* Map more functions of the OpenCV Transparent API with UMat and `…

…UMatVector` parameters (issue bytedeco/javacv#518)

CHANGELOG.md

@@ -1,4 +1,5 @@
 
+ * Map more functions of the OpenCV Transparent API with `UMat` and `UMatVector` parameters ([issue bytedeco/javacv#518](https://github.com/bytedeco/javacv/issues/518))
  * Add support for `android-arm` and `android-x86` platforms to TensorFlow presets ([pull #297](https://github.com/bytedeco/javacpp-presets/pull/297))
  * Keep a reference of `tensorflow.SessionOptions` in `AbstractSession` to prevent premature deallocation ([pull #297](https://github.com/bytedeco/javacpp-presets/pull/297))
  * Enable CUDA in `cppbuild.sh` script for TensorFlow ([issue #294](https://github.com/bytedeco/javacpp-presets/issues/294))

opencv/src/main/java/org/bytedeco/javacpp/opencv_bioinspired.java

@@ -1,4 +1,4 @@
-// Targeted by JavaCPP version 1.2: DO NOT EDIT THIS FILE
+// Targeted by JavaCPP version 1.2.5-SNAPSHOT: DO NOT EDIT THIS FILE
 
 package org.bytedeco.javacpp;
 
@@ -506,6 +506,7 @@ the magnocellular way (motion information channel), unit is frames, typical valu
     format (from 8bit to 16bits)
      */
     public native void run(@ByVal Mat inputImage);
+    public native void run(@ByVal UMat inputImage);
 
     /** \brief Method which processes an image in the aim to correct its luminance correct
     backlight problems, enhance details in shadows.
@@ -524,6 +525,7 @@ This method is designed to perform High Dynamic Range image tone mapping (compre
     @param outputToneMappedImage the output 8bit/channel tone mapped image (CV_8U or CV_8UC3 format).
      */
     public native void applyFastToneMapping(@ByVal Mat inputImage, @ByVal Mat outputToneMappedImage);
+    public native void applyFastToneMapping(@ByVal UMat inputImage, @ByVal UMat outputToneMappedImage);
 
     /** \brief Accessor of the details channel of the retina (models foveal vision).
     <p>
@@ -538,11 +540,13 @@ This method is designed to perform High Dynamic Range image tone mapping (compre
     @see getParvoRAW
      */
     public native void getParvo(@ByVal Mat retinaOutput_parvo);
+    public native void getParvo(@ByVal UMat retinaOutput_parvo);
 
     /** \brief Accessor of the details channel of the retina (models foveal vision).
     @see getParvo
      */
     public native void getParvoRAW(@ByVal Mat retinaOutput_parvo);
+    public native void getParvoRAW(@ByVal UMat retinaOutput_parvo);
 
     /** \brief Accessor of the motion channel of the retina (models peripheral vision).
     <p>
@@ -555,11 +559,13 @@ This method is designed to perform High Dynamic Range image tone mapping (compre
     @see getMagnoRAW
      */
     public native void getMagno(@ByVal Mat retinaOutput_magno);
+    public native void getMagno(@ByVal UMat retinaOutput_magno);
 
     /** \brief Accessor of the motion channel of the retina (models peripheral vision).
     @see getMagno
      */
     public native void getMagnoRAW(@ByVal Mat retinaOutput_magno);
+    public native void getMagnoRAW(@ByVal UMat retinaOutput_magno);
 
     /** \overload */
     public native @Const @ByVal Mat getMagnoRAW();
@@ -756,6 +762,7 @@ This algorithm is already implemented in thre Retina class (retina::applyFastTon
     @param outputToneMappedImage the output tone mapped image
     */
     public native void applyFastToneMapping(@ByVal Mat inputImage, @ByVal Mat outputToneMappedImage);
+    public native void applyFastToneMapping(@ByVal UMat inputImage, @ByVal UMat outputToneMappedImage);
 
     /** \brief updates tone mapping behaviors by adjusing the local luminance computation area
     <p>
@@ -965,11 +972,14 @@ This algorithm is already implemented in thre Retina class (retina::applyFastTon
     */
     public native void run(@ByVal Mat inputToSegment, int channelIndex/*=0*/);
     public native void run(@ByVal Mat inputToSegment);
+    public native void run(@ByVal UMat inputToSegment, int channelIndex/*=0*/);
+    public native void run(@ByVal UMat inputToSegment);
 
     /** \brief access function
     @return the last segmentation result: a boolean picture which is resampled between 0 and 255 for a display purpose
    */
     public native void getSegmentationPicture(@ByVal Mat transientAreas);
+    public native void getSegmentationPicture(@ByVal UMat transientAreas);
 
     /** \brief cleans all the buffers of the instance
     */

opencv/src/main/java/org/bytedeco/javacpp/opencv_dnn.java

@@ -1,4 +1,4 @@
-// Targeted by JavaCPP version 1.2: DO NOT EDIT THIS FILE
+// Targeted by JavaCPP version 1.2.5-SNAPSHOT: DO NOT EDIT THIS FILE
 
 package org.bytedeco.javacpp;
 
@@ -425,6 +425,10 @@ Functionality of this module is designed only for forward pass computations (i.
         private native void allocate(@ByVal Mat image, int dstCn/*=-1*/);
         public Blob(@ByVal Mat image) { super((Pointer)null); allocate(image); }
         private native void allocate(@ByVal Mat image);
+        public Blob(@ByVal UMat image, int dstCn/*=-1*/) { super((Pointer)null); allocate(image, dstCn); }
+        private native void allocate(@ByVal UMat image, int dstCn/*=-1*/);
+        public Blob(@ByVal UMat image) { super((Pointer)null); allocate(image); }
+        private native void allocate(@ByVal UMat image);
 
         /** \brief Creates blob with specified \p shape and \p type. */
         public native void create(@Const @ByRef BlobShape shape, int type/*=CV_32F*/);

opencv/src/main/java/org/bytedeco/javacpp/opencv_face.java

@@ -1,4 +1,4 @@
-// Targeted by JavaCPP version 1.2: DO NOT EDIT THIS FILE
+// Targeted by JavaCPP version 1.2.5-SNAPSHOT: DO NOT EDIT THIS FILE
 
 package org.bytedeco.javacpp;
 
@@ -346,6 +346,9 @@ And finally train it on the given dataset (the face images and labels):
     }</pre>
      */
     public native void train(@ByVal MatVector src, @ByVal Mat labels);
+    public native void train(@ByVal UMatVector src, @ByVal Mat labels);
+    public native void train(@ByVal MatVector src, @ByVal UMat labels);
+    public native void train(@ByVal UMatVector src, @ByVal UMat labels);
 
     /** \brief Updates a FaceRecognizer with given data and associated labels.
     <p>
@@ -395,9 +398,13 @@ Calling update on an Eigenfaces model (see createEigenFaceRecognizer), which doe
     responsible for maintaining the dataset, he want to work with.
      */
     public native void update(@ByVal MatVector src, @ByVal Mat labels);
+    public native void update(@ByVal UMatVector src, @ByVal Mat labels);
+    public native void update(@ByVal MatVector src, @ByVal UMat labels);
+    public native void update(@ByVal UMatVector src, @ByVal UMat labels);
 
     /** \overload */
     public native int predict(@ByVal Mat src);
+    public native int predict(@ByVal UMat src);
 
 
     /** \brief Predicts a label and associated confidence (e.g. distance) for a given input image.
@@ -437,7 +444,8 @@ Or to get a prediction and the associated confidence (e.g. distance):
      */
     public native void predict(@ByVal Mat src, @ByRef IntPointer label, @ByRef DoublePointer confidence);
     public native void predict(@ByVal Mat src, @ByRef IntBuffer label, @ByRef DoubleBuffer confidence);
-    public native void predict(@ByVal Mat src, @ByRef int[] label, @ByRef double[] confidence);
+    public native void predict(@ByVal UMat src, @ByRef int[] label, @ByRef double[] confidence);
+    public native void predict(@ByVal UMat src, @ByRef IntPointer label, @ByRef DoublePointer confidence);
 
 
     /** \brief - if implemented - send all result of prediction to collector that can be used for somehow custom result handling
@@ -450,6 +458,8 @@ To implement this method u just have to do same internal cycle as in predict(Inp
     */
     public native void predict(@ByVal Mat src, @Ptr PredictCollector collector, int state/*=0*/);
     public native void predict(@ByVal Mat src, @Ptr PredictCollector collector);
+    public native void predict(@ByVal UMat src, @Ptr PredictCollector collector, int state/*=0*/);
+    public native void predict(@ByVal UMat src, @Ptr PredictCollector collector);
 
     /** \brief Saves a FaceRecognizer and its model state.
     <p>