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migration: github.com/opencv/opencv

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This commit is contained in:
Alexander Alekhin
2016-06-14 16:01:36 +03:00
parent 6c6badb6a6
commit ddc0b42bc3
94 changed files with 120 additions and 120 deletions
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2
doc/tutorials/core/basic_geometric_drawing/basic_geometric_drawing.markdown
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@@ -47,7 +47,7 @@ Code
----
- This code is in your OpenCV sample folder. Otherwise you can grab it from
[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/Matrix/Drawing_1.cpp)
Explanation
-----------

4
doc/tutorials/core/discrete_fourier_transform/discrete_fourier_transform.markdown
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@@ -15,7 +15,7 @@ Source code
-----------
You can [download this from here
](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp) or
find it in the
`samples/cpp/tutorial_code/core/discrete_fourier_transform/discrete_fourier_transform.cpp` of the
OpenCV source code library.
@@ -140,7 +140,7 @@ An application idea would be to determine the geometrical orientation present in
example, let us find out if a text is horizontal or not? Looking at some text you'll notice that the
text lines sort of form also horizontal lines and the letters form sort of vertical lines. These two
main components of a text snippet may be also seen in case of the Fourier transform. Let us use
[this horizontal ](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/Itseez/opencv/tree/master/samples/data/imageTextR.png)
[this horizontal ](https://github.com/opencv/opencv/tree/master/samples/data/imageTextN.png) and [this rotated](https://github.com/opencv/opencv/tree/master/samples/data/imageTextR.png)
image about a text.
In case of the horizontal text:

2
doc/tutorials/core/file_input_output_with_xml_yml/file_input_output_with_xml_yml.markdown
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@@ -16,7 +16,7 @@ Source code
-----------
You can [download this from here
](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp) or find it in the
`samples/cpp/tutorial_code/core/file_input_output/file_input_output.cpp` of the OpenCV source code
library.

2
doc/tutorials/core/how_to_scan_images/how_to_scan_images.markdown
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@@ -51,7 +51,7 @@ three major ways of going through an image pixel by pixel. To make things a litt
will make the scanning for each image using all of these methods, and print out how long it took.
You can download the full source code [here
](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/how_to_scan_images/how_to_scan_images.cpp) or look it up in
the samples directory of OpenCV at the cpp tutorial code for the core section. Its basic usage is:
@code{.bash}
how_to_scan_images imageName.jpg intValueToReduce [G]

2
doc/tutorials/core/how_to_use_ippa_conversion/how_to_use_ippa_conversion.markdown
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@@ -16,7 +16,7 @@ Code
You may also find the source code in the
`samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp` file of the OpenCV source library or
download it from [here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
download it from [here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/ippasync/ippasync_sample.cpp).
@include cpp/tutorial_code/core/ippasync/ippasync_sample.cpp

4
doc/tutorials/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.markdown
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@@ -85,7 +85,7 @@ L = Mat(pI);
A case study
------------
Now that you have the basics done [here's](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
Now that you have the basics done [here's](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
an example that mixes the usage of the C interface with the C++ one. You will also find it in the
sample directory of the OpenCV source code library at the
`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp` .
@@ -132,7 +132,7 @@ output:
You may observe a runtime instance of this on the [YouTube
here](https://www.youtube.com/watch?v=qckm-zvo31w) and you can [download the source code from here
](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp)
or find it in the
`samples/cpp/tutorial_code/core/interoperability_with_OpenCV_1/interoperability_with_OpenCV_1.cpp`
of the OpenCV source code library.

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doc/tutorials/core/mat-mask-operations/mat_mask_operations.markdown
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@@ -133,7 +133,7 @@ For example:
![](images/resultMatMaskFilter2D.png)
You can download this source code from [here
](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp) or look in the
OpenCV source code libraries sample directory at
`samples/cpp/tutorial_code/core/mat_mask_operations/mat_mask_operations.cpp`.

2
doc/tutorials/core/mat_the_basic_image_container/mat_the_basic_image_container.markdown
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@@ -258,7 +258,7 @@ OpenCV offers support for output of other common OpenCV data structures too via
![](images/MatBasicContainerOut15.png)
Most of the samples here have been included in a small console application. You can download it from
[here](https://github.com/Itseez/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
[here](https://github.com/opencv/opencv/tree/master/samples/cpp/tutorial_code/core/mat_the_basic_image_container/mat_the_basic_image_container.cpp)
or in the core section of the cpp samples.
You can also find a quick video demonstration of this on