<commit_before>        VisionGL

The objective of this library is to provide an easy way to prototype and 
implement image and video processing functions in CUDA and GLSL. The library
provides wrapper code generators for both CUDA and GLSL languages. 

The wrapper functions are generated in C++ from the shader code, written 
in either CUDA or GLSL. The shader code must contain three types of 
directives in comments:
1 - Documentation comment: a multiple line comment between /** and */
    This comment is copied ipsis literis to the output files.
2 - Declaration comment: a single line comment describing the parameter 
    list of the wrapper function. The list has variable name, type, and, when  
    it is an image, semantics indicating if it is an input or output image.
3 - Attribution comment: single line comments associating variables in C++
    to its counterparts in GLSL or CUDA

The wrapper functions use a common variable type to store image data, called 
VglImage. It contains space to store the image data in RAM, and handles to 
store the image in both CUDA and OpenGL contexts. These contexts are used 
under demand. If the image is used only in OpenGL context, the CUDA handle 
will be empty (NULL or -1) and vice-versa.


        Compilation

The library requires OpenCV 2.4.0 or superior, CUDA 4 or superior, 
GLEW 1.6 or superior and freeglut 3 or superior. OpenGL is also required!

To install GLEW:
apt-get install libglew1.6 libglew1.6-dev

To install freeglut:
apt-get install freeglut3 freeglut3-dev

To install OpenCV:
apt-get install libopencv-dev


        Compilation using cmake
On Linux:
		
Go to the root directory of the project and run:
cmake .
make

On Windows:

Go to the root directory of the project and run:
cmake .

Depending on what generator you have configured it'll create a solution or
a project or a MinGW Makefile. Only tested with Microsoft Visual Studio 2010
as generator. In this case, a solution will be built using the name "visiongl",
just open the solution as usual on Visual Studio, and compile it, you're done.

If you're willing to use Visual Studio 2010 as generator, use the following command:

cmake . -G "Visual Studio 10"

        Compilation using Makefile_linux

Please open Makefile_linux and edit the variables OPENCV_PATH, CUDA_PATH, 
referring to the paths where OpenCV and CUDA are installed. Edit also
INSTALL_PATH, referring to the path where the library and its include files
will be installed.

To build the library:
make -f Makefile_linux all

To install the library to INSTALL_PATH
make -f Makefile_linux install

To build the demos:
make -f Makefile_linux democam
make -f Makefile_linux demofrac
make -f Makefile_linux demobenchmark

To run the demos:
make -f Makefile_linux rundemocam
make -f Makefile_linux rundemofrac
make -f Makefile_linux rundemobenchmark

To build the documentation:
build dox

To generate wrapper code after some shader is modified:
make -f Makefile_linux frag
make -f Makefile_linux frag_bg
make -f Makefile_linux frag_stereo
make -f Makefile_linux frag_diffeq
make -f Makefile_linux cuda

        Compilation with GDCM

Please download gdcm-2.4.2 source code or later. It is available in: 
http://sourceforge.net/projects/gdcm/files/gdcm%202.x/GDCM%202.4.2/

Set the options below as follows:
GDCM_BUILD_SHARED_LIBS: ON
CMAKE_INSTALL_PREFFIX: /usr/local/gdcm

Optionally, set also
GDCM_BUILD_APPLICATIONS: ON

Then run:
make
sudo make install

To compile VisionGL with support to GDCM, please set WITH_GDCM = 1 in 
the VisionGL makefile.

        Compilation with DCMTK

Please download dcmtk-3.6.1_20131114 source code or later, available in:
http://sourceforge.net/projects/gdcm/files/gdcm%202.x/GDCM%202.4.2/

Set the options below as follows:
GDCM_BUILD_SHARED_LIBS: ON
CMAKE_INSTALL_PREFFIX: /usr/local/dcmtk

Then run:
make
sudo make install

To compile VisionGL with support to GDCM, please set WITH_DCMTK = 1 in 
the VisionGL makefile.

        About the demos

demofrac: Probably the most basic demo. Does not require any aditional 
library besides the minimum. Use the arrows in the numpad to navigate,
 z/x to zoom in/out, and q to quit. 
 
democam: Another basic demo that does not require aditional libraries.
Captures images from the first webcam found. The capture is done by 
OpenCV function cvCaptureFromCAM. An OpenGL window shows four versions 
of the captured image after a few operations.

demogdcm: To run this example, please compile VisionGL with
GDCM support. In a previous section there are instructions about how
to compile GDCM.

demodcmtk: To run this example, please compile VisionGL with
DCMTK support. In a previous section there are instructions about how
to compile DCMTK.

demogdcm: To run this example, please compile VisionGL with
GDCM support.

demobenchmark: This demo is composed by three programs.
 - demobenchmark_cv: The simplest one, requires OpenCV.
 - demobenchmark_cl: To run this example, please compile VisionGL with
                     OpenCL support.
 - demobenchmark_cvocl: To run this example, please compile OpenCV with
                     OpenCL support. Download OpenCV and look for the 
                     folder modules/ocl. It may be not present in the
                     master branch from the git repository, but it is 
                     present in the 2.4.8 and 2.4.9 tags. Get OpenCV
                     with git by running:

                     git clone https://github.com/Itseez/opencv.git
                     git checkout 2.4.9

References

[1] <NAME>, <NAME>
Automatic generation of wrapper code for video processing functions
Learning and Nonlinear models, Vol 9, Num 2, 2011
http://www.deti.ufc.br/~lnlm/papers/vol9-no2-art5.pdf
<commit_msg>Modified README.txt. Corrected links and added comments about demos.<commit_after>        VisionGL

The objective of this library is to provide an easy way to prototype and 
implement image and video processing functions in CUDA and GLSL. The library
provides wrapper code generators for both CUDA and GLSL languages. 

The wrapper functions are generated in C++ from the shader code, written 
in either CUDA or GLSL. The shader code must contain three types of 
directives in comments:
1 - Documentation comment: a multiple line comment between /** and */
    This comment is copied ipsis literis to the output files.
2 - Declaration comment: a single line comment describing the parameter 
    list of the wrapper function. The list has variable name, type, and, when  
    it is an image, semantics indicating if it is an input or output image.
3 - Attribution comment: single line comments associating variables in C++
    to its counterparts in GLSL or CUDA

The wrapper functions use a common variable type to store image data, called 
VglImage. It contains space to store the image data in RAM, and handles to 
store the image in both CUDA and OpenGL contexts. These contexts are used 
under demand. If the image is used only in OpenGL context, the CUDA handle 
will be empty (NULL or -1) and vice-versa.


        Compilation

The library requires OpenCV 2.4.0 or superior, CUDA 4 or superior, 
GLEW 1.6 or superior and freeglut 3 or superior. OpenGL is also required!

To install GLEW:
apt-get install libglew1.6 libglew1.6-dev

To install freeglut:
apt-get install freeglut3 freeglut3-dev

To install OpenCV:
apt-get install libopencv-dev


        Compilation using cmake
On Linux:
		
Go to the root directory of the project and run:
cmake .
make

On Windows:

Go to the root directory of the project and run:
cmake .

Depending on the compiler you have installed, cmake will create a solution,
a project or a MinGW Makefile. The generator works with Microsoft Visual 
Studio 2010. In this case, a solution will be built using the name "visiongl",
just open the solution as usual on Visual Studio, and compile it, you're done.

If you want to use Visual Studio 2010, use the following command:

cmake . -G "Visual Studio 10"

        Compilation using Makefile_linux

Please open Makefile_linux and edit the variables OPENCV_PATH, CUDA_PATH, 
referring to the paths where OpenCV and CUDA are installed. Edit also
INSTALL_PATH, referring to the path where the library and its include files
will be installed.

To build the library:
make -f Makefile_linux all

To install the library to INSTALL_PATH
make -f Makefile_linux install

To build the demos:
make -f Makefile_linux democam
make -f Makefile_linux demofrac
make -f Makefile_linux demobenchmark

To run the demos:
make -f Makefile_linux rundemocam
make -f Makefile_linux rundemofrac
make -f Makefile_linux rundemobenchmark

To build the documentation:
build dox

To generate wrapper code after some shader is modified:
make -f Makefile_linux frag
make -f Makefile_linux frag_bg
make -f Makefile_linux frag_stereo
make -f Makefile_linux frag_diffeq
make -f Makefile_linux cuda

        Compilation with GDCM

Please download gdcm-2.4.2 source code or later. It is available in: 
http://sourceforge.net/projects/gdcm/files/gdcm%202.x/GDCM%202.4.2/

Set the options below as follows:
GDCM_BUILD_SHARED_LIBS: ON
CMAKE_INSTALL_PREFFIX: /usr/local/gdcm

Optionally, set also
GDCM_BUILD_APPLICATIONS: ON

Then run:
make
sudo make install

To compile VisionGL with support to GDCM, please set WITH_GDCM = 1 in 
the VisionGL makefile.

        Compilation with DCMTK

Please download dcmtk-3.6.1_20131114 source code or later, available in:
http://dicom.offis.de/download/dcmtk/snapshot/

Set the options below as follows:
GDCM_BUILD_SHARED_LIBS: ON
CMAKE_INSTALL_PREFFIX: /usr/local/dcmtk

Then run:
make
sudo make install

To compile VisionGL with support to DCMTK, please set WITH_DCMTK = 1 in 
the VisionGL makefile.

        About the demos

demofrac: Probably the most basic demo. Does not require any aditional 
library besides the minimum. Use the arrows in the numpad to navigate,
 z/x to zoom in/out, and q to quit. 
 
democam: Another basic demo that does not require aditional libraries.
Captures images from the first webcam found. The capture is done by 
OpenCV function cvCaptureFromCAM. An OpenGL window shows four versions 
of the captured image after a few operations.

demogdcm: To run this example, please compile VisionGL with
GDCM support. In a previous section there are instructions about how
to compile GDCM.

demodcmtk: To run this example, please compile VisionGL with
DCMTK support. In a previous section there are instructions about how
to compile DCMTK.

demobenchmark: This demo is composed by three programs.
 - demobenchmark_cv: The simplest one, requires OpenCV.
 - demobenchmark_cl: To run this example, please compile VisionGL with
                     OpenCL support.
 - demobenchmark_cvocl: To run this example, please compile OpenCV with
                     OpenCL support. Download OpenCV and look for the 
                     folder modules/ocl. It may be not present in the
                     master branch from the git repository, but it is 
                     present in the 2.4.8 and 2.4.9 tags. Get OpenCV
                     with git by running:

                     git clone https://github.com/Itseez/opencv.git
                     git checkout 2.4.9

 - demobenchmark_cl3d: To run this example, please compile VisionGL with
                     OpenCL support.
                     Your device must support the extension
                     cl_khr_3d_image_writes. This extension is available 
                     in most AMD video cards. Please use the function 
                     clGetDeviceInfo with the option CL_DEVICE_EXTENSIONS
                     to check the extension availability. An alternative is 
                     to look for the card model in compupench.org and look 
                     for the card details.

References

[1] <NAME>, <NAME>
Automatic generation of wrapper code for video processing functions
Learning and Nonlinear models, Vol 9, Num 2, 2011
https://www.academia.edu/4367451/Automatic_generation_of_wrapper_code_for_video_processing_functions
http://www.deti.ufc.br/~lnlm/papers/vol9-no2-art5.pdf

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