Qt wiki will be updated on October 12th 2023 starting at 11:30 AM (EEST) and the maintenance will last around 2-3 hours. During the maintenance the site will be unavailable.
OpenCV with Qt: Difference between revisions
Jump to navigation
Jump to search
No edit summary |
No edit summary |
||
| Line 1: | Line 1: | ||
'''OpenCV''' is a cross-platform, open-source, commonly used computer vision library. It uses C++ as its primary interface, but other languages such as C and Python can also be used. OpenCV was originally developed by Intel back in 1999 and is now maintained by Willow Garage and ItSeez. | '''OpenCV''' is a cross-platform, open-source, commonly used computer vision library. It uses C++ as its primary interface, but other languages such as C and Python can also be used. OpenCV was originally developed by Intel back in 1999 and is now maintained by Willow Garage and ItSeez. | ||
OpenCV was originally written in C for maximum performance and portability. | OpenCV was originally written in C for maximum performance and portability. | ||
OpenCV v2.0 was released in October of 2009 and includes major improvements in C++ interface. | |||
Latest releases introduced support to GPU calculation (CUDA, OpenCL), Android platform, iOS platform and Linux Embedded platforms. | Latest releases introduced support to GPU calculation (CUDA, OpenCL), Android platform, iOS platform and Linux Embedded platforms. | ||
OpenCV main strengths are computational efficiency with a focus on near-real-time applications. | OpenCV main strengths are computational efficiency with a focus on near-real-time applications. | ||
This makes OpenCV perfectly suitable for writing applications on mobile platforms such as robots and cell phones. | |||
Face recognition, Object Identification and Augmented Reality are some of the examples of OpenCV usage. | Face recognition, Object Identification and Augmented Reality are some of the examples of OpenCV usage. | ||
'''Installation guides''' | '''Installation guides''' | ||
Installers for Linux, Mac and Windows are readily available "here":http://opencv.org/downloads.html. | |||
* "Linux installation guide":http://docs.opencv.org/doc/tutorials/introduction/linux_install/linux_install.html?highlight=installation | |||
* "Windows installation guide":http://docs.opencv.org/doc/tutorials/introduction/windows_install/windows_install.html?highlight=installation | |||
'''Documentation''' | '''Documentation''' | ||
* "Official documentation":http://docs.opencv.org/ | |||
* For more in-depth info about OpenCV there's a 500+ page book published by O'REILLY about OpenCV 2.0 "Learning OpenCV: Computer Vision with the OpenCV Library":http://www.amazon.com/dp/0596516134 | |||
* Packt Publishing realized a lot of good book "available here":http://www.packtpub.com/books?keys=opencv. | |||
'''Tutorials''' | '''Tutorials''' | ||
There is an open source Widget based on OpenGL available on an italian blog (English tutorial and documentation available): | |||
* "Part 1: base tutorial":http://www.robot-home.it/blog/software/tutorial-opencv-qt-opengl-widget-per-visualizzare-immagini-da-opencv-in-una-gui-con-qt/?lang=en | |||
* "Part 2: how to use":http://www.robot-home.it/blog/software/tutorial-opencv-qt-opengl-widget-per-visualizzare-immagini-da-opencv-in-una-gui-con-qt-seconda-parte/?lang=en | |||
'''Qt based demos''' | '''Qt based demos''' | ||
* "Image Compression":http://www.robot-home.it/blog/software/tutorial-opencv-qt-comprimere-un-immagine-in-memoria/?lang=en | |||
Revision as of 08:50, 25 February 2015
OpenCV is a cross-platform, open-source, commonly used computer vision library. It uses C++ as its primary interface, but other languages such as C and Python can also be used. OpenCV was originally developed by Intel back in 1999 and is now maintained by Willow Garage and ItSeez.
OpenCV was originally written in C for maximum performance and portability. OpenCV v2.0 was released in October of 2009 and includes major improvements in C++ interface.
Latest releases introduced support to GPU calculation (CUDA, OpenCL), Android platform, iOS platform and Linux Embedded platforms.
OpenCV main strengths are computational efficiency with a focus on near-real-time applications. This makes OpenCV perfectly suitable for writing applications on mobile platforms such as robots and cell phones.
Face recognition, Object Identification and Augmented Reality are some of the examples of OpenCV usage.
Installation guides Installers for Linux, Mac and Windows are readily available "here":http://opencv.org/downloads.html.
- "Linux installation guide":http://docs.opencv.org/doc/tutorials/introduction/linux_install/linux_install.html?highlight=installation
- "Windows installation guide":http://docs.opencv.org/doc/tutorials/introduction/windows_install/windows_install.html?highlight=installation
Documentation
- "Official documentation":http://docs.opencv.org/
- For more in-depth info about OpenCV there's a 500+ page book published by O'REILLY about OpenCV 2.0 "Learning OpenCV: Computer Vision with the OpenCV Library":http://www.amazon.com/dp/0596516134
- Packt Publishing realized a lot of good book "available here":http://www.packtpub.com/books?keys=opencv.
Tutorials There is an open source Widget based on OpenGL available on an italian blog (English tutorial and documentation available):
- "Part 1: base tutorial":http://www.robot-home.it/blog/software/tutorial-opencv-qt-opengl-widget-per-visualizzare-immagini-da-opencv-in-una-gui-con-qt/?lang=en
- "Part 2: how to use":http://www.robot-home.it/blog/software/tutorial-opencv-qt-opengl-widget-per-visualizzare-immagini-da-opencv-in-una-gui-con-qt-seconda-parte/?lang=en
Qt based demos