Add missing OpenCV 5 geometry APIs; fix stale readNet doc

src/OpenCvSharp/Modules/dnn/Cv2.Dnn.cs

@@ -62,23 +62,20 @@ public static partial class Dnn
 
         /// <summary>
         /// Read deep learning network represented in one of the supported formats.
-        /// 
-        /// This function automatically detects an origin framework of trained model 
-        /// and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow,
+        ///
+        /// This function automatically detects an origin framework of trained model
+        /// and calls an appropriate function such @ref readNetFromTensorflow, @ref readNetFromONNX,
+        /// or @ref readNetFromModelOptimizer. The Caffe, Darknet and Torch parsers were removed in OpenCV 5.
         /// </summary>
         /// <param name="model">Binary file contains trained weights. The following file
         /// *                  extensions are expected for models from different frameworks:
-        /// *                  * `*.caffemodel` (Caffe, http://caffe.berkeleyvision.org/)
         /// *                  * `*.pb` (TensorFlow, https://www.tensorflow.org/)
-        /// *                  * `*.t7` | `*.net` (Torch, http://torch.ch/)
-        /// *                  * `*.weights` (Darknet, https://pjreddie.com/darknet/)
-        /// *                  * `*.bin` (DLDT, https://software.intel.com/openvino-toolkit)</param>
+        /// *                  * `*.onnx` (ONNX, https://onnx.ai/)
+        /// *                  * `*.bin` (OpenVINO, https://software.intel.com/openvino-toolkit)</param>
         /// <param name="config">Text file contains network configuration. It could be a
         /// *                   file with the following extensions:
-        /// *                  * `*.prototxt` (Caffe, http://caffe.berkeleyvision.org/)
         /// *                  * `*.pbtxt` (TensorFlow, https://www.tensorflow.org/)
-        /// *                  * `*.cfg` (Darknet, https://pjreddie.com/darknet/)
-        /// *                  * `*.xml` (DLDT, https://software.intel.com/openvino-toolkit)</param>
+        /// *                  * `*.xml` (OpenVINO, https://software.intel.com/openvino-toolkit)</param>
         /// <param name="framework">Explicit framework name tag to determine a format.</param>
         /// <returns></returns>
         /// <param name="engine">DNN engine to use. <see cref="EngineType.Auto"/> tries the new engine first and falls back to the classic one.</param>

src/OpenCvSharp/Modules/dnn/Net.cs

@@ -146,23 +146,20 @@ private void InitSafeHandle(IntPtr p, bool ownsHandle = true)
 
     /// <summary>
     /// Read deep learning network represented in one of the supported formats.
-    /// 
-    /// This function automatically detects an origin framework of trained model 
-    /// and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow,
+    ///
+    /// This function automatically detects an origin framework of trained model
+    /// and calls an appropriate function such @ref readNetFromTensorflow, @ref readNetFromONNX,
+    /// or @ref readNetFromModelOptimizer. The Caffe, Darknet and Torch parsers were removed in OpenCV 5.
     /// </summary>
     /// <param name="model">Binary file contains trained weights. The following file
     /// *                  extensions are expected for models from different frameworks:
-    /// *                  * `*.caffemodel` (Caffe, http://caffe.berkeleyvision.org/)
     /// *                  * `*.pb` (TensorFlow, https://www.tensorflow.org/)
-    /// *                  * `*.t7` | `*.net` (Torch, http://torch.ch/)
-    /// *                  * `*.weights` (Darknet, https://pjreddie.com/darknet/)
-    /// *                  * `*.bin` (DLDT, https://software.intel.com/openvino-toolkit)</param>
+    /// *                  * `*.onnx` (ONNX, https://onnx.ai/)
+    /// *                  * `*.bin` (OpenVINO, https://software.intel.com/openvino-toolkit)</param>
     /// <param name="config">Text file contains network configuration. It could be a
     /// *                   file with the following extensions:
-    /// *                  * `*.prototxt` (Caffe, http://caffe.berkeleyvision.org/)
     /// *                  * `*.pbtxt` (TensorFlow, https://www.tensorflow.org/)
-    /// *                  * `*.cfg` (Darknet, https://pjreddie.com/darknet/)
-    /// *                  * `*.xml` (DLDT, https://software.intel.com/openvino-toolkit)</param>
+    /// *                  * `*.xml` (OpenVINO, https://software.intel.com/openvino-toolkit)</param>
     /// <param name="framework">Explicit framework name tag to determine a format.</param>
     /// <returns></returns>
     /// <param name="engine">DNN engine to use. <see cref="EngineType.Auto"/> tries the new engine first and falls back to the classic one.</param>

src/OpenCvSharp/Modules/geometry/Enum/MSTAlgorithm.cs

@@ -0,0 +1,18 @@
+namespace OpenCvSharp;
+
+// ReSharper disable InconsistentNaming
+/// <summary>
+/// Algorithms available for building a Minimum Spanning Tree (MST). See <see cref="Cv2.BuildMST"/>.
+/// </summary>
+public enum MSTAlgorithm
+{
+    /// <summary>
+    /// Prim's algorithm.
+    /// </summary>
+    Prim = 0,
+
+    /// <summary>
+    /// Kruskal's algorithm.
+    /// </summary>
+    Kruskal = 1
+}

src/OpenCvSharp/Modules/geometry/MSTEdge.cs

@@ -0,0 +1,27 @@
+using System.Runtime.InteropServices;
+
+#pragma warning disable CA1051
+
+namespace OpenCvSharp;
+
+/// <summary>
+/// Represents an edge in a graph for Minimum Spanning Tree (MST) computation. See <see cref="Cv2.BuildMST"/>.
+/// </summary>
+[StructLayout(LayoutKind.Sequential)]
+public record struct MSTEdge(int Source, int Target, double Weight)
+{
+    /// <summary>
+    /// Source node index.
+    /// </summary>
+    public int Source = Source;
+
+    /// <summary>
+    /// Target node index.
+    /// </summary>
+    public int Target = Target;
+
+    /// <summary>
+    /// Edge weight.
+    /// </summary>
+    public double Weight = Weight;
+}

src/OpenCvSharp/Modules/imgproc/Moments.cs

@@ -147,7 +147,7 @@ public Moments(IEnumerable<Point2f> array, bool binaryImage = false)
     private void InitializeFromInputArray(InputArray array, bool binaryImage)
     {
         NativeMethods.HandleException(
-            NativeMethods.imgproc_moments(array.Proxy, binaryImage ? 1 : 0, out var m));
+            NativeMethods.geometry_moments(array.Proxy, binaryImage ? 1 : 0, out var m));
         GC.KeepAlive(array.Source);
         Initialize(m.m00, m.m10, m.m01, m.m20, m.m11, m.m02, m.m30, m.m21, m.m12, m.m03);
     }