Open Source Computer Vision Library https://opencv.org/
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Remapping {#tutorial_remap}
=========
Goal
----
In this tutorial you will learn how to:
a. Use the OpenCV function @ref cv::remap to implement simple remapping routines.
Theory
------
### What is remapping?
- It is the process of taking pixels from one place in the image and locating them in another
position in a new image.
- To accomplish the mapping process, it might be necessary to do some interpolation for
non-integer pixel locations, since there will not always be a one-to-one-pixel correspondence
between source and destination images.
- We can express the remap for every pixel location \f$(x,y)\f$ as:
\f[g(x,y) = f ( h(x,y) )\f]
where \f$g()\f$ is the remapped image, \f$f()\f$ the source image and \f$h(x,y)\f$ is the mapping function
that operates on \f$(x,y)\f$.
- Let's think in a quick example. Imagine that we have an image \f$I\f$ and, say, we want to do a
remap such that:
\f[h(x,y) = (I.cols - x, y )\f]
What would happen? It is easily seen that the image would flip in the \f$x\f$ direction. For
instance, consider the input image:
![](images/Remap_Tutorial_Theory_0.jpg)
observe how the red circle changes positions with respect to x (considering \f$x\f$ the horizontal
direction):
![](images/Remap_Tutorial_Theory_1.jpg)
- In OpenCV, the function @ref cv::remap offers a simple remapping implementation.
Code
----
- **What does this program do?**
- Loads an image
- Each second, apply 1 of 4 different remapping processes to the image and display them
indefinitely in a window.
- Wait for the user to exit the program
@add_toggle_cpp
- The tutorial code's is shown lines below. You can also download it from
[here](https://github.com/opencv/opencv/tree/3.4/samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp)
@include samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp
@end_toggle
@add_toggle_java
- The tutorial code's is shown lines below. You can also download it from
[here](https://github.com/opencv/opencv/tree/3.4/samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java)
@include samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java
@end_toggle
@add_toggle_python
- The tutorial code's is shown lines below. You can also download it from
[here](https://github.com/opencv/opencv/tree/3.4/samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py)
@include samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py
@end_toggle
Explanation
-----------
- Load an image:
@add_toggle_cpp
@snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Load
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Load
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Load
@end_toggle
- Create the destination image and the two mapping matrices (for x and y )
@add_toggle_cpp
@snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Create
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Create
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Create
@end_toggle
- Create a window to display results
@add_toggle_cpp
@snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Window
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Window
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Window
@end_toggle
- Establish a loop. Each 1000 ms we update our mapping matrices (*mat_x* and *mat_y*) and apply
them to our source image:
@add_toggle_cpp
@snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Loop
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Loop
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Loop
@end_toggle
- The function that applies the remapping is @ref cv::remap . We give the following arguments:
- **src**: Source image
- **dst**: Destination image of same size as *src*
- **map_x**: The mapping function in the x direction. It is equivalent to the first component
of \f$h(i,j)\f$
- **map_y**: Same as above, but in y direction. Note that *map_y* and *map_x* are both of
the same size as *src*
- **INTER_LINEAR**: The type of interpolation to use for non-integer pixels. This is by
default.
- **BORDER_CONSTANT**: Default
How do we update our mapping matrices *mat_x* and *mat_y*? Go on reading:
- **Updating the mapping matrices:** We are going to perform 4 different mappings:
-# Reduce the picture to half its size and will display it in the middle:
\f[h(i,j) = ( 2 \times i - src.cols/2 + 0.5, 2 \times j - src.rows/2 + 0.5)\f]
for all pairs \f$(i,j)\f$ such that: \f$\dfrac{src.cols}{4}<i<\dfrac{3 \cdot src.cols}{4}\f$ and
\f$\dfrac{src.rows}{4}<j<\dfrac{3 \cdot src.rows}{4}\f$
-# Turn the image upside down: \f$h( i, j ) = (i, src.rows - j)\f$
-# Reflect the image from left to right: \f$h(i,j) = ( src.cols - i, j )\f$
-# Combination of b and c: \f$h(i,j) = ( src.cols - i, src.rows - j )\f$
This is expressed in the following snippet. Here, *map_x* represents the first coordinate of
*h(i,j)* and *map_y* the second coordinate.
@add_toggle_cpp
@snippet samples/cpp/tutorial_code/ImgTrans/Remap_Demo.cpp Update
@end_toggle
@add_toggle_java
@snippet samples/java/tutorial_code/ImgTrans/remap/RemapDemo.java Update
@end_toggle
@add_toggle_python
@snippet samples/python/tutorial_code/ImgTrans/remap/Remap_Demo.py Update
@end_toggle
Result
------
-# After compiling the code above, you can execute it giving as argument an image path. For
instance, by using the following image:
![](images/Remap_Tutorial_Original_Image.jpg)
-# This is the result of reducing it to half the size and centering it:
![](images/Remap_Tutorial_Result_0.jpg)
-# Turning it upside down:
![](images/Remap_Tutorial_Result_1.jpg)
-# Reflecting it in the x direction:
![](images/Remap_Tutorial_Result_2.jpg)
-# Reflecting it in both directions:
![](images/Remap_Tutorial_Result_3.jpg)