Fix typos

modules/dnn/include/opencv2/dnn/blob.hpp

@@ -84,7 +84,7 @@ namespace dnn
         /** @brief Returns the size of the specified @p axis.
          *
          * Does the same thing as size(int) const, but if non-existing axis will be passed then 1 will be returned,
-         * therefore this function always finishes successfuly.
+         * therefore this function always finishes successfully.
          */
         int xsize(int axis) const;
 
@@ -152,7 +152,7 @@ namespace dnn
         /** @brief Returns the size of the specified @p axis.
          *
          * Does the same thing as size(int) const, but if non-existing axis will be passed then 1 will be returned,
-         * therefore this function always finishes successfuly.
+         * therefore this function always finishes successfully.
          */
         int xsize(int axis) const;
 
@@ -172,21 +172,18 @@ namespace dnn
         /** @brief Checks equality of two blobs shapes. */
         bool equalShape(const Blob &other) const;
 
-        /** @brief Returns sclice of first two dimensions.
-         *  @details The behavior is similar to the following numpy code: blob[n, cn, ...]
+        /** @brief Returns slice of first two dimensions.
+         *  @details The behaviour is similar to the following numpy code: blob[n, cn, ...]
          */
         Mat getPlane(int n, int cn);
 
-        /** @addtogroup Shape getters of 4-dimensional blobs.
-         *  @{
-         */
+        /* Shape getters of 4-dimensional blobs. */
         int cols() const;       //!< Returns size of the fourth axis blob.
         int rows() const;       //!< Returns size of the thrid  axis blob.
         int channels() const;   //!< Returns size of the second axis blob.
         int num() const;        //!< Returns size of the first  axis blob.
         Size size2() const;     //!< Returns cv::Size(cols(), rows())
-        Vec4i shape4() const;   //!< Returns shape of firt four blob axes.
-        /** @}*/
+        Vec4i shape4() const;   //!< Returns shape of first four blob axes.
 
         /** @brief Returns linear index of the element with specified coordinates in the blob.
          *
@@ -198,9 +195,7 @@ namespace dnn
         /** @overload */
         size_t offset(int n = 0, int cn = 0, int row = 0, int col = 0) const;
 
-        /** @addtogroup CPU pointer getters
-         *  @{
-         */
+        /* CPU pointer getters */
         /** @brief Returns pointer to the blob element with the specified position, stored in CPU memory.
          *
          * @p n correspond to the first axis, @p cn - to the second, etc.
@@ -214,7 +209,6 @@ namespace dnn
         /** @overload ptr<float>() */
         float *ptrf(int n = 0, int cn = 0, int row = 0, int col = 0);
         //TODO: add const ptr methods
-        /** @}*/
 
         /** @brief Shares data from other @p blob.
          * @returns *this

modules/dnn/include/opencv2/dnn/dict.hpp

@@ -72,7 +72,7 @@ struct DictValue
     static DictValue arrayString(TypeIter begin, int size); //!< Constructs array of strings
 
     template<typename T>
-    T get(int idx = -1) const; //!< Tries to convert array element with specified index to requested type and returns it.
+    T get(int idx = -1) const; //!< Tries to convert array element with specified index to requested type and returns its.
 
     int size() const;
 

modules/dnn/include/opencv2/dnn/dnn.hpp

@@ -116,14 +116,14 @@ namespace dnn //! This namespace is used for dnn module functionlaity.
         String type; //!< Type name which was used for creating layer by layer factory.
 
         Layer();
-        explicit Layer(const LayerParams &params); //!< Intialize only #name, #type and #blobs fields.
+        explicit Layer(const LayerParams &params); //!< Initialize only #name, #type and #blobs fields.
         virtual ~Layer();
     };
 
-    /** @brief This class allows to create and maunipulate comprehensive artifical neural networks.
+    /** @brief This class allows to create and manipulate comprehensive artificial neural networks.
      *
      * Neural network is presented as directed acyclic graph (DAG), where vertices are Layer instances,
-     * and edges specify relationships between layers inputs and ouputs.
+     * and edges specify relationships between layers inputs and outputs.
      *
      * Each network layer has unique integer id and unique string name inside its network.
      * LayerId can store either layer name or layer id.
@@ -165,7 +165,7 @@ namespace dnn //! This namespace is used for dnn module functionlaity.
          *  @param inpPin descriptor of the second layer input.
          *
          * Descriptors have the following template <DFN>&lt;layer_name&gt;[.input_number]</DFN>:
-         * - the first part of the tamplate <DFN>layer_name</DFN> is sting name of the added layer.
+         * - the first part of the template <DFN>layer_name</DFN> is sting name of the added layer.
          *   If this part is empty then the network input pseudo layer will be used;
          * - the second optional part of the template <DFN>input_number</DFN>
          *   is either number of the layer input, either label one.

modules/dnn/tutorials/tutorial_dnn_build.markdown

@@ -26,19 +26,16 @@ git clone https://github.com/Itseez/opencv_contrib
 
     - Set binaries directory, for example, to **opencv_root**/build_opencv.
       This directory will contain built libraries.
-
-![](images/build_1.png)
+      ![](images/build_1.png)
 
 -# Configure opencv:
        - press *Configure*;
        - choose the preferred project generator (Makefiles for Linux, MS Visual Studio for Windows);
        - also you can set many opencv build options, for more details see @ref tutorial_linux_install.
-
-![](images/build_2.png)
+         ![](images/build_2.png)
 
 -# In the appeared list of build parameters find parameter `OPENCV_EXTRA_MODULES_PATH` and set it to the **opencv_root**/opencv_contrib.
-
-![](images/build_3.png)
+   ![](images/build_3.png)
 
 -# *Configure* the project again, and set build options of dnn module:
 
@@ -51,12 +48,10 @@ git clone https://github.com/Itseez/opencv_contrib
 
     - You can additionally check `opencv_dnn_BUILD_TORCH_IMPORTER` parameter to build [Torch7](http://torch.ch) importer.
        It allows you to use networks, generated by Torch7 [nn](https://github.com/torch/nn/blob/master/README.md) module.
-
-![](images/build_4.png)
+       ![](images/build_4.png)
 
 -# Press *Configure* and *Generate*.
-
-![](images/build_5.png)
+   ![](images/build_5.png)
 
 -# Build the generated project:
     - If Makefiles generator on Unix was used, run the following in terminal:

modules/dnn/tutorials/tutorial_dnn_googlenet.markdown

@@ -56,7 +56,7 @@ Explanation
    We put the output of "prob" layer, which contain probabilities for each of 1000 ILSVRC2012 image classes, to the `prob` blob.
    And find the index of element with maximal value in this one. This index correspond to the class of the image.
 
--# Print the results
+-# Print results
    @snippet dnn/samples/caffe_googlenet.cpp print_info
    For our image we get:
 > Best class: #812 'space shuttle'