Merge pull request #25709 from dkurt:wrap_addLayer

* Wrap dnn addLayer
* Add typing stubs

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()