init - 初始化项目

doc/tutorials/core/adding_images/adding_images.markdown

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+Adding (blending) two images using OpenCV {#tutorial_adding_images}
+=========================================
+
+@tableofcontents
+
+@prev_tutorial{tutorial_mat_operations}
+@next_tutorial{tutorial_basic_linear_transform}
+
+|    |    |
+| -: | :- |
+| Original author | Ana Huamán |
+| Compatibility | OpenCV >= 3.0 |
+
+We will learn how to blend two images!
+Goal
+----
+
+In this tutorial you will learn:
+
+-   what is *linear blending* and why it is useful;
+-   how to add two images using **addWeighted()**
+
+Theory
+------
+
+@note
+   The explanation below belongs to the book [Computer Vision: Algorithms and
+    Applications](http://szeliski.org/Book/) by Richard Szeliski
+
+From our previous tutorial, we know already a bit of *Pixel operators*. An interesting dyadic
+(two-input) operator is the *linear blend operator*:
+
+\f[g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)\f]
+
+By varying \f$\alpha\f$ from \f$0 \rightarrow 1\f$ this operator can be used to perform a temporal
+*cross-dissolve* between two images or videos, as seen in slide shows and film productions (cool,
+eh?)
+
+Source Code
+-----------
+
+@add_toggle_cpp
+Download the source code from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/cpp/tutorial_code/core/AddingImages/AddingImages.cpp).
+@include cpp/tutorial_code/core/AddingImages/AddingImages.cpp
+@end_toggle
+
+@add_toggle_java
+Download the source code from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/java/tutorial_code/core/AddingImages/AddingImages.java).
+@include java/tutorial_code/core/AddingImages/AddingImages.java
+@end_toggle
+
+@add_toggle_python
+Download the source code from
+[here](https://raw.githubusercontent.com/opencv/opencv/master/samples/python/tutorial_code/core/AddingImages/adding_images.py).
+@include python/tutorial_code/core/AddingImages/adding_images.py
+@end_toggle
+
+Explanation
+-----------
+
+Since we are going to perform:
+
+\f[g(x) = (1 - \alpha)f_{0}(x) + \alpha f_{1}(x)\f]
+
+We need two source images (\f$f_{0}(x)\f$ and \f$f_{1}(x)\f$). So, we load them in the usual way:
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp load
+@end_toggle
+
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java load
+@end_toggle
+
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py load
+@end_toggle
+
+We used the following images: [LinuxLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/LinuxLogo.jpg) and [WindowsLogo.jpg](https://raw.githubusercontent.com/opencv/opencv/master/samples/data/WindowsLogo.jpg)
+
+@warning Since we are *adding* *src1* and *src2*, they both have to be of the same size
+(width and height) and type.
+
+Now we need to generate the `g(x)` image. For this, the function **addWeighted()** comes quite handy:
+
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp blend_images
+@end_toggle
+
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java blend_images
+@end_toggle
+
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py blend_images
+Numpy version of above line (but cv function is around 2x faster):
+\code{.py}
+    dst = np.uint8(alpha*(img1)+beta*(img2))
+\endcode
+@end_toggle
+
+since **addWeighted()**  produces:
+\f[dst = \alpha \cdot src1 + \beta \cdot src2 + \gamma\f]
+In this case, `gamma` is the argument \f$0.0\f$ in the code above.
+
+Create windows, show the images and wait for the user to end the program.
+@add_toggle_cpp
+@snippet cpp/tutorial_code/core/AddingImages/AddingImages.cpp display
+@end_toggle
+
+@add_toggle_java
+@snippet java/tutorial_code/core/AddingImages/AddingImages.java display
+@end_toggle
+
+@add_toggle_python
+@snippet python/tutorial_code/core/AddingImages/adding_images.py display
+@end_toggle
+
+Result
+------
+
+![](images/Adding_Images_Tutorial_Result_Big.jpg)