfo.name+"*)%(n)s_nativeObj)", "jni_type" : "jlong",
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"jni_name" : "(*("+name+"*)%(n)s_nativeObj)", "jni_type" : "jlong",
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"suffix" : "J" }
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type_dict[name+'*'] = \
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{ "j_type" : classinfo.jname,
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"jn_type" : "long", "jn_args" : (("__int64", ".nativeObj"),),
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"jni_name" : "("+name+"*)%(n)s_nativeObj", "jni_type" : "jlong",
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"suffix" : "J" }
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# missing_consts { Module : { public : [[name, val],...], private : [[]...] } }
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if classinfo.name in missing_consts:
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if 'private' in missing_consts[classinfo.name]:
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for (name, val) in missing_consts[classinfo.name]['private']:
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classinfo.private_consts.append( ConstInfo(name, name, val, True) )
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if 'public' in missing_consts[classinfo.name]:
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for (name, val) in missing_consts[classinfo.name]['public']:
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classinfo.consts.append( ConstInfo(name, name, val, True) )
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if name in missing_consts:
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if 'private' in missing_consts[name]:
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for (n, val) in missing_consts[name]['private']:
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classinfo.private_consts.append( ConstInfo(n, n, val, True) )
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if 'public' in missing_consts[name]:
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for (n, val) in missing_consts[name]['public']:
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classinfo.consts.append( ConstInfo(n, n, val, True) )
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# class props
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for p in decl[3]:
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if "vector" not in p[0]:
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classinfo.props.append( ClassPropInfo(p) )
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else:
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print "Skipped property: [%s]" % classinfo.name, p
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print "Skipped property: [%s]" % name, p
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self.add_class_code_stream(classinfo.name)
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self.add_class_code_stream(name)
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def add_const(self, decl): # [ "const cname", val, [], [] ]
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@ -754,17 +762,16 @@ extern "C" {
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# generate code for the classes
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for name in self.classes.keys():
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if name == "Mat":
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continue
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self.gen_class(name)
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# saving code streams
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for cls in self.java_code.keys():
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# saving code streams
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imports = "\n".join([ "import %s;" % c for c in \
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sorted(self.classes[cls].imports) if not c.startswith('org.opencv.'+self.module) ])
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##imports = "import org.opencv.core.*;\nimport org.opencv.Converters;\n"
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self.java_code[cls]["j_code"].write("\n\n%s\n}\n" % self.java_code[cls]["jn_code"].getvalue())
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java_code = self.java_code[cls]["j_code"].getvalue()
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sorted(self.classes[name].imports) if not c.startswith('org.opencv.'+self.module) ])
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self.java_code[name]["j_code"].write("\n\n%s\n}\n" % self.java_code[name]["jn_code"].getvalue())
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java_code = self.java_code[name]["j_code"].getvalue()
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java_code = Template(java_code).substitute(imports = imports)
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self.save("%s/%s+%s.java" % (output_path, module, cls), java_code)
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self.save("%s/%s+%s.java" % (output_path, module, self.classes[name].jname), java_code)
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self.cpp_code.write( '\n} // extern "C"\n' )
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self.save(output_path+"/"+module+".cpp", self.cpp_code.getvalue())
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@ -944,20 +951,30 @@ extern "C" {
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# e.g.
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# public static void add( Mat src1, Mat src2, Mat dst, Mat mask, int dtype )
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# { n_add( src1.nativeObj, src2.nativeObj, dst.nativeObj, mask.nativeObj, dtype ); }
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ret_val = type_dict[fi.ctype]["j_type"] + " retVal = "
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ret_type = fi.ctype
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if fi.ctype.endswith('*'):
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ret_type = ret_type[:-1]
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ret_val = type_dict[ret_type]["j_type"] + " retVal = "
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tail = ""
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ret = "return retVal;"
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if fi.ctype == "void":
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if ret_type.startswith('vector'):
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ret_val = "Mat retValMat = new Mat("
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tail = ")"
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j_type = type_dict[ret_type]["j_type"]
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j_prologue.append( j_type + ' retVal = new Array' + j_type+'();')
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self.classes[fi.classname or self.Module].imports.add('java.util.ArrayList')
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j_epilogue.append('Converters.Mat_to_' + ret_type + '(retValMat, retVal);')
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elif ret_type == "void":
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ret_val = ""
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ret = "return;"
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elif fi.ctype == "": # c-tor
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elif ret_type == "": # c-tor
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ret_val = "nativeObj = "
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ret = "return;"
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elif fi.ctype in self.classes: # wrapped class
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ret_val = type_dict[fi.ctype]["j_type"] + " retVal = new " + self.classes[fi.ctype].jname + "("
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elif ret_type in self.classes: # wrapped class
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ret_val = type_dict[ret_type]["j_type"] + " retVal = new " + self.classes[ret_type].jname + "("
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tail = ")"
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elif "jn_type" not in type_dict[fi.ctype]:
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ret_val = type_dict[fi.ctype]["j_type"] + " retVal = new " + type_dict[fi.ctype]["j_type"] + "("
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elif "jn_type" not in type_dict[ret_type]:
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ret_val = type_dict[fi.ctype]["j_type"] + " retVal = new " + type_dict[ret_type]["j_type"] + "("
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tail = ")"
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static = "static"
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@ -998,11 +1015,15 @@ extern "C" {
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default = "return;"
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elif not fi.ctype: # c-tor
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ret = "return (jlong) _retval_;"
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elif fi.ctype.startswith('vector'): # c-tor
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ret = "return (jlong) _retval_;"
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elif fi.ctype == "string":
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ret = "return env->NewStringUTF(_retval_.c_str());"
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default = 'return env->NewStringUTF("");'
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elif fi.ctype in self.classes: # wrapped class:
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ret = "return (jlong) new %s(_retval_);" % fi.ctype
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elif ret_type in self.classes: # pointer to wrapped class:
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ret = "return (jlong) _retval_;"
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elif type_dict[fi.ctype]["jni_type"] == "jdoubleArray":
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ret = "return _da_retval_;"
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@ -1018,6 +1039,10 @@ extern "C" {
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retval = fi.ctype + " _retval_ = "
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if fi.ctype == "void":
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retval = ""
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elif fi.ctype.startswith('vector'):
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retval = type_dict[fi.ctype]['jni_var'] % {"n" : '_ret_val_vector_'} + " = "
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c_epilogue.append("Mat* _retval_ = new Mat();")
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c_epilogue.append(fi.ctype+"_to_Mat(_ret_val_vector_, *_retval_);")
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if fi.classname:
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if not fi.ctype: # c-tor
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retval = fi.classname + "* _retval_ = "
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@ -1096,8 +1121,6 @@ JNIEXPORT $rtype JNICALL Java_org_opencv_${module}_${clazz}_$fname
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def gen_class(self, name):
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# generate code for the class
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if name == "Mat":
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return
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ci = self.classes[name]
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# constants
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if ci.private_consts:
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@ -1116,6 +1139,9 @@ JNIEXPORT $rtype JNICALL Java_org_opencv_${module}_${clazz}_$fname
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for n, ffi in fflist:
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if ffi.isconstructor:
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for fi in ffi.funcs:
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fi.jname = ci.jname
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fi.jn_name = "n_" + fi.jname
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fi.jni_name= re.sub("_", "_1", fi.jn_name)
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self.gen_func(fi, len(ffi.funcs)>1)
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# other methods
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for n, ffi in fflist:
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@ -33,7 +33,7 @@ public:
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#if 0
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CV_WRAP virtual bool isMaskSupported() const;
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CV_WRAP virtual void add( const vector<Mat>& descriptors );
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//CV_WRAP const vector<Mat>& getTrainDescriptors() const;
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CV_WRAP const vector<Mat>& getTrainDescriptors() const;
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CV_WRAP virtual void clear();
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CV_WRAP virtual bool empty() const;
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CV_WRAP virtual void train();
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