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Fixed several opencv version references

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This commit is contained in:
Andrey Kamaev 2012-07-02 15:40:18 +00:00
parent 81a5415417
commit de153f0154
5 changed files with 239 additions and 239 deletions
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2
android/service/doc/JavaHelper.rst
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@ -14,7 +14,7 @@ boolean initDebug()
-------------------
.. method:: static boolean initDebug()
Load and initialize OpenCV library from current application package. Roughly it is analog of system.loadLibrary("opencv_java")
:rtype: boolean

2
cmake/OpenCVConfig.cmake
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@ -150,7 +150,7 @@ if(OpenCV_LIB_PATH AND EXISTS "${OpenCV_LIB_PATH}/OpenCVConfig.cmake")
endif()
else()
if(NOT OpenCV_FIND_QUIETLY)
message(WARNING "Found OpenCV 2.4.0 Windows Super Pack but it has not binaries compatible with your configuration.
message(WARNING "Found OpenCV 2.4.2 Windows Super Pack but it has not binaries compatible with your configuration.
You should manually point CMake variable OpenCV_DIR to your build of OpenCV library.")
endif()
set(OpenCV_FOUND FALSE CACHE BOOL "" FORCE)

142
doc/tutorials/introduction/android_binary_package/android_binary_package.rst
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@ -5,14 +5,14 @@
Using Android binary package with Eclipse
*****************************************
This tutorial was tested using Ubuntu 10.04 and Windows 7 SP1 operating systems.
Nevertheless, it should also work on any other **OS**\ es supported by Android SDK (including Mac OS X).
This tutorial was tested using Ubuntu 10.04 and Windows 7 SP1 operating systems.
Nevertheless, it should also work on any other **OS**\ es supported by Android SDK (including Mac OS X).
If you encounter errors after following the steps described here, feel free to contact us via `android-opencv <https://groups.google.com/group/android-opencv/>`_ discussion group and we will try to help you.
Quick environment setup for Android development
===============================================
If you are making a clean environment installation then you can try `Tegra Android Development Pack <http://developer.nvidia.com/tegra-android-development-pack>`_
If you are making a clean environment installation then you can try `Tegra Android Development Pack <http://developer.nvidia.com/tegra-android-development-pack>`_
(**TADP**) released by **NVIDIA**:
It will cover all of the environment set up automatically and you can go to the next step :ref:`Get_the_OpenCV_package_for_Android_development` right after automatic setup.
@ -20,7 +20,7 @@ It will cover all of the environment set up automatically and you can go to the
If you are a beginner in Android development then we recommentd you to start with TADP.
.. note:: *NVIDIA*\ 's Tegra Android Development Pack includes some special features for |Nvidia_Tegra_Platform|_ but it is not just for *Tegra* devices
+ You need at least *1.6 Gb* free disk space for installation.
+ TADP will download Android SDK platforms and Android NDK from Google's server, so you need an Internet connection for the installation.
@ -37,7 +37,7 @@ If you are a beginner in Android development then we recommentd you to start wit
.. |Tegra_Ventana_Development_Kit| replace:: Tegra Ventana Development Kit
.. _Tegra_Ventana_Development_Kit: http://developer.nvidia.com/tegra-ventana-development-kit
.. _Android_Environment_Setup_Lite:
.. _Android_Environment_Setup_Lite:
Manual environment setup for Android Development
================================================
@ -48,7 +48,7 @@ You need the following tools to be installed:
Visit `Java SE Downloads page <http://www.oracle.com/technetwork/java/javase/downloads/>`_ and download installer for your OS.
Here is a detailed :abbr:`JDK (Java Development Kit)` `installation guide <http://source.android.com/source/initializing.html#installing-the-jdk>`_
Here is a detailed :abbr:`JDK (Java Development Kit)` `installation guide <http://source.android.com/source/initializing.html#installing-the-jdk>`_
for Ubuntu and Mac OS (only JDK sections are applicable for OpenCV)
.. note:: OpenJDK is not usable for Android development because Android SDK supports only Sun JDK.
@ -76,7 +76,7 @@ You need the following tools to be installed:
.. code-block:: bash
sudo yum install libXtst.i386
sudo yum install libXtst.i386
#. **Android SDK components**
@ -91,21 +91,21 @@ You need the following tools to be installed:
The minimal platform supported by OpenCV Java API is **Android 2.2** (API 8). This is also the minimum API Level required for the provided samples to run.
See the ``<uses-sdk android:minSdkVersion="8"/>`` tag in their **AndroidManifest.xml** files.
But for successful compilation of some samples the **target** platform should be set to Android 3.0 (API 11) or higher. It will not block them from running on Android 2.2+.
.. image:: images/android_sdk_and_avd_manager.png
:height: 500px
:height: 500px
:alt: Android SDK Manager
:align: center
See `Adding SDK Components <http://developer.android.com/sdk/adding-components.html>`_ for help with installing/updating SDK components.
#. **Eclipse IDE**
Check the `Android SDK System Requirements <http://developer.android.com/sdk/requirements.html>`_ document for a list of Eclipse versions that are compatible with the Android SDK.
Check the `Android SDK System Requirements <http://developer.android.com/sdk/requirements.html>`_ document for a list of Eclipse versions that are compatible with the Android SDK.
For OpenCV 2.4.x we recommend Eclipse 3.7 (Indigo) or later versions. They work well for OpenCV under both Windows and Linux.
If you have no Eclipse installed, you can get it from the `download page <http://www.eclipse.org/downloads/>`_.
#. **ADT plugin for Eclipse**
This instruction is copied from `Android Developers site <http://developer.android.com/sdk/eclipse-adt.html>`_.
@ -122,14 +122,14 @@ You need the following tools to be installed:
#. Click :guilabel:`OK`
.. note:: If you have trouble acquiring the plugin, try using "http" in the Location URL, instead of "https" (https is preferred for security reasons).
#. In the :guilabel:`Available Software` dialog, select the checkbox next to :guilabel:`Developer Tools` and click :guilabel:`Next`.
#. In the next window, you'll see a list of the tools to be downloaded. Click :guilabel:`Next`.
#. Read and accept the license agreements, then click :guilabel:`Finish`.
.. note:: If you get a security warning saying that the authenticity or validity of the software can't be established, click :guilabel:`OK`.
#. When the installation completes, restart Eclipse.
#. When the installation completes, restart Eclipse.
.. _Get_the_OpenCV_package_for_Android_development:
@ -151,15 +151,15 @@ Get the OpenCV package for Android development
:align: center
On Unix you can also use the following command:
.. code-block:: bash
tar -jxvf ~/Downloads/OpenCV-2.4.1-android-bin2.tar.bz2
tar -jxvf ~/Downloads/OpenCV-2.4.2-android-sdk.tar.bz2
For this tutorial I have unpacked OpenCV to the :file:`C:\\Work\\android-opencv\\` directory.
.. |opencv_android_bin_pack| replace:: OpenCV-2.4.1-android-bin2.tar.bz2
.. _opencv_android_bin_pack_url: http://sourceforge.net/projects/opencvlibrary/files/opencv-android/2.4.1/OpenCV-2.4.1-android-bin2.tar.bz2/download
.. |opencv_android_bin_pack| replace:: OpenCV-2.4.2-android-sdk.tar.bz2
.. _opencv_android_bin_pack_url: http://sourceforge.net/projects/opencvlibrary/files/opencv-android/2.4.2/OpenCV-2.4.2-android-sdk.tar.bz2/download
.. |opencv_android_bin_pack_url| replace:: |opencv_android_bin_pack|
.. |seven_zip| replace:: 7-Zip
.. _seven_zip: http://www.7-zip.org/
@ -184,15 +184,15 @@ Open OpenCV library and samples in Eclipse
:align: center
Select :guilabel:`Use existing SDKs` option, browse for Android SDK folder and click :guilabel:`Finish`.
To make sure the SDK folder is set correctly do the following step taken from `Configuring the ADT Plugin <http://developer.android.com/sdk/eclipse-adt.html#configuring>`_ document from *Google*:
* Select :menuselection:`Window --> Preferences...` to open the Preferences panel (Mac OS X: :menuselection:`Eclipse --> Preferences`):
.. image:: images/eclipse_2_window_preferences.png
:alt: Select Window > Preferences...
:align: center
* Select :guilabel:`Android` from the left panel.
You may see a dialog asking whether you want to send usage statistics to *Google*. If so, make your choice and click :guilabel:`Proceed`. You cannot continue with this procedure until you click :guilabel:`Proceed`.
@ -203,10 +203,10 @@ Open OpenCV library and samples in Eclipse
:alt: Select Android from the left panel
:align: center
* For the SDK Location in the main panel, click :guilabel:`Browse...` and locate your Android SDK directory.
* For the SDK Location in the main panel, click :guilabel:`Browse...` and locate your Android SDK directory.
* Click :guilabel:`Apply` button at the bottom right corner of main panel.
If the SDK folder is already set correctly you'll see something like this:
.. image:: images/eclipse_4_locate_sdk.png
@ -219,10 +219,10 @@ Open OpenCV library and samples in Eclipse
OpenCV library is packed as a ready-for-use `Android Library Project
<http://developer.android.com/guide/developing/projects/index.html#LibraryProjects>`_. You can simply reference it in your projects.
Each sample included into |opencv_android_bin_pack| is a regular Android project that already references OpenCV library.
Follow next steps to import OpenCV and samples into workspace:
* Right click on the :guilabel:`Package Explorer` window and choose :guilabel:`Import...` option from the context menu:
.. image:: images/eclipse_5_import_command.png
@ -242,7 +242,7 @@ Open OpenCV library and samples in Eclipse
:align: center
* Click :guilabel:`Finish` button to complete the import operation.
After clicking :guilabel:`Finish` button Eclipse will load all selected projects into workspace. And... will indicate numerous errors:
.. image:: images/eclipse_8_false_alarm.png
@ -250,9 +250,9 @@ Open OpenCV library and samples in Eclipse
:align: center
However **all these errors are only false-alarms**!
To help Eclipse to understand that there are no any errors choose OpenCV library in :guilabel:`Package Explorer` (left mouse click) and press :kbd:`F5` button on your keyboard. Then choose any sample (except first samples in *Tutorial Base* and *Tutorial Advanced*) and also press :kbd:`F5`.
Sometimes more advanced manipulations are needed:
* The provided projects are configured for `android-11` target that can be missing platform in your Android SDK. After right click on any project select :guilabel:`Properties` and then :guilabel:`Android` on the left pane. Click some target with `API Level` 11 or higher:
@ -266,7 +266,7 @@ Open OpenCV library and samples in Eclipse
.. image:: images/eclipse_8b_fix_props.png
:alt: Fixing project properties
:align: center
After this manipulation Eclipse will rebuild your workspace and error icons will disappear one after another:
.. image:: images/eclipse_9_errors_dissapearing.png
@ -309,11 +309,11 @@ Well, running samples from Eclipse is very simple:
:align: center
* Select the :guilabel:`Android Application` option and click :guilabel:`OK` button. Eclipse will install and run the sample.
Here is ``Tutorial 1 - Add OpenCV`` sample detecting edges using Canny algorithm from OpenCV:
.. image:: images/emulator_canny.png
:height: 600px
:height: 600px
:alt: Tutorial 1 Basic - 1. Add OpenCV - running Canny
:align: center
@ -325,7 +325,7 @@ Application development with async initialization
Using async initialization is a preferred way for application Development. It uses OpenCV Manager service to get OpenCV libraries.
#. Add OpenCV library project to your workspace. Go to :guilabel:`File –> Import –> Existing project in your workspace`, push Browse button and select OpenCV SDK path.
#. Add OpenCV library project to your workspace. Go to :guilabel:`File –> Import –> Existing project in your workspace`, push Browse button and select OpenCV SDK path.
.. image:: images/eclipse_opencv_dependency0.png
:alt: Add dependency from OpenCV library
@ -349,55 +349,55 @@ There is a very base code snippet for Async init. It shows only basis principles
.. code-block:: java
:linenos:
public class MyActivity extends Activity implements HelperCallbackInterface
{
private BaseLoaderCallback mOpenCVCallBack = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
// Create and set View
mView = new puzzle15View(mAppContext);
setContentView(mView);
} break;
default:
{
super.onManagerConnected(status);
} break;
}
}
};
private BaseLoaderCallback mOpenCVCallBack = new BaseLoaderCallback(this) {
@Override
public void onManagerConnected(int status) {
switch (status) {
case LoaderCallbackInterface.SUCCESS:
{
Log.i(TAG, "OpenCV loaded successfully");
// Create and set View
mView = new puzzle15View(mAppContext);
setContentView(mView);
} break;
default:
{
super.onManagerConnected(status);
} break;
}
}
};
/** Called when the activity is first created. */
@Override
public void onCreate(Bundle savedInstanceState)
{
Log.i(TAG, "onCreate");
super.onCreate(savedInstanceState);
Log.i(TAG, "Trying to load OpenCV library");
if (!OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_0, this, mOpenCVCallBack))
{
Log.e(TAG, "Cannot connect to OpenCV Manager");
}
}
/** Called when the activity is first created. */
@Override
public void onCreate(Bundle savedInstanceState)
{
Log.i(TAG, "onCreate");
super.onCreate(savedInstanceState);
// ...
Log.i(TAG, "Trying to load OpenCV library");
if (!OpenCVLoader.initAsync(OpenCVLoader.OPENCV_VERSION_2_4_0, this, mOpenCVCallBack))
{
Log.e(TAG, "Cannot connect to OpenCV Manager");
}
}
// ...
}
It this case application works with OpenCV Manager in asynchronous fashion. OnManagerConnected callback will be called in UI thread, when initialization finishes.
It this case application works with OpenCV Manager in asynchronous fashion. OnManagerConnected callback will be called in UI thread, when initialization finishes.
Attention, It is not allowed to use CV calls or load OpenCV-dependent native libs before invoking this callback. Load your own native libraries after OpenCV initialization.
Application development with static initialization
--------------------------------------------------
In this way of using OpenCV all OpenCV binaries a linked and put to your application package. It is designed for experimental and local development purposes only.
In this way of using OpenCV all OpenCV binaries a linked and put to your application package. It is designed for experimental and local development purposes only.
This way is depricated for production code. If you want to publish your app use approach with async initialization.
#. Add OpenCV library project to your workspace. Go to :guilabel:`File –> Import –> Existing project in your workspace`, push Browse button and select OpenCV SDK path.
#. Add OpenCV library project to your workspace. Go to :guilabel:`File –> Import –> Existing project in your workspace`, push Browse button and select OpenCV SDK path.
.. image:: images/eclipse_opencv_dependency0.png
:alt: Add dependency from OpenCV library

56
doc/tutorials/introduction/android_binary_package/android_binary_package_using_with_NDK.rst
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@ -8,16 +8,16 @@ Using C++ OpenCV code with Android binary package
The Android way is writing all your code in Java. But somethimes it is not enough and you need to go to a native level and write part of your application in C/C++.
This is important when you already have some computer vision functionality which is written in C++ and uses OpenCV, and you want to use it in your Android application,
but do not want to rewrite the C++ code to Java.
In this case the only way is to use JNI mechanism.
but do not want to rewrite the C++ code to Java.
In this case the only way is to use JNI mechanism.
It means, that you should add a class with native methods wrapping your C++ functionality into the Java part of your Android application.
This tutorial describes a fast way how to create and build Android applications containing OpenCV code written in C++. It shows how to build an application which uses OpenCV inside its JNI calls.
Please note that before starting this tutorial you should fulfill all the steps, described in the tutorial :ref:`Android_Binary_Package`.
This tutorial was tested using Ubuntu 10.04 and Windows 7 SP1 operating systems.
Nevertheless, it should also work on Mac OS X. If you encounter errors after following the steps described here, feel free to contact us via
This tutorial was tested using Ubuntu 10.04 and Windows 7 SP1 operating systems.
Nevertheless, it should also work on Mac OS X. If you encounter errors after following the steps described here, feel free to contact us via
`android-opencv <https://groups.google.com/group/android-opencv/>`_ discussion group and we will try to help you.
@ -32,10 +32,10 @@ To install Android NDK just extract the archive to some folder on your computer.
.. note:: Before start you can read official Android NDK documentation which is in the Android NDK archive, in the folder :file:`docs/`.
The main article about using Android NDK build system you can read in the file :file:`ANDROID-MK.html`.
The main article about using Android NDK build system you can read in the file :file:`ANDROID-MK.html`.
Also some additional useful information you can read in the files
:file:`APPLICATION-MK.html`, :file:`NDK-BUILD.html`, and in the files :file:`CPU-ARM-NEON.html`, :file:`CPLUSPLUS-SUPPORT.html`, :file:`PREBUILTS.html`.
:file:`APPLICATION-MK.html`, :file:`NDK-BUILD.html`, and in the files :file:`CPU-ARM-NEON.html`, :file:`CPLUSPLUS-SUPPORT.html`, :file:`PREBUILTS.html`.
Theory: Android application structure
=====================================
@ -67,22 +67,22 @@ where
+ the :file:`libs` folder will contain native libraries after successful build,
+ and the :file:`jni` folder contains C/C++ application source code and NDK's build scripts :file:`Android.mk` and :file:`Application.mk`.
These scripts control the C++ build process (they are written in Makefile language).
These scripts control the C++ build process (they are written in Makefile language).
Also the root folder should contain the following files
Also the root folder should contain the following files
* :file:`AndroidManifest.xml` file presents essential information about application to the Android system
(name of the Application, name of main application's package, components of the application, required permissions, etc)
* :file:`AndroidManifest.xml` file presents essential information about application to the Android system
(name of the Application, name of main application's package, components of the application, required permissions, etc)
It can be created using Eclipse wizard or :command:`android` tool from Android SDK
* :file:`project.properties` is a text file containing information about target Android platform and other build details.
This file is generated by Eclipse or can be created with :command:`android` tool from Android SDK
.. note:: Both files (:file:`AndroidManifest.xml` and :file:`project.properties`) are required to compile the C++ part of the application (NDK build system uses information from these files). If any of these files does not exist, compile the Java part of the project before the C++ part.
.. note:: Both files (:file:`AndroidManifest.xml` and :file:`project.properties`) are required to compile the C++ part of the application (NDK build system uses information from these files). If any of these files does not exist, compile the Java part of the project before the C++ part.
.. _NDK_build_cli:
@ -90,7 +90,7 @@ Also the root folder should contain the following files
Theory: How to build Android application having C++ native part (from command line)
===================================================================================
Here is the standard way to compile C++ part of an Android application:
Here is the standard way to compile C++ part of an Android application:
#. Open console and go to the root folder of Android application
@ -114,7 +114,7 @@ Here is the standard way to compile C++ part of an Android application:
#. After executing this command the C++ part of the source code is compiled.
After that the Java part of the application can be (re)compiled (using either *Eclipse* or :command:`ant` build tool).
After that the Java part of the application can be (re)compiled (using either *Eclipse* or :command:`ant` build tool).
.. note:: Some parameters can be set for the :command:`ndk-build`:
@ -148,18 +148,18 @@ We recommend the approach based on Eclipse :abbr:`CDT(C/C++ Development Tooling)
To install the `CDT plugin <http://eclipse.org/cdt/>`_ use menu ``Help`` -> ``Install New Software...``,
then paste the CDT 8.0 repository URL http://download.eclipse.org/tools/cdt/releases/indigo as shown on the picture below and click :guilabel:`Add...`, name it *CDT* and click :guilabel:`OK`.
.. image:: images/eclipse_inst_cdt.png
:alt: Configure builders
:align: center
``CDT Main Features`` should be enough:
.. image:: images/eclipse_inst_cdt_2.png
:alt: Configure builders
:align: center
.. important:: OpenCV 2.4.2 for Android package contains samples projects pre-configured to use CDT Builder for JNI part build via ``ndk-build``.
#. Define the ``NDKROOT`` environment variable containing the path to Android NDK in your system (e.g. **"X:\\Apps\\android-ndk-r8"** or **"/opt/android-ndk-r8"**)
@ -174,13 +174,13 @@ then paste the CDT 8.0 repository URL http://download.eclipse.org/tools/cdt/rele
#. Use menu :guilabel:`Project` -> :guilabel:`Clean...` to make sure that NDK build is invoked on the project build:
.. image:: images/eclipse_ndk_build.png
:alt: Select resources folder to refresh automatically
:alt: Select resources folder to refresh automatically
:align: center
Theory: The structure of :file:`Android.mk` and :file:`Application.mk` scripts
==============================================================================
The script :file:`Android.mk` usually have the following structure:
The script :file:`Android.mk` usually have the following structure:
.. code-block:: make
@ -211,7 +211,7 @@ Practice: Build samples from OpenCV binary package
OpenCV binary package includes 3 samples having JNI resources:
* *Tutorial 3 (Advanced) - Add Native OpenCV*
This sample illustrates how you can use OpenCV in C++ but without OpenCV Java API.
* *Tutorial 4 (Advanced) - Mix Java+Native OpenCV*
@ -221,7 +221,7 @@ OpenCV binary package includes 3 samples having JNI resources:
* *Sample - face-detection*
This sample illustrates usage of both simple OpenCV face detector via Java API and advanced detection based face tracker via JNI and C++.
.. important:: Before OpenCV **2.4.2** for Android these projects were not configured to use CDT for building their native part , so you can do it yourself.
Practice: Create an Android application, which uses OpenCV
@ -238,7 +238,7 @@ To build your own Android application, which uses OpenCV from native part, the f
For detailed information see the Android NDK documentation from the Android NDK archive, in the file
:file:`<path_where_NDK_is_placed>/docs/ANDROID-MK.html`
#. The line
#. The line
.. code-block:: make
@ -274,15 +274,15 @@ To build your own Android application, which uses OpenCV from native part, the f
.. code-block:: make
APP_STL := gnustl_static
APP_STL := gnustl_static
APP_CPPFLAGS := -frtti -fexceptions
Also the line
.. code-block:: make
APP_ABI := armeabi-v7a
APP_ABI := armeabi-v7a
is recommended for the applications targeting modern ARMs
is recommended for the applications targeting modern ARMs
#. Either use :ref:`manual <NDK_build_cli>` ``ndk-build`` invocation or :ref:`setup Eclipse CDT Builder <Android_NDK_integration_with_Eclipse>` to build native JNI lib before Java part [re]build and APK creation.

276
doc/tutorials/introduction/windows_install/windows_install.rst
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@ -7,47 +7,47 @@ Installation in Windows
The description here was tested by the author using the Windows 7 SP1 **o**\ perating **s**\ ystem (*OS*). Nevertheless, it should also work on any other Windows OS too. If you encounter errors after following the steps described here feel free to contact us via our :opencv_group:`user group <>` and we will try to fix your problem.
.. note:: To use the OpenCV library you have two options: :ref:`Windows_Install_Prebuild` or :ref:`CppTutWindowsMakeOwn`. While the first one is easier to complete, it only works if you are coding inside the latest Microsoft Visual Studio **i**\ ntegrated **d**\ evelopment **e**\ nvironments (*IDE*) and doesn't takes advantage of the most novel technologies we integrate into our library.
.. note:: To use the OpenCV library you have two options: :ref:`Windows_Install_Prebuild` or :ref:`CppTutWindowsMakeOwn`. While the first one is easier to complete, it only works if you are coding inside the latest Microsoft Visual Studio **i**\ ntegrated **d**\ evelopment **e**\ nvironments (*IDE*) and doesn't takes advantage of the most novel technologies we integrate into our library.
.. _Windows_Install_Prebuild:
.. _Windows_Install_Prebuild:
Installation by using the pre-built libraries
=============================================
1. Open up a web browser and go to: http://sourceforge.net/projects/opencvlibrary/files/opencv-win/
#. Open the folder for the latest version (currently this is 2.4.1).
#. Open the folder for the latest version (currently this is 2.4.2).
#. Choose a build you want to use and download it. The naming conventions used will show what kind of support they offer. For example:
.. container:: enumeratevisibleitemswithsquare
* *vs2010* means the Visual Studio
* *vs2010* means the Visual Studio
* *win32* means that it is for 32 bit applications in the OS
* *gpu* means that it includes the support for using your GPU in order to further increase the performance of the library).
If you downloaded the source files present here see :ref:`CppTutWindowsMakeOwn`.
#. Make sure you have admin rights. Start the setup and follow the wizard. Agree to the \" License Agreement \" .
#. Make sure you have admin rights. Start the setup and follow the wizard. Agree to the \" License Agreement \" .
#. While adding the OpenCV library to the system path is a good decision for a better control of this we will do it manually. Therefore, make sure you do not set this option.
#. While adding the OpenCV library to the system path is a good decision for a better control of this we will do it manually. Therefore, make sure you do not set this option.
#. Most of the time it is a good idea to install the source files as this will allow for you to debug into the OpenCV library, if it is necessary. Therefore, just follow the default settings of the wizard and finish the installation.
#. Most of the time it is a good idea to install the source files as this will allow for you to debug into the OpenCV library, if it is necessary. Therefore, just follow the default settings of the wizard and finish the installation.
#. You can check the installation at the chosen path as you can see below.
#. You can check the installation at the chosen path as you can see below.
.. image:: images/OpenCV_Install_Directory.png
:alt: An example of how the installation directory should look in case of success.
:align: center
#. To finalize the installation go to the :ref:`WindowsSetPathAndEnviromentVariable` section.
#. To finalize the installation go to the :ref:`WindowsSetPathAndEnviromentVariable` section.
.. _CppTutWindowsMakeOwn:
.. _CppTutWindowsMakeOwn:
Installation by making your own libraries from the source files
===============================================================
You may find the content of this tutorial also inside the following videos: `Part 1 <https://www.youtube.com/watch?v=NnovZ1cTlMs>`_ and `Part 2 <https://www.youtube.com/watch?v=qGNWMcfWwPU>`_, hosted on YouTube.
You may find the content of this tutorial also inside the following videos: `Part 1 <https://www.youtube.com/watch?v=NnovZ1cTlMs>`_ and `Part 2 <https://www.youtube.com/watch?v=qGNWMcfWwPU>`_, hosted on YouTube.
.. raw:: html
@ -60,10 +60,10 @@ If you are building your own libraries you can take either the source files from
.. container:: enumeratevisibleitemswithsquare
+ stable and tested build - http://code.opencv.org/svn/opencv/tags/2.4.1 (the number at the end will change with every new realease, so change it to that)
+ stable and tested build - http://code.opencv.org/svn/opencv/tags/2.4.2 (the number at the end will change with every new realease, so change it to that)
+ development build - http://code.opencv.org/svn/opencv/trunk/
While the later one may contain a couple of new and experimental algorithms, performance increases and interface improvements, be aware, that it may also contain some bugs. Using the first one is recommended in most of the cases. That is unless you are extending the OpenCV library itself or really need the most up to date version of it.
While the later one may contain a couple of new and experimental algorithms, performance increases and interface improvements, be aware, that it may also contain some bugs. Using the first one is recommended in most of the cases. That is unless you are extending the OpenCV library itself or really need the most up to date version of it.
Building the OpenCV library from scratch requires a couple of tools installed beforehand:
@ -79,7 +79,7 @@ Building the OpenCV library from scratch requires a couple of tools installed be
.. _IntelTBB: http://threadingbuildingblocks.org/file.php?fid=77
.. |IntelIIP| replace:: Intel |copy| Integrated Performance Primitives (*IPP*)
.. _IntelIIP: http://software.intel.com/en-us/articles/intel-ipp/
.. |qtframework| replace:: Qt framework
.. |qtframework| replace:: Qt framework
.. _qtframework: http://qt.nokia.com/downloads
.. |Eigen| replace:: Eigen
.. _Eigen: http://eigen.tuxfamily.org/index.php?title=Main_Page#Download
@ -96,246 +96,246 @@ Building the OpenCV library from scratch requires a couple of tools installed be
.. container:: enumeratevisibleitemswithsquare
+ An **I**\ ntegrated **D**\ eveloper **E**\ nviroment (*IDE*) preferably, or just a C\C++ compiler that will actually make the binary files. Here I will use the `Microsoft Visual Studio <https://www.microsoft.com/visualstudio/en-us>`_. Nevertheless, you can use any other *IDE* that has a valid C\\C++ compiler.
+ Then |CMake|_ is a neat tool that will make the project files (for your choosen *IDE*) from the OpenCV source files. It will also allow an easy configuration of the OpenCV build files, in order to make binary files that fits exactly to your needs.
+ An **I**\ ntegrated **D**\ eveloper **E**\ nviroment (*IDE*) preferably, or just a C\C++ compiler that will actually make the binary files. Here I will use the `Microsoft Visual Studio <https://www.microsoft.com/visualstudio/en-us>`_. Nevertheless, you can use any other *IDE* that has a valid C\\C++ compiler.
+ Then |CMake|_ is a neat tool that will make the project files (for your choosen *IDE*) from the OpenCV source files. It will also allow an easy configuration of the OpenCV build files, in order to make binary files that fits exactly to your needs.
+ A **S**\ ubversion **C**\ ontrol **S**\ ystem (*SVN*) to acquire the OpenCV source files. A good tool for this is |TortoiseSVN|_. Alternatively, you can just download an archived version of the source files from the `Sourceforge OpenCV page <http://sourceforge.net/projects/opencvlibrary/files/opencv-win/>`_.
OpenCV may come in multiple flavors. There is a "core" section that will work on its own. Nevertheless, they are a couple of tools, libraries made by other organizations (so called 3rd parties) that offer services of which the OpenCV may take advantage. These will improve in many ways its capabilities. In order to use any of them, you need to download and install them on your system.
OpenCV may come in multiple flavors. There is a "core" section that will work on its own. Nevertheless, they are a couple of tools, libraries made by other organizations (so called 3rd parties) that offer services of which the OpenCV may take advantage. These will improve in many ways its capabilities. In order to use any of them, you need to download and install them on your system.
.. container:: enumeratevisibleitemswithsquare
+ The |Python_Libraries|_ are required to build the *Python interface* of OpenCV. For now use the version :file:`2.7.{x}`. This is also a must have if you want to build the *OpenCV documentation*.
+ |Numpy|_ is a scientific computing package for Python. Required for the *Python interface*.
+ |Numpy|_ is a scientific computing package for Python. Required for the *Python interface*.
+ |IntelTBB|_ is used inside OpenCV for parallel code snippets. Using this will make sure that the OpenCV library will take advantage of all the cores you have in your systems CPU.
+ |IntelTBB|_ is used inside OpenCV for parallel code snippets. Using this will make sure that the OpenCV library will take advantage of all the cores you have in your systems CPU.
+ |IntelIIP|_ may be used to improve the performance of color conversion, Haar training and DFT functions of the OpenCV library. Watch out as this isn't a *free* service.
+ |IntelIIP|_ may be used to improve the performance of color conversion, Haar training and DFT functions of the OpenCV library. Watch out as this isn't a *free* service.
+ OpenCV offers a somewhat fancier and more useful graphical user interface, than the default one by using the |qtframework|_. For a quick overview of what this has to offer look into the documentations *highgui* module, under the *Qt New Functions* section. Version 4.6 or later of the framework is required.
+ OpenCV offers a somewhat fancier and more useful graphical user interface, than the default one by using the |qtframework|_. For a quick overview of what this has to offer look into the documentations *highgui* module, under the *Qt New Functions* section. Version 4.6 or later of the framework is required.
+ |Eigen|_ is a C++ template library for linear algebra.
+ |Eigen|_ is a C++ template library for linear algebra.
+ The latest |CUDA_Toolkit|_ will allow you to use the power lying inside your GPU. This will drastically improve performance for some of the algorithms, like the HOG descriptor. Getting to work more and more of our algorithms on the GPUs is a constant effort of the OpenCV team.
+ The latest |CUDA_Toolkit|_ will allow you to use the power lying inside your GPU. This will drastically improve performance for some of the algorithms, like the HOG descriptor. Getting to work more and more of our algorithms on the GPUs is a constant effort of the OpenCV team.
+ |OpenEXR|_ source files are required for the library to work with this high dynamic range (HDR) image file format.
+ |OpenEXR|_ source files are required for the library to work with this high dynamic range (HDR) image file format.
+ The |OpenNI_Framework|_ contains a set of open source APIs that provide support for natural interaction with devices via methods such as voice command recognition, hand gestures and body motion tracking.
+ The |OpenNI_Framework|_ contains a set of open source APIs that provide support for natural interaction with devices via methods such as voice command recognition, hand gestures and body motion tracking.
+ |Miktex|_ is the best `TEX <https://secure.wikimedia.org/wikipedia/en/wiki/TeX>`_ implementation on the Windows OS. It is required to build the *OpenCV documentation*.
+ |Miktex|_ is the best `TEX <https://secure.wikimedia.org/wikipedia/en/wiki/TeX>`_ implementation on the Windows OS. It is required to build the *OpenCV documentation*.
+ |Sphinx|_ is a python documentation generator and is the tool that will actually create the *OpenCV documentation*. This on its own requires a couple of tools installed, I will cover this in depth at the :ref:`How to Install Sphinx <HereInstallSphinx>` section.
+ |Sphinx|_ is a python documentation generator and is the tool that will actually create the *OpenCV documentation*. This on its own requires a couple of tools installed, I will cover this in depth at the :ref:`How to Install Sphinx <HereInstallSphinx>` section.
Now I will describe the steps to follow for a full build (using all the above frameworks, tools and libraries). If you do not need the support for some of these you can just freely skip those parts.
Now I will describe the steps to follow for a full build (using all the above frameworks, tools and libraries). If you do not need the support for some of these you can just freely skip those parts.
.. _WindowsBuildLibrary:
Building the library
^^^^^^^^^^^^^^^^^^^^
1. Make sure you have a working IDE with a valid compiler. In case of the Microsoft Visual Studio just install it and make sure it starts up.
1. Make sure you have a working IDE with a valid compiler. In case of the Microsoft Visual Studio just install it and make sure it starts up.
#. Install |CMake|_. Simply follow the wizard, no need to add it to the path. The default install options are great. No need to change them.
#. Install |CMake|_. Simply follow the wizard, no need to add it to the path. The default install options are great. No need to change them.
#. Install |TortoiseSVN|_. Choose the 32 or 64 bit version according to the type of OS you work in. Again follow the wizard, default options are good. Restart of your system is required.
#. Install |TortoiseSVN|_. Choose the 32 or 64 bit version according to the type of OS you work in. Again follow the wizard, default options are good. Restart of your system is required.
#. Choose a directory in your file system where you will download the OpenCV libraries. I recommend creating a new one that has short path and no special charachters in it, for example :file:`D:/OpenCV`. During this tutorial I'll suppose you've done so. If you use a different directory just change this front part of the path in my future examples. Then, :menuselection:`Right Click --> SVN Checkout...` in the directory.
#. Choose a directory in your file system where you will download the OpenCV libraries. I recommend creating a new one that has short path and no special charachters in it, for example :file:`D:/OpenCV`. During this tutorial I'll suppose you've done so. If you use a different directory just change this front part of the path in my future examples. Then, :menuselection:`Right Click --> SVN Checkout...` in the directory.
.. image:: images/TortoiseSVNCheckout.png
:alt: The TortoiseSVN Checkout Menu
:align: center
A window will appear where you can select from what repository you want to download source files (1) and to which directory (2):
.. image:: images/TortoiseSVNCheckoutWindow.png
:alt: The TortoiseSVN Checkout Window
:align: center
Add here either ones of the versions described above. Then push the OK button and be patient as the repository currently is over 330MB to download. It will take some time until it is finished depending on your Internet connection.
Add here either ones of the versions described above. Then push the OK button and be patient as the repository currently is over 330MB to download. It will take some time until it is finished depending on your Internet connection.
.. image:: images/SVNCheckOutProgress.png
:alt: The TortoiseSVN Checkout Progress
:align: center
When you are done you should have a *opencv* and an *opencv_extra* directory as seen at (3).
When you are done you should have a *opencv* and an *opencv_extra* directory as seen at (3).
#. In this section I will cover installing the 3rd party libraries.
a) Download the |Python_Libraries|_ and install it with the default options. You will need a couple other python extensions. Luckily installing all these may be automated by a nice tool called `Setuptools <http://pypi.python.org/pypi/setuptools#downloads>`_. Download and install again.
#) .. _HereInstallSphinx:
#) .. _HereInstallSphinx:
Installing Sphinx is easy once you have installed *Setuptools*. This contains a little application that will automatically connect to the python databases and download the latest version of many python scripts. Start up a command window (enter *cmd* into the windows start menu and press enter) and use the *CD* command to navigate to your Python folders Script sub-folder. Here just pass to the *easy_install.exe* as argument the name of the program you want to install. Add the *sphinx* argument.
Installing Sphinx is easy once you have installed *Setuptools*. This contains a little application that will automatically connect to the python databases and download the latest version of many python scripts. Start up a command window (enter *cmd* into the windows start menu and press enter) and use the *CD* command to navigate to your Python folders Script sub-folder. Here just pass to the *easy_install.exe* as argument the name of the program you want to install. Add the *sphinx* argument.
.. image:: images/cmsdstartwindows.jpg
:alt: The Windows Command Startup
:align: center
.. image:: images/Sphinx_Install.png
:alt: How to start the command window
:align: center
.. note::
The *CD* navigation command works only inside a drive. For example if you are somewhere in the *C:* drive you cannot use it this to go to another drive (like for example *D:*). To do so you first need to change drives letters. For this simply enter the command *D:*. Then you can use the *CD* to navigate to specific folder inside the drive. Bonus tip: you can clear the screen by using the *CLS* command.
.. note::
This will also install its prerequisites `Jinja2 <http://jinja.pocoo.org/docs/>`_ and `Pygments <http://pygments.org/>`_.
The *CD* navigation command works only inside a drive. For example if you are somewhere in the *C:* drive you cannot use it this to go to another drive (like for example *D:*). To do so you first need to change drives letters. For this simply enter the command *D:*. Then you can use the *CD* to navigate to specific folder inside the drive. Bonus tip: you can clear the screen by using the *CLS* command.
This will also install its prerequisites `Jinja2 <http://jinja.pocoo.org/docs/>`_ and `Pygments <http://pygments.org/>`_.
#) The easiest way to install |Numpy|_ is to just download its binaries from the `sourceforga page <http://sourceforge.net/projects/numpy/files/NumPy/>`_. Make sure your download and install exactly the binary for your python version (so for version :file:`2.7`).
#) Download the |Miktex|_ and install it. Again just follow the wizard. At the fourth step make sure you select for the *"Install missing packages on-the-fly"* the *Yes* option, as you can see on the image below. Again this will take quite some time so be patient.
#) Download the |Miktex|_ and install it. Again just follow the wizard. At the fourth step make sure you select for the *"Install missing packages on-the-fly"* the *Yes* option, as you can see on the image below. Again this will take quite some time so be patient.
.. image:: images/MiktexInstall.png
:alt: The Miktex Install Screen
:align: center
#) For the |IntelTBB|_ download the source files and extract it inside a directory on your system. For example let there be :file:`D:/OpenCV/dep`. For installing the |IntelIIP|_ the story is the same. For exctracting the archives I recommend using the `7-Zip <http://www.7-zip.org/>`_ application.
#) For the |IntelTBB|_ download the source files and extract it inside a directory on your system. For example let there be :file:`D:/OpenCV/dep`. For installing the |IntelIIP|_ the story is the same. For exctracting the archives I recommend using the `7-Zip <http://www.7-zip.org/>`_ application.
.. image:: images/IntelTBB.png
:alt: The Miktex Install Screen
:align: center
#) In case of the |Eigen|_ library it is again a case of download and extract to the :file:`D:/OpenCV/dep` directory.
#) Same as above with |OpenEXR|_.
#) Same as above with |OpenEXR|_.
#) For the |OpenNI_Framework|_ you need to install both the `development build <http://www.openni.org/downloadfiles/opennimodules/openni-binaries/21-stable>`_ and the `PrimeSensor Module <http://www.openni.org/downloadfiles/opennimodules/openni-compliant-hardware-binaries/32-stable>`_.
#) For the CUDA you need again two modules: the latest |CUDA_Toolkit|_ and the *CUDA Tools SDK*. Download and install both of them with a *complete* option by using the 32 or 64 bit setups according to your OS.
#) In case of the |qtframework|_ you need to build yourself the binary files (unless you use the Microsoft Visual Studio 2008 with 32 bit compiler). To do this go to the `Qt Downloads <http://qt.nokia.com/downloads>`_ page. Download the source files (not the installers!!!):
.. image:: images/qtDownloadThisPackage.png
:alt: Download this Qt Package
:align: center
Extract it into a nice and short named directory like :file:`D:/OpenCV/dep/qt/` .
Then you need to build it. Start up a *Visual* *Studio* *Command* *Prompt* (*2010*) by using the start menu search (or navigate through the start menu :menuselection:`All Programs --> Microsoft Visual Studio 2010 --> Visual Studio Tools --> Visual Studio Command Prompt (2010)`).
Extract it into a nice and short named directory like :file:`D:/OpenCV/dep/qt/` .
Then you need to build it. Start up a *Visual* *Studio* *Command* *Prompt* (*2010*) by using the start menu search (or navigate through the start menu :menuselection:`All Programs --> Microsoft Visual Studio 2010 --> Visual Studio Tools --> Visual Studio Command Prompt (2010)`).
.. image:: images/visualstudiocommandprompt.jpg
:alt: The Visual Studio command prompt
:align: center
Now navigate to the extracted folder and enter inside it by using this console window. You should have a folder containing files like *Install*, *Make* and so on. Use the *dir* command to list files inside your current directory. Once arrived at this directory enter the following command:
Now navigate to the extracted folder and enter inside it by using this console window. You should have a folder containing files like *Install*, *Make* and so on. Use the *dir* command to list files inside your current directory. Once arrived at this directory enter the following command:
.. code-block:: bash
configure.exe -release -no-webkit -no-phonon -no-phonon-backend -no-script -no-scripttools
configure.exe -release -no-webkit -no-phonon -no-phonon-backend -no-script -no-scripttools
-no-qt3support -no-multimedia -no-ltcg
Completing this will take around 10-20 minutes. Then enter the next command that will take a lot longer (can easily take even more than a full hour):
.. code-block:: bash
nmake
After this set the Qt enviroment variables using the following command on Windows 7:
.. code-block:: bash
setx -m QTDIR D:/OpenCV/dep/qt/qt-everywhere-opensource-src-4.7.3
.. |PathEditor| replace:: Path Editor
.. _PathEditor: http://www.redfernplace.com/software-projects/patheditor/
Also, add the built binary files path to the system path by using the |PathEditor|_. In our case this is :file:`D:/OpenCV/dep/qt/qt-everywhere-opensource-src-4.7.3/bin`.
.. note::
If you plan on doing Qt application development you can also install at this point the *Qt Visual Studio Add-in*. After this you can make and build Qt applications without using the *Qt Creator*. Everything is nicely integrated into Visual Studio.
#. Now start the *CMake (cmake-gui)*. You may again enter it in the start menu search or get it from the :menuselection:`All Programs --> CMake 2.8 --> CMake (cmake-gui)`. First, select the directory for the source files of the OpenCV library (1). Then, specify a directory where you will build the binary files for OpenCV (2).
Also, add the built binary files path to the system path by using the |PathEditor|_. In our case this is :file:`D:/OpenCV/dep/qt/qt-everywhere-opensource-src-4.7.3/bin`.
.. note::
If you plan on doing Qt application development you can also install at this point the *Qt Visual Studio Add-in*. After this you can make and build Qt applications without using the *Qt Creator*. Everything is nicely integrated into Visual Studio.
#. Now start the *CMake (cmake-gui)*. You may again enter it in the start menu search or get it from the :menuselection:`All Programs --> CMake 2.8 --> CMake (cmake-gui)`. First, select the directory for the source files of the OpenCV library (1). Then, specify a directory where you will build the binary files for OpenCV (2).
.. image:: images/CMakeSelectBin.jpg
:alt: Select the directories
:align: center
Press the Configure button to specify the compiler (and *IDE*) you want to use. Note that in case you can choose between different compilers for making either 64 bit or 32 bit libraries. Select the one you use in your application development.
Press the Configure button to specify the compiler (and *IDE*) you want to use. Note that in case you can choose between different compilers for making either 64 bit or 32 bit libraries. Select the one you use in your application development.
.. image:: images/CMake_Configure_Windows.jpg
:alt: How CMake should look at build time.
:alt: How CMake should look at build time.
:align: center
CMake will start out and based on your system variables will try to automatically locate as many packages as possible. You can modify the packages to use for the build in the :menuselection:`WITH --> WITH_X` menu points (where *X* is the package abbreviation). Here are a list of current packages you can turn on or off:
CMake will start out and based on your system variables will try to automatically locate as many packages as possible. You can modify the packages to use for the build in the :menuselection:`WITH --> WITH_X` menu points (where *X* is the package abbreviation). Here are a list of current packages you can turn on or off:
.. image:: images/CMakeBuildWithWindowsGUI.jpg
:alt: The packages OpenCV may use
:align: center
Select all the packages you want to use and press again the *Configure* button. For an easier overview of the build options make sure the *Grouped* option under the binary directory selection is turned on. For some of the packages CMake may not find all of the required files or directories. In case of these CMake will throw an error in its output window (located at the bottom of the GUI) and set its field values, to not found constants. For example:
Select all the packages you want to use and press again the *Configure* button. For an easier overview of the build options make sure the *Grouped* option under the binary directory selection is turned on. For some of the packages CMake may not find all of the required files or directories. In case of these CMake will throw an error in its output window (located at the bottom of the GUI) and set its field values, to not found constants. For example:
.. image:: images/CMakePackageNotFoundWindows.jpg
:alt: Constant for not found packages
:align: center
.. image:: images/CMakeOutputPackageNotFound.jpg
:alt: Error (warning) thrown in output window of the CMake GUI
:align: center
For these you need to manually set the queried directories or files path. After this press again the *Configure* button to see if the value entered by you was accepted or not. Do this until all entries are good and you cannot see errors in the field/value or the output part of the GUI.
Now I want to emphasize an option that you will definitely love: :menuselection:`ENABLE --> ENABLE_SOLUTION_FOLDERS`. OpenCV will create many-many projects and turning this option will make sure that they are categorized inside directories in the *Solution Explorer*. It is a must have feature, if you ask me.
Now I want to emphasize an option that you will definitely love: :menuselection:`ENABLE --> ENABLE_SOLUTION_FOLDERS`. OpenCV will create many-many projects and turning this option will make sure that they are categorized inside directories in the *Solution Explorer*. It is a must have feature, if you ask me.
.. image:: images/CMakeBuildOptionsOpenCV.jpg
:alt: Set the Solution Folders and the parts you want to build
:align: center
Furthermore, you need to select what part of OpenCV you want to build.
.. container:: enumeratevisibleitemswithsquare
+ *BUILD_DOCS* -> It creates two projects for building the documentation of OpenCV (there will be a separate project for building the HTML and the PDF files). Note that these aren't built together with the solution. You need to make an explicit build project command on these to do so.
+ *BUILD_EXAMPLES* -> OpenCV comes with many example applications from which you may learn most of the libraries capabilities. This will also come handy to easily try out if OpenCV is fully functional on your computer.
+ *BUILD_PACKAGE* -> Prior to version 2.3 with this you could build a project that will build an OpenCV installer. With this you can easily install your OpenCV flavor on other systems. For the latest source files of OpenCV it generates a new project that simply creates zip archive with OpenCV sources.
+ *BUILD_SHARED_LIBS* -> With this you can control to build DLL files (when turned on) or static library files (\*.lib) otherwise.
+ *BUILD_TESTS* -> Each module of OpenCV has a test project assigned to it. Building these test projects is also a good way to try out, that the modules work just as expected on your system too.
+ *BUILD_PERF_TESTS* -> There are also performance tests for many OpenCV functions. If you're concerned about performance, build them and run.
+ *BUILD_opencv_python* -> Self-explanatory. Create the binaries to use OpenCV from the Python language.
+ *BUILD_EXAMPLES* -> OpenCV comes with many example applications from which you may learn most of the libraries capabilities. This will also come handy to easily try out if OpenCV is fully functional on your computer.
+ *BUILD_PACKAGE* -> Prior to version 2.3 with this you could build a project that will build an OpenCV installer. With this you can easily install your OpenCV flavor on other systems. For the latest source files of OpenCV it generates a new project that simply creates zip archive with OpenCV sources.
+ *BUILD_SHARED_LIBS* -> With this you can control to build DLL files (when turned on) or static library files (\*.lib) otherwise.
+ *BUILD_TESTS* -> Each module of OpenCV has a test project assigned to it. Building these test projects is also a good way to try out, that the modules work just as expected on your system too.
+ *BUILD_PERF_TESTS* -> There are also performance tests for many OpenCV functions. If you're concerned about performance, build them and run.
+ *BUILD_opencv_python* -> Self-explanatory. Create the binaries to use OpenCV from the Python language.
Press again the *Configure* button and ensure no errors are reported. If this is the case you can tell CMake to create the project files by pushing the *Generate* button. Go to the build directory and open the created **OpenCV** solution.
Depending on just how much of the above options you have selected the solution may contain quite a lot of projects so be tolerant on the IDE at the startup.
Depending on just how much of the above options you have selected the solution may contain quite a lot of projects so be tolerant on the IDE at the startup.
Now you need to build both the *Release* and the *Debug* binaries. Use the drop-down menu on your IDE to change to another of these after building for one of them.
.. image:: images/ChangeBuildVisualStudio.jpg
:alt: Look here for changing the Build Type
:align: center
In the end you can observe the built binary files inside the bin directory:
.. image:: images/OpenCVBuildResultWindows.jpg
:alt: The Result of the build.
:alt: The Result of the build.
:align: center
For the documentation you need to explicitly issue the build commands on the *doc* project for the PDF files and on the *doc_html* for the HTML ones. Each of these will call *Sphinx* to do all the hard work. You can find the generated documentation inside the :file:`Build/Doc/_html` for the HTML pages and within the :file:`Build/Doc` the PDF manuals.
For the documentation you need to explicitly issue the build commands on the *doc* project for the PDF files and on the *doc_html* for the HTML ones. Each of these will call *Sphinx* to do all the hard work. You can find the generated documentation inside the :file:`Build/Doc/_html` for the HTML pages and within the :file:`Build/Doc` the PDF manuals.
.. image:: images/WindowsBuildDoc.png
:alt: The Documentation Projects
:align: center
To collect the header and the binary files, that you will use during your own projects, into a separate directory (simillary to how the pre-built binaries ship) you need to explicitely build the *Install* project.
To collect the header and the binary files, that you will use during your own projects, into a separate directory (simillary to how the pre-built binaries ship) you need to explicitely build the *Install* project.
.. image:: images/WindowsBuildInstall.png
:alt: The Install Project
:align: center
This will create an *install* directory inside the *Build* one collecting all the built binaries into a single place. Use this only after you built both the *Release* and *Debug* versions.
This will create an *install* directory inside the *Build* one collecting all the built binaries into a single place. Use this only after you built both the *Release* and *Debug* versions.
.. note::
To create an installer you need to install `NSIS <http://nsis.sourceforge.net/Download>`_. Then just build the *Package* project to build the installer into the :file:`Build/_CPack_Packages/{win32}/NSIS` folder. You can then use this to distribute OpenCV with your build settings on other systems.
.. image:: images/WindowsOpenCVInstaller.png
:alt: The Installer directory
:align: center
To test your build just go into the :file:`Build/bin/Debug` or :file:`Build/bin/Release` directory and start a couple of applications like the *contours.exe*. If they run, you are done. Otherwise, something definitely went awfully wrong. In this case you should contact us via our :opencv_group:`user group <>`.
If everything is okay the *contours.exe* output should resemble the following image (if built with Qt support):
To test your build just go into the :file:`Build/bin/Debug` or :file:`Build/bin/Release` directory and start a couple of applications like the *contours.exe*. If they run, you are done. Otherwise, something definitely went awfully wrong. In this case you should contact us via our :opencv_group:`user group <>`.
If everything is okay the *contours.exe* output should resemble the following image (if built with Qt support):
.. image:: images/WindowsQtContoursOutput.png
:alt: A good output result
:align: center
.. note::
If you use the GPU module (CUDA libraries) make sure you also upgrade to the latest drivers of your GPU. Error messages containing invalid entries in (or cannot find) the nvcuda.dll are caused mostly by old video card drivers. For testing the GPU (if built) run the *performance_gpu.exe* sample application.
@ -351,7 +351,7 @@ First we set an enviroment variable to make easier our work. This will hold the
setx -m OPENCV_DIR D:\OpenCV\Build\Install
Here the directory is where you have your OpenCV binaries (*installed* or *built*). Inside this you should have folders like *bin* and *include*. The -m should be added if you wish to make the settings computer wise, instead of user wise.
Here the directory is where you have your OpenCV binaries (*installed* or *built*). Inside this you should have folders like *bin* and *include*. The -m should be added if you wish to make the settings computer wise, instead of user wise.
If you built static libraries then you are done. Otherwise, you need to add the *bin* folders path to the systems path.This is cause you will use the OpenCV library in form of *\"Dynamic-link libraries\"* (also known as **DLL**). Inside these are stored all the algorithms and information the OpenCV library contains. The operating system will load them only on demand, during runtime. However, to do this he needs to know where they are. The systems **PATH** contains a list of folders where DLLs can be found. Add the OpenCV library path to this and the OS will know where to look if he ever needs the OpenCV binaries. Otherwise, you will need to copy the used DLLs right beside the applications executable file (*exe*) for the OS to find it, which is highly unpleasent if you work on many projects. To do this start up again the |PathEditor|_ and add the following new entry (right click in the application to bring up the menu):
@ -360,13 +360,13 @@ If you built static libraries then you are done. Otherwise, you need to add the
%OPENCV_DIR%\bin
.. image:: images/PathEditorOpenCVInsertNew.png
:alt: Right click to insert new path manually.
:alt: Right click to insert new path manually.
:align: center
.. image:: images/PathEditorOpenCVSetPath.png
:alt: Add the entry.
:alt: Add the entry.
:align: center
Save it to the registry and you are done. If you ever change the location of your install directories or want to try out your applicaton with a different build all you will need to do is to update the OPENCV_DIR variable via the *setx* command inside a command window.
Save it to the registry and you are done. If you ever change the location of your install directories or want to try out your applicaton with a different build all you will need to do is to update the OPENCV_DIR variable via the *setx* command inside a command window.
Now you can continue reading the tutorials with the :ref:`Windows_Visual_Studio_How_To` section. There you will find out how to use the OpenCV library in your own projects with the help of the Microsoft Visual Studio IDE.
Now you can continue reading the tutorials with the :ref:`Windows_Visual_Studio_How_To` section. There you will find out how to use the OpenCV library in your own projects with the help of the Microsoft Visual Studio IDE.