Merge pull request #193 from aferust/master

update docs finally

Author: aferust

docs/builddoc.sh

@@ -5,7 +5,7 @@ set DDOCFILE=dcv.ddoc
 cd ../
 
 dub --build=docs --compiler=ldc2 dcv:core
-dub --build=docs --compiler=ldc2 dcv:io
-dub --build=docs --compiler=ldc2 dcv:plot
+dub --build=docs --compiler=ldc2 dcv:imageio
+dub --build=docs --compiler=ldc2 dcv:linalg
 
 cd docs

source/dcv/core/image.d

@@ -1,17 +1,28 @@
 /**
 Module implements Image utility class, and basic API for image manipulation.
 Image class encapsulates image properties with minimal functionality. It is primarily designed to be used as I/O unit.
-For any image processing needs, image data can be sliced to mir.ndslice.slice.Slice. 
+For any image processing needs, image data can be sliced to mir.ndslice.slice.Slice.
+If an Image instance is initialized with non-null ubyte[] data, this time, 
+the Image instance behaves like a slice shell, and it does not attempt to deallocate the borrowed data slice.
 Example:
 ----
-Image image = new Image(32, 32, ImageFormat.IF_MONO, BitDepth.BD_32);
-Slice!(float*, 3, Contiguous) slice = image.sliced!float; // slice image data, considering the data is of float type.
+Image image1 = new Image(32, 32, ImageFormat.IF_MONO, BitDepth.BD_32);
+Slice!(ubyte*, 3, Contiguous) slice = image1.sliced; // slice image data
+// Slice!(ubyte*, 2, Contiguous) slice = image1.sliced2D; // if it is known that the data represents a monochrome image
+
 assert(image.height == slice.length!0 && image.width == slice.length!1);
 assert(image.channels == 1);
-image = slice.asImage(ImageFormat.IF_MONO); // create the image back from sliced data.
+image2 = slice.asImage(ImageFormat.IF_MONO); // create the image back from sliced data.
+// asImage allocates with malloc, so it should be freed manually.
+destroyFree(image2)
+...
+
+// here image3 is does neither copy nor own the someUbyteSlice.
+Image image3 = new Image(32, 32, ImageFormat.IF_MONO, BitDepth.BD_32, someUbyteSlice); // or mallocNew!Image(...);
+destroy(image3); // or destroyFree(image3) this does not attempt to free someUbyteSlice.
 ----
 Copyright: Copyright Relja Ljubobratovic 2016.
-Authors: Relja Ljubobratovic
+Authors: Relja Ljubobratovic, Ferhat Kurtulmuş
 License: $(LINK3 http://www.boost.org/LICENSE_1_0.txt, Boost Software License - Version 1.0).
 */
 module dcv.core.image;
@@ -260,9 +271,6 @@ public:
     Get data array from this image.
     Cast data array to corresponding dynamic array type,
     and return it.
-    8-bit data is considered ubyte, 16-bit ushort, and 32-bit float.
-    Params:
-        T = (template parameter) value type (default ubyte) to which data array is casted to.
     */
     inout auto data()
     {

source/dcv/features/package.d

@@ -6,12 +6,12 @@ module dcv.features;
  * v0.1 norm:
  * harris
  * shi-tomasi
- * fast (wrap C version by author: http://www.edwardrosten.com/work/fast.html
+ * fast $(LPAREN)wrap C version by author: http://www.edwardrosten.com/work/fast.html$(RPAREN)
  * most popular blob detectors - sift, ???
  * dense features - hog
  * 
  * v0.1+:
- * other popular feature detectors, descriptor (surf, brief, orb, akaze, etc.)
+ * other popular feature detectors, descriptor, such as surf, brief, orb, akaze, etc.
  */
 
 public import dcv.features.corner, dcv.features.utils, dcv.features.sift;

source/dcv/features/utils.d

@@ -38,24 +38,19 @@ struct Feature
     float score;
 }
 
+@nogc nothrow:
+
 /**
 Extract corners as array of 2D points, from response matrix.
 
 Params:
-    cornerResponse = Response matrix, collected as output from corner
-    detection algoritms such as harrisCorners, or shiTomasiCorners.
-    count = Number of corners which need to be extracted. Default is
-    -1 which indicate that all responses with value above the threshold
-    will be returned.
-    threshold = Response threshold - response values in the matrix
-    larger than this are considered as valid corners.
-
+    cornerResponse = Response matrix, collected as output from corner detection algoritms such as harrisCorners, or shiTomasiCorners.
+    count = Number of corners which need to be extracted. Default is -1 which indicate that all responses with value above the threshold will be returned.
+    threshold = Response threshold - response values in the matrix larger than this are considered as valid corners.
 Returns:
-    Lazy array of size_t[2], as in array of 2D points, of corner reponses
+    RCArray!Pair, as in array of 2D points, of corner reponses
     which fit the given criteria.
 */
-@nogc nothrow:
-
 auto extractCorners(T)
 (
     Slice!(T*, 2, Contiguous) cornerResponse,
@@ -162,9 +157,16 @@ unittest
     assert(res[0] == [1, 1]);
 }
 
-/++
-    Returns euclidean distance between feature descriptor vectors.
-+/
+/**
+    Compute the Euclidean distance between two feature descriptor vectors.
+
+    Params:
+        desc1 = The first feature descriptor vector of const DescriptorValueType[].
+        desc2 = The second feature descriptor vector of const DescriptorValueType[].
+
+    Returns:
+        double = The Euclidean distance between the two feature descriptor vectors.
+*/
 double euclideanDistBetweenDescriptors(DescriptorValueType)(const DescriptorValueType[] desc1, const DescriptorValueType[] desc2) 
 {
     double sum = 0;
@@ -176,9 +178,22 @@ double euclideanDistBetweenDescriptors(DescriptorValueType)(const DescriptorValu
 }
 
 alias FeatureMatch = Tuple!(int, "index1", int, "index2", double, "distNearestNeighbor", double, "nearestNeighborDistanceRatio");
-/++
-    Returns an Array containing matched indices of the given Keypoints with brute force approach.
-+/
+
+/**
+    Finds matching points between two sets of keypoints using the brute force approach.
+
+    This function matches keypoints from two sets by comparing each keypoint in the first set with every keypoint in the second set.
+
+    Params:
+        keypoints1 = The first set of keypoints of const ref Array!KeyPoint .
+        keypoints2 = The second set of keypoints of const ref Array!KeyPoint .
+        threshold = The distance ratio threshold for determining matches. Defaults to 0.5.
+
+    Returns:
+        Array!FeatureMatch = An array containing matched indices of keypoints. Each element in the array is a tuple
+                             containing the index of the keypoint from the first set, the index of the matching keypoint
+                             from the second set, the distance to the nearest neighbor, and the nearest neighbor distance ratio.
+*/
 Array!FeatureMatch
 find_MatchingPointsBruteForce(KeyPoint)(const ref Array!KeyPoint keypoints1,
                      const ref Array!KeyPoint keypoints2, double threshold = 0.5)

source/dcv/imageio/image.d

@@ -1,7 +1,7 @@
 /**
 Module for image I/O.
 Copyright: Copyright Relja Ljubobratovic 2016.
-Authors: Relja Ljubobratovic
+Authors: Relja Ljubobratovic, Ferhat Kurtulmuş
 License: $(LINK3 http://www.boost.org/LICENSE_1_0.txt, Boost Software License - Version 1.0).
 */
 module dcv.imageio.image;
@@ -92,8 +92,6 @@ color format. To load original depth or format, set to _UNASSIGNED (ImageFormat.
 BitDepth.BD_UNASSIGNED).
 return:
 Image read from the filesystem.
-throws:
-Exception and ImageIOException from imageformats library.
 */
 Image imread(in string path, ReadParams params = ReadParams(ImageFormat.IF_UNASSIGNED, BitDepth.BD_UNASSIGNED))
 {

source/dcv/imgproc/convolution.d

@@ -5,19 +5,19 @@ Following example loads famous image of Lena Söderberg and performs gaussian bl
 
 ----
 import dcv.imageio.image : imread, ReadParams;
-import dcv.core.image : Image, asType;
+import dcv.core.image : Image;
 import dcv.imgproc.convolution : conv;
 
 Image lenaImage = imread("../data/lena.png", ReadParams(ImageFormat.IF_MONO, BitDepth.BD_8));
-auto slice = lenaImage.sliced!ubyte;
+auto slice = lenaImage.sliced;
 ----
 
 ... this loads the following image:<br>
 $(IMAGE https://github.com/libmir/dcv/blob/master/examples/data/lena.png?raw=true)
 
 ----
 blurred = slice
-             .asType!float // convert ubyte data to float.
+             .as!float // convert ubyte data to float.
              .conv(gaussian!float(0.84f, 5, 5)); // convolve image with gaussian kernel
 
 ----
@@ -69,7 +69,6 @@ Params:
     prealloc is not of same shape as input input, resulting array will be newly allocated.
     mask = Masking input. Convolution will skip each element where mask is 0. Default value
     is empty slice, which tells that convolution will be performed on the whole input.
-    pool = Optional TaskPool instance used to parallelize computation.
 
 Returns:
     Resulting image after convolution, of same type as input tensor.

source/dcv/imgproc/filter.d

@@ -527,7 +527,6 @@ Params:
                       Default value is EdgeKernel.SIMPLE, which calls calcPartialDerivatives function
                       to calculate derivatives. Other options will perform convolution with requested
                       kernel type.
-    pool            = TaskPool instance used parallelise the algorithm.
 
 Note:
     Input slice's memory has to be contiguous. Magnitude and orientation slices' strides
@@ -615,7 +614,6 @@ Params:
     mag         = Gradient magnitude.
     orient      = Gradient orientation of the same image source as magnitude.
     prealloc    = Optional pre-allocated buffer for output slice.
-    pool        = TaskPool instance used parallelise the algorithm.
 
 Note:
     Orientation and pre-allocated structures must match. If prealloc
@@ -684,7 +682,6 @@ Params:
     upThresh        = upper threshold value after non-maxima suppression.
     edgeKernelType  = Type of edge kernel used to calculate image gradients.
     prealloc        = Optional pre-allocated buffer.
-    pool            = TaskPool instance used parallelise the algorithm.
 */
 @nogc nothrow
 Slice!(RCI!V, 2LU, Contiguous) canny(V, T, SliceKind kind)
@@ -738,7 +735,6 @@ Params:
     sigmaSpace  = Spatial sigma value.
     kernelSize  = Size of convolution kernel. Must be odd number.
     prealloc    = Optional pre-allocated result image buffer. If not of same shape as input slice, its allocated anew.
-    pool        = Optional TaskPool instance used to parallelize computation.
 
 Returns:
     Slice of filtered image.
@@ -861,7 +857,6 @@ Params:
     slice       = Input image slice.
     kernelSize  = Square size of median kernel.
     prealloc    = Optional pre-allocated return image buffer.
-    pool        = Optional TaskPool instance used to parallelize computation.
 
 Returns:
     Returns filtered image of same size as the input. If prealloc parameter is not an empty slice, and is
@@ -1122,7 +1117,6 @@ Params:
     slice       = Input image slice, to be eroded.
     kernel      = Erosion kernel. Default value is radialKernel!T(3).
     prealloc    = Optional pre-allocated buffer to hold result.
-    pool        = Optional TaskPool instance used to parallelize computation.
 
 Returns:
     Eroded image slice, of same type as input image.
@@ -1187,7 +1181,6 @@ Params:
     slice       = Input image slice, to be eroded.
     kernel      = Dilation kernel. Default value is radialKernel!T(3).
     prealloc    = Optional pre-allocated buffer to hold result.
-    pool        = Optional TaskPool instance used to parallelize computation.
     
 Returns:
     Dilated image slice, of same type as input image.
@@ -1216,7 +1209,6 @@ Params:
     slice       = Input image slice, to be eroded.
     kernel      = Erosion/Dilation kernel. Default value is radialKernel!T(3).
     prealloc    = Optional pre-allocated buffer to hold result.
-    pool        = Optional TaskPool instance used to parallelize computation.
     
 Returns:
     Opened image slice, of same type as input image.
@@ -1246,7 +1238,6 @@ Params:
     slice = Input image slice, to be eroded.
     kernel = Erosion/Dilation kernel. Default value is radialKernel!T(3).
     prealloc = Optional pre-allocated buffer to hold result.
-    pool = Optional TaskPool instance used to parallelize computation.
     
 Returns:
     Closed image slice, of same type as input image.

source/dcv/imgproc/interpolate.d

@@ -56,7 +56,7 @@ Linear interpolation.
 
 Params:
     slice = Input slice which values are interpolated.
-    pos = Position on which slice values are interpolated.
+    pos0 = Position on which slice values are interpolated.
 
 Returns:
     Interpolated resulting value.

source/dcv/imgproc/threshold.d

@@ -3,7 +3,7 @@ Image thresholding module.
 
 Copyright: Copyright Relja Ljubobratovic 2016.
 
-Authors: Relja Ljubobratovic
+Authors: Relja Ljubobratovic, Ferhat Kurtulmuş
 
 License: $(LINK3 http://www.boost.org/LICENSE_1_0.txt, Boost Software License - Version 1.0).
 */
@@ -36,6 +36,7 @@ Params:
     input = Input slice.
     lowThresh   = Lower threshold value.
     highThresh  = Higher threshold value.
+    inverse     = A flag to set output image as a negative binary image
     prealloc    = Optional pre-allocated slice buffer for output.
 
 Note:
@@ -109,6 +110,7 @@ Calls threshold(slice, thresh, thresh, prealloc)
 Params:
     input       = Input slice.
     thresh      = Threshold value - any value lower than this will be set to 0, and higher to 1.
+    inverse     = A flag to set output image as a negative binary image
     prealloc    = Optional pre-allocated slice buffer for output.
 
 Note: