1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
|
#ifdef HAVE_OPENCV_DNN
typedef dnn::DictValue LayerId;
typedef std::vector<dnn::MatShape> vector_MatShape;
typedef std::vector<std::vector<dnn::MatShape> > vector_vector_MatShape;
template<>
bool pyopencv_to(PyObject *o, dnn::DictValue &dv, const ArgInfo& info)
{
CV_UNUSED(info);
if (!o || o == Py_None)
return true; //Current state will be used
else if (PyLong_Check(o))
{
dv = dnn::DictValue((int64)PyLong_AsLongLong(o));
return true;
}
else if (PyInt_Check(o))
{
dv = dnn::DictValue((int64)PyInt_AS_LONG(o));
return true;
}
else if (PyFloat_Check(o))
{
dv = dnn::DictValue(PyFloat_AsDouble(o));
return true;
}
else
{
std::string str;
if (getUnicodeString(o, str))
{
dv = dnn::DictValue(str);
return true;
}
}
return false;
}
template<typename T>
PyObject* pyopencv_from(const dnn::DictValue &dv)
{
if (dv.size() > 1)
{
std::vector<T> vec(dv.size());
for (int i = 0; i < dv.size(); ++i)
vec[i] = dv.get<T>(i);
return pyopencv_from_generic_vec(vec);
}
else
return pyopencv_from(dv.get<T>());
}
template<>
PyObject* pyopencv_from(const dnn::DictValue &dv)
{
if (dv.isInt()) return pyopencv_from<int>(dv);
if (dv.isReal()) return pyopencv_from<float>(dv);
if (dv.isString()) return pyopencv_from<String>(dv);
CV_Error(Error::StsNotImplemented, "Unknown value type");
return NULL;
}
template<>
PyObject* pyopencv_from(const dnn::LayerParams& lp)
{
PyObject* dict = PyDict_New();
for (std::map<String, dnn::DictValue>::const_iterator it = lp.begin(); it != lp.end(); ++it)
{
CV_Assert(!PyDict_SetItemString(dict, it->first.c_str(), pyopencv_from(it->second)));
}
return dict;
}
template<>
PyObject* pyopencv_from(const std::vector<dnn::Target> &t)
{
return pyopencv_from(std::vector<int>(t.begin(), t.end()));
}
class pycvLayer CV_FINAL : public dnn::Layer
{
public:
pycvLayer(const dnn::LayerParams ¶ms, PyObject* pyLayer) : Layer(params)
{
PyGILState_STATE gstate;
gstate = PyGILState_Ensure();
PyObject* args = PyTuple_New(2);
CV_Assert(!PyTuple_SetItem(args, 0, pyopencv_from(params)));
CV_Assert(!PyTuple_SetItem(args, 1, pyopencv_from(params.blobs)));
o = PyObject_CallObject(pyLayer, args);
Py_DECREF(args);
PyGILState_Release(gstate);
if (!o)
CV_Error(Error::StsError, "Failed to create an instance of custom layer");
}
static void registerLayer(const std::string& type, PyObject* o)
{
std::map<std::string, std::vector<PyObject*> >::iterator it = pyLayers.find(type);
if (it != pyLayers.end())
it->second.push_back(o);
else
pyLayers[type] = std::vector<PyObject*>(1, o);
}
static void unregisterLayer(const std::string& type)
{
std::map<std::string, std::vector<PyObject*> >::iterator it = pyLayers.find(type);
if (it != pyLayers.end())
{
if (it->second.size() > 1)
it->second.pop_back();
else
pyLayers.erase(it);
}
}
static Ptr<dnn::Layer> create(dnn::LayerParams ¶ms)
{
std::map<std::string, std::vector<PyObject*> >::iterator it = pyLayers.find(params.type);
if (it == pyLayers.end())
CV_Error(Error::StsNotImplemented, "Layer with a type \"" + params.type +
"\" is not implemented");
CV_Assert(!it->second.empty());
return Ptr<dnn::Layer>(new pycvLayer(params, it->second.back()));
}
virtual bool getMemoryShapes(const std::vector<std::vector<int> > &inputs,
const int,
std::vector<std::vector<int> > &outputs,
std::vector<std::vector<int> > &) const CV_OVERRIDE
{
PyGILState_STATE gstate;
gstate = PyGILState_Ensure();
PyObject* args = PyList_New(inputs.size());
for(size_t i = 0; i < inputs.size(); ++i)
PyList_SetItem(args, i, pyopencv_from_generic_vec(inputs[i]));
PyObject* res = PyObject_CallMethodObjArgs(o, PyString_FromString("getMemoryShapes"), args, NULL);
Py_DECREF(args);
PyGILState_Release(gstate);
if (!res)
CV_Error(Error::StsNotImplemented, "Failed to call \"getMemoryShapes\" method");
CV_Assert(pyopencv_to_generic_vec(res, outputs, ArgInfo("", 0)));
return false;
}
virtual void forward(InputArrayOfArrays inputs_arr, OutputArrayOfArrays outputs_arr, OutputArrayOfArrays) CV_OVERRIDE
{
PyGILState_STATE gstate;
gstate = PyGILState_Ensure();
std::vector<Mat> inputs, outputs;
inputs_arr.getMatVector(inputs);
outputs_arr.getMatVector(outputs);
PyObject* args = pyopencv_from(inputs);
PyObject* res = PyObject_CallMethodObjArgs(o, PyString_FromString("forward"), args, NULL);
Py_DECREF(args);
if (!res)
CV_Error(Error::StsNotImplemented, "Failed to call \"forward\" method");
std::vector<Mat> pyOutputs;
CV_Assert(pyopencv_to(res, pyOutputs, ArgInfo("", 0)));
Py_DECREF(res);
PyGILState_Release(gstate);
CV_Assert(pyOutputs.size() == outputs.size());
for (size_t i = 0; i < outputs.size(); ++i)
{
CV_Assert(pyOutputs[i].size == outputs[i].size);
CV_Assert(pyOutputs[i].type() == outputs[i].type());
pyOutputs[i].copyTo(outputs[i]);
}
}
private:
// Map layers types to python classes.
static std::map<std::string, std::vector<PyObject*> > pyLayers;
PyObject* o; // Instance of implemented python layer.
};
std::map<std::string, std::vector<PyObject*> > pycvLayer::pyLayers;
static PyObject *pyopencv_cv_dnn_registerLayer(PyObject*, PyObject *args, PyObject *kw)
{
const char *keywords[] = { "type", "class", NULL };
char* layerType;
PyObject *classInstance;
if (!PyArg_ParseTupleAndKeywords(args, kw, "sO", (char**)keywords, &layerType, &classInstance))
return NULL;
if (!PyCallable_Check(classInstance)) {
PyErr_SetString(PyExc_TypeError, "class must be callable");
return NULL;
}
pycvLayer::registerLayer(layerType, classInstance);
dnn::LayerFactory::registerLayer(layerType, pycvLayer::create);
Py_RETURN_NONE;
}
static PyObject *pyopencv_cv_dnn_unregisterLayer(PyObject*, PyObject *args, PyObject *kw)
{
const char *keywords[] = { "type", NULL };
char* layerType;
if (!PyArg_ParseTupleAndKeywords(args, kw, "s", (char**)keywords, &layerType))
return NULL;
pycvLayer::unregisterLayer(layerType);
dnn::LayerFactory::unregisterLayer(layerType);
Py_RETURN_NONE;
}
#endif // HAVE_OPENCV_DNN
|
