Merge pull request #25709 from dkurt:wrap_addLayer

* Wrap dnn addLayer
* Add typing stubs

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -533,7 +533,7 @@ CV__DNN_INLINE_NS_BEGIN
          *  @param params parameters which will be used to initialize the creating layer.
          *  @returns unique identifier of created layer, or -1 if a failure will happen.
          */
-        int addLayer(const String &name, const String &type, const int &dtype, LayerParams &params);
+        CV_WRAP int addLayer(const String &name, const String &type, const int &dtype, LayerParams &params);
 
         /** @overload Datatype of output blobs set to default CV_32F */
         int addLayer(const String &name, const String &type, LayerParams &params);
@@ -541,7 +541,7 @@ CV__DNN_INLINE_NS_BEGIN
         /** @brief Adds new layer and connects its first input to the first output of previously added layer.
          *  @see addLayer()
          */
-        int addLayerToPrev(const String &name, const String &type, const int &dtype, LayerParams &params);
+        CV_WRAP int addLayerToPrev(const String &name, const String &type, const int &dtype, LayerParams &params);
 
         /** @overload */
         int addLayerToPrev(const String &name, const String &type, LayerParams &params);

modules/dnn/misc/python/pyopencv_dnn.hpp

@@ -71,6 +71,22 @@ PyObject* pyopencv_from(const dnn::LayerParams& lp)
     return dict;
 }
 
+template<>
+bool pyopencv_to(PyObject *o, dnn::LayerParams &lp, const ArgInfo& info)
+{
+    CV_Assert(PyDict_Check(o));
+    PyObject *key, *value;
+    Py_ssize_t pos = 0;
+    std::string keyName;
+    while (PyDict_Next(o, &pos, &key, &value)) {
+        getUnicodeString(key, keyName);
+        dnn::DictValue dv;
+        pyopencv_to(value, dv, info);
+        lp.set(keyName, dv);
+    }
+    return true;
+}
+
 template<>
 PyObject* pyopencv_from(const std::vector<dnn::Target> &t)
 {

modules/dnn/misc/python/test/test_dnn.py

@@ -480,5 +480,21 @@ class dnn_test(NewOpenCVTests):
         params.scalefactor = 2.0
         self.assertEqual(params.scalefactor, (2.0, 0.0, 0.0, 0.0))
 
+    def test_net_builder(self):
+        net = cv.dnn.Net()
+        params = {
+            "kernel_w": 3,
+            "kernel_h": 3,
+            "stride_w": 3,
+            "stride_h": 3,
+            "pool": "max",
+        }
+        net.addLayerToPrev("pool", "Pooling", cv.CV_32F, params)
+
+        inp = np.random.standard_normal([1, 2, 9, 12]).astype(np.float32)
+        net.setInput(inp)
+        out = net.forward()
+        self.assertEqual(out.shape, (1, 2, 3, 4))
+
 if __name__ == '__main__':
     NewOpenCVTests.bootstrap()

modules/python/src2/typing_stubs_generation/predefined_types.py

@@ -194,6 +194,13 @@ _PREDEFINED_TYPES = (
         export_name="ExtractMetaCallback"
     ),
     AliasTypeNode.class_("LayerId", "DictValue"),
+    AliasTypeNode.dict_("LayerParams",
+                        key_type=PrimitiveTypeNode.str_(),
+                        value_type=UnionTypeNode("DictValue", items=(
+                            PrimitiveTypeNode.int_(),
+                            PrimitiveTypeNode.float_(),
+                            PrimitiveTypeNode.str_())
+                        )),
     PrimitiveTypeNode.int_("cvflann_flann_distance_t"),
     PrimitiveTypeNode.int_("flann_flann_distance_t"),
     PrimitiveTypeNode.int_("cvflann_flann_algorithm_t"),