Merge pull request #356 from kyamagu/cv330

OpenCV 3.3.0

+cv/FeatureDetector.m

@@ -46,6 +46,9 @@
             %             `xfeatures2d` module)
             %       * __MSDDetector__ see cv.MSDDetector (requires
             %             `xfeatures2d` module)
+            %       * __HarrisLaplaceFeatureDetector__ see
+            %             cv.HarrisLaplaceFeatureDetector (requires
+            %             `xfeatures2d` module)
             %
             % ## Options
             % Refer to the constructors of each feature detector for a

+cv/RTrees.m

@@ -601,6 +601,43 @@ function load(this, fname_or_str, varargin)
             v = RTrees_(this.id, 'getVarImportance');
         end
 
+        function votes = getVotes(this, samples, varargin)
+            %GETVOTES  Returns the result of each individual tree in the forest
+            %
+            %    votes = model.getVotes(samples)
+            %    votes = model.getVotes(..., 'OptionName',optionValue, ...)
+            %
+            % ## Input
+            % * __samples__ matrix containg the samples for which votes will
+            %       be calculated.
+            %
+            % ## Output
+            % * __votes__ matrix of the result of the calculation.
+            %
+            % ## Options
+            % * __Flags__ Flags for defining the type of RTrees. For
+            %       convenience, you can set the individual flag options
+            %       below, instead of directly setting bits here. default 0
+            % * __RawOutput__ See the predict method. default false
+            % * __CompressedInput__ See the predict method. default false
+            % * __PreprocessedInput__ See the predict method. default false
+            % * __PredictAuto__ See the predict method. default false
+            % * __PredictSum__ See the predict method. default false
+            % * __PredictMaxVote__ See the predict method. default false
+            %
+            % In case the model is a regression problem, the method will
+            % return each of the trees' results for each of the sample cases,
+            % i.e `nsamples-by-ntrees` matrix.
+            % If the model is a classifier, it will return a matrix with
+            % `nsamples + 1` rows, where the first row gives the class number
+            % and the following rows return the votes each class had for each
+            % sample, i.e `(nsamples+1)-by-nclasses` matrix.
+            %
+            % See also: cv.RTrees.predict
+            %
+            votes = RTrees_(this.id, 'getVotes', samples, varargin{:});
+        end
+
         function roots = getRoots(this)
             %GETROOTS  Returns indices of root nodes
             %

+cv/StereoSGBM.m

@@ -52,9 +52,9 @@
         % Minimum possible disparity value, default 0
         MinDisparity
         % Maximum disparity minus minimum disparity, positive and divisble by
-        % 16. default 64
+        % 16. default 16
         NumDisparities
-        % Matched block size, default 7
+        % Matched block size (SAD window size), default 3
         BlockSize
         % Maximum size of smooth disparity regions to consider their noise
         % speckles and invalidate (when `SpeckleRange>=0` and
@@ -81,9 +81,11 @@
         P2
         % Algorithm Mode, default 'SGBM'
         %
-        % * __SGBM__
-        % * __SGBM3Way__
-        % * __HH__ runs the full-scale two-pass dynamic programming algorithm
+        % * __SGBM__ 5-directional version of the algorithm
+        % * __HH__ 8-dir mode, runs the full-scale two-pass dynamic
+        %       programming algorithm (slowest, memory intensive)
+        % * __SGBM3Way__ 3-dir mode (fastest)
+        % * __HH4__ 4-directional variation of SGBM
         Mode
     end
 
@@ -102,10 +104,10 @@
             % * __NumDisparities__ Maximum disparity minus minimum disparity.
             %       The value is always greater than zero. In the current
             %       implementation, this parameter must be divisible by 16.
-            %       default 64
+            %       default 16
             % * __BlockSize__ Matched block size. It must be an odd number >=1.
             %       Normally, it should be somewhere in the 3..11 range.
-            %       default 7
+            %       default 3
             % * __P1__ The first parameter controlling the disparity
             %       smoothness. See `P2`. default 0 (which uses 2).
             % * __P2__ The second parameter controlling the disparity

+cv/VideoCapture.m

@@ -137,17 +137,17 @@
         Format
         % Backend-specific value indicating the current capture mode.
         Mode
-        % Brightness of the image (only for cameras).
+        % Brightness of the image (only for those cameras that support it).
         Brightness
         % Contrast of the image (only for cameras).
         Contrast
         % Saturation of the image (only for cameras).
         Saturation
         % Hue of the image (only for cameras).
         Hue
-        % Gain of the image (only for cameras).
+        % Gain of the image (only for those cameras that support it).
         Gain
-        % Exposure (only for cameras).
+        % Exposure (only for those cameras that support it).
         Exposure
         % Boolean flags indicating whether images should be converted to RGB.
         ConvertRGB
@@ -220,6 +220,7 @@ function delete(this)
             %         Note that each video stream or IP camera feed has its
             %         own URL scheme. Please refer to the documentation of
             %         source stream to know the right URL.
+            %       * or device name (for backends like V4L or gPhoto2)
             %
             % ## Output
             % * __successFlag__ bool, true if the file/camera has been
@@ -264,6 +265,8 @@ function delete(this)
             %             library.
             %       * __Images__ OpenCV Image Sequence (e.g. `img_%02d.jpg`).
             %       * __Aravis__ Aravis GigE SDK.
+            %       * __MotionJPEG__ Built-in OpenCV MotionJPEG codec.
+            %       * __MediaSDK__ Intel MediaSDK.
             %
             % The method first calls cv.VideoCapture.release to close the
             % already opened file or camera.

+cv/VideoWriter.m

@@ -78,34 +78,47 @@ function delete(this)
             VideoWriter_(this.id, 'delete');
         end
 
-        function retval = open(this, filename, frameSize, varargin)
+        function successFlag = open(this, filename, frameSize, varargin)
             %OPEN  Initializes or reinitializes video writer
             %
-            %    retval = vid.open(filename, frameSize)
-            %    retval = vid.open(filename, frameSize, 'OptionName',optionValue, ...)
+            %    successFlag = vid.open(filename, frameSize)
+            %    successFlag = vid.open(filename, frameSize, 'OptionName',optionValue, ...)
             %
             % ## Input
             % * __filename__ Name of the output video file
             % * __frameSize__ Size of the video frames `[width, height]`.
             %
             % ## Output
-            % * __retval__ bool, true if video writer has been successfully
+            % * __successFlag__ bool, true if video writer has been successfully
             %       initialized.
             %
             % ## Options
+            % * __API__ The parameter allows to specify API backends to use.
+            %       Can be used to enforce a specific writer implementation if
+            %       multiple are available: e.g. 'FFMPEG' or 'GStreamer'
+            %       * __Any__ (default) Auto detect
+            %       * __VfW__ Video For Windows
+            %       * __QuickTime__ QuickTime
+            %       * __AVFoundation__ AVFoundation framework for iOS
+            %       * __MediaFoundation__ Microsoft Media Foundation
+            %       * __GStreamer__ GStreamer
+            %       * __FFMPEG__ FFMPEG library
+            %       * __Images__ OpenCV Image Sequence (e.g. `img_%02d.jpg`)
+            %       * __MotionJPEG__ Built-in OpenCV MotionJPEG codec
+            %       * __MediaSDK__ Intel Media SDK
             % * __FourCC__ 4-character code of codec used to compress the
             %       frames. List of codes can be obtained at [FOURCC]. FFMPEG
             %       backend with MP4 container natively uses other values as
             %       FourCC code: see [ObjectType], so you may receive a
             %       warning message from OpenCV about fourcc code conversion.
             %       Examples are:
             %       * __PIM1__ MPEG-1 codec
-            %       * __MJPG__ Motion-JPEG codec
+            %       * __MJPG__ Motion-JPEG codec (default)
             %       * __MP42__ MPEG-4 (Microsoft)
             %       * __DIV3__ DivX MPEG-4 Part 2
             %       * __DIVX__ DivX codec
             %       * __XVID__ XVID MPEG-4 Part 2
-            %       * __U263__ H263 (default)
+            %       * __U263__ H263
             %       * __I263__ ITU H.263
             %       * __FLV1__ Sorenson Spark (Flash Video)
             %       * __X264__ H.264
@@ -149,7 +162,7 @@ function delete(this)
             %
             % See also: cv.VideoWriter.VideoWriter, cv.VideoWriter.isOpened
             %
-            retval = VideoWriter_(this.id, 'open', filename, frameSize, varargin{:});
+            successFlag = VideoWriter_(this.id, 'open', filename, frameSize, varargin{:});
         end
 
         function retval = isOpened(this)

+cv/accumulate.m

@@ -4,9 +4,10 @@
 %    dst = cv.accumulate(src, dst, 'OptionName',optionValue, ...)
 %
 % ## Input
-% * __src__ Input image as 1- or 3-channel, 8-bit or 32-bit floating-point.
+% * __src__ Input image of type `uint8`, `uint16`, `single`, or `double, with
+%       any number of channels
 % * __dst__ Input accumulator image with the same number of channels as input
-%       image, 32-bit or 64-bit floating-point.
+%       image, and a depth of `single` or `double`.
 %
 % ## Output
 % * __dst__ Output accumulator image.

+cv/accumulateProduct.m

@@ -4,11 +4,11 @@
 %    dst = cv.accumulateProduct(src1, src2, dst, 'OptionName',optionValue, ...)
 %
 % ## Input
-% * __src1__ First input image, 1- or 3-channel, 8-bit or 32-bit floating
-%       point.
+% * __src1__ First input image of type `uint8`, `uint16`, `single`, or `double,
+%       with any number of channels
 % * __src2__ Second input image of the same type and the same size as `src1`.
-% * __dst__ Input accumulator with the same number of channels as input
-%       images, 32-bit or 64-bit floating-point.
+% * __dst__ Input accumulator image with the same number of channels as input
+%       images, and a depth of `single` or `double`.
 %
 % ## Output
 % * __dst__ Output accumulator image.

+cv/accumulateSquare.m

@@ -4,9 +4,10 @@
 %    dst = cv.accumulateSquare(src, dst, 'OptionName',optionValue, ...)
 %
 % ## Input
-% * __src__ Input image as 1- or 3-channel, 8-bit or 32-bit floating-point.
+% * __src__ Input image of type `uint8`, `uint16`, `single`, or `double, with
+%       any number of channels
 % * __dst__ Input accumulator image with the same number of channels as input
-%       image, 32-bit or 64-bit floating-point.
+%       image, and a depth of `single` or `double`.
 %
 % ## Output
 % * __dst__ Output accumulator image.

+cv/accumulateWeighted.m

@@ -4,9 +4,10 @@
 %    dst = cv.accumulateWeighted(..., 'OptionName',optionValue, ...)
 %
 % ## Input
-% * __src__ Input image as 1- or 3-channel, 8-bit or 32-bit floating-point.
+% * __src__ Input image of type `uint8`, `uint16`, `single`, or `double, with
+%       any number of channels
 % * __dst__ Input accumulator image with the same number of channels as input
-%       image, 32-bit or 64-bit floating-point.
+%       image, and a depth of `single` or `double`.
 % * __alpha__ Weight of the input image. A scalar double.
 %
 % ## Output

+cv/applyColorMap.m

@@ -1,6 +1,7 @@
 %APPLYCOLORMAP  Applies a GNU Octave/MATLAB equivalent colormap on a given image
 %
 %    dst = cv.applyColorMap(src, colormap)
+%    dst = cv.applyColorMap(src, userColor)
 %    dst = cv.applyColorMap(..., 'OptionName',optionValue, ...)
 %
 % ## Input
@@ -19,6 +20,8 @@
 %       * __Pink__ Pastel shades of pink color map.
 %       * __Hot__ Black-red-yellow-white color map.
 %       * __Parula__ Blue-green-orange-yellow color map.
+% * __userColor__ The colormap to apply of type `uint8` (1 or 3 channels) and
+%       length 256.
 %
 % ## Output
 % * __dst__ The result is the colormapped source image. Same row/column size
@@ -34,6 +37,9 @@
 % OpenCV now comes with various colormaps to enhance the visualization in your
 % computer vision application.
 %
+% The second variant of the function applies a user-defined colormap on the
+% given image.
+%
 % ## Example
 %
 % In OpenCV you only need cv.applyColorMap to apply a colormap on a given

+cv/calibrateCamera.m

@@ -78,6 +78,10 @@
 %       default false.
 % * __ZeroTangentDist__ Tangential distortion coefficients `p1` and `p2` are
 %       set to zeros and stay fixed. default false.
+% * __FixTangentDist__ The tangential distortion coefficients are not
+%       changed during the optimization. If `UseIntrinsicGuess` is set, the
+%       coefficient from the supplied `DistCoeffs` matrix is used. Otherwise,
+%       it is set to 0. default false.
 % * __FixK1__, ..., __FixK6__ The corresponding radial distortion coefficient
 %       is not changed during the optimization. If `UseIntrinsicGuess` is set,
 %       the coefficient from the supplied `DistCoeffs` matrix is used.

+cv/cvtColor.m

@@ -79,7 +79,9 @@
 %       * __BayerBG2BGR__, __BayerGB2BGR__, __BayerRG2BGR__, __BayerGR2BGR__,
 %         __BayerBG2RGB__, __BayerGB2RGB__, __BayerRG2RGB__, __BayerGR2RGB__,
 %         __BayerBG2GRAY__, __BayerGB2GRAY__, __BayerRG2GRAY__,
-%         __BayerGR2GRAY__: Demosaicing
+%         __BayerGR2GRAY__, __BayerBG2BGRA__, __BayerGB2BGRA__,
+%         __BayerRG2BGRA__, __BayerGR2BGRA__, __BayerBG2RGBA__,
+%         __BayerGB2RGBA__, __BayerRG2RGBA__, __BayerGR2RGBA__: Demosaicing
 %       * **BayerBG2BGR_VNG**, **BayerGB2BGR_VNG**, **BayerRG2BGR_VNG**,
 %         **BayerGR2BGR_VNG**, **BayerBG2RGB_VNG**, **BayerGB2RGB_VNG**,
 %         **BayerRG2RGB_VNG**, **BayerGR2RGB_VNG**: Demosaicing using

+cv/dft.m

@@ -41,6 +41,10 @@
 %       inverse transformation is executed, the function treats the input as a
 %       packed complex-conjugate symmetrical array, and the output will also
 %       be a real array). default false
+% * __ComplexInput__ specifies that input is complex input. If this flag is
+%       set, the input must have 2 channels. On the other hand, for backwards
+%       compatibility reason, if input has 2 channels, input is already
+%       considered complex. default false
 % * __NonzeroRows__ when the parameter is not zero, the function assumes that
 %       only the first `NonzeroRows` rows of the input array (`Inverse` is not
 %       set) or only the first `NonzeroRows` of the output array (`Inverse` is

+cv/findCirclesGrid.m

@@ -31,6 +31,25 @@
 %       optional parameters used to construct the specified feature detector.
 %       See cv.FeatureDetector for possible types.
 %       default is to use cv.SimpleBlobDetector with its default parameters.
+% * __FinderParameters__ Parameters for finding circles in a grid pattern.
+%       You can specify the parameters as a cell-array that starts with the
+%       grid type followed by pairs of key-value options
+%       `{'Symmetric', 'key',val, ...}`, or as a structure where the fields
+%       are the options `struct('GridType','Symmetric', 'key',val, ...)`.
+%       * __GridType__ one of 'Symmetric' (default) or 'Asymmetric'
+%       * __DensityNeighborhoodSize__ default [16,16]
+%       * __MinDensity__ default 10.0
+%       * __KmeansAttempts__ default 100
+%       * __MinDistanceToAddKeypoint__ default 20
+%       * __KeypointScale__ default 1
+%       * __MinGraphConfidence__ default 9.0
+%       * __VertexGain__ default 1.0
+%       * __VertexPenalty__ default -0.6
+%       * __ExistingVertexGain__ default 10000.0
+%       * __EdgeGain__ default 1.0
+%       * __EdgePenalty__ default -0.6
+%       * __ConvexHullFactor__ default 1.1
+%       * __MinRNGEdgeSwitchDist__ default 5.0
 %
 % The function attempts to determine whether the input image contains a grid
 % of circles. If it is, the function locates centers of the circles. The

+cv/findTransformECC.m

@@ -34,7 +34,7 @@
 % * __Mask__ An optional mask to indicate valid values of `inputImage`.
 %       Not set by default.
 % * __InputWarp__ Initial estimate for `warpMatrix`. See the notes
-%       below. Default `eye(2,3)`
+%       below. Default `eye(2,3)` or `eye(3,3)` depending on motion type.
 %
 % The function estimates the optimum transformation (`warpMatrix`) with
 % respect to ECC criterion ([EP08]), that is:
@@ -55,7 +55,7 @@
 % cv.findTransformECC implements an area-based alignment that builds on
 % intensity similarities. In essence, the function updates the initial
 % transformation that roughly aligns the images. If this information is
-% missing, the identity warp (unity matrix) should be given as input. Note
+% missing, the identity warp (unity matrix) is used as an initialization. Note
 % that if images undergo strong displacements/rotations, an initial
 % transformation that roughly aligns the images is necessary (e.g., a simple
 % euclidean/similarity transform that allows for the images showing the same

+cv/imdecode.m

@@ -21,6 +21,8 @@
 %       default true
 % * __Grayscale__ If set, always convert image to the single channel grayscale
 %       image. default false
+% * __IgnoreOrientation__ If set, do not rotate the image according to EXIF's
+%       orientation flag. default false
 % * __Flags__ Advanced option to directly set the flag specifying the depth
 %       and color type of a loaded image. Note that setting this integer flag
 %       overrides all the other flag options. Not set by default:

+cv/imwrite.m

@@ -29,14 +29,15 @@
 % * __JpegChromaQuality__ Separate chroma quality level, 0 - 100,
 %       default is 0 (don't use).
 % * __PngCompression__ For PNG, it can be the compression level from 0 to 9.
-%       A higher value means a smaller size and longer compression time.
-%       Default value is 3. Also strategy is changed to `Default`.
+%       A higher value means a smaller size and longer compression time. If
+%       specified, `PngStrategy` is changed to `Default`. Default value is 1
+%       (best speed setting).
 % * __PngStrategy__ For PNG; used to tune the compression algorithm. These
 %       flags will be modify the way of PNG image compression and will be
 %       passed to the underlying zlib processing stage. The strategy parameter
 %       only affects the compression ratio but not the correctness of the
 %       compressed output even if it is not set appropriately. One of:
-%       * __Default__ (default) Use this value for normal data.
+%       * __Default__ Use this value for normal data.
 %       * __Filtered__ Use this value for data produced by a filter (or
 %             predictor). Filtered data consists mostly of small values with a
 %             somewhat random distribution. In this case, the compression
@@ -46,8 +47,8 @@
 %             `HuffmanOnly`.
 %       * __HuffmanOnly__ Use this value to force Huffman encoding only
 %             (no string match).
-%       * __RLE__ Use this value to limit match distances to one (run-length
-%             encoding). `RLE` is designed to be almost as fast as
+%       * __RLE__ (default) Use this value to limit match distances to one
+%             (run-length encoding). `RLE` is designed to be almost as fast as
 %             `HuffmanOnly`, but give better compression for PNG image data.
 %       * __Fixed__ Using this value prevents the use of dynamic Huffman
 %             codes, allowing for a simpler decoder for special applications.