OpenCV
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| - | * Web site: | + | * Web site: http://sourceforge.net/projects/opencvlibrary/ |
| - | * Described version: | + | * Described version: 2.3.0 |
| - | * Licensing: | + | * Licensing: BSD license |
* User documentation: link | * User documentation: link | ||
* Download: link | * Download: link | ||
| Line 12: | Line 12: | ||
== Summary == | == Summary == | ||
| - | + | Computer vision is everywhere-in security systems, manufacturing inspection systems, | |
| + | medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps | ||
| + | and Google Earth together, checks the pixels on LCD screens, and makes sure the | ||
| + | stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer | ||
| + | vision framework and a comprehensive library with more than 500 functions that can run vision code in real time. Thus OpenCV (Open Source Computer Vision) is a library of | ||
| + | programming functions for real time computer vision. OpenCV is written in C/C++ and | ||
| + | Python and more recently supports GPUs. More specifically, the OpenCV GPU module is a | ||
| + | set of classes and functions that utilize GPU computational capabilities. It is | ||
| + | implemented using NVidia CUDA Runtime API, so only that vendor GPUs are supported. | ||
| + | It includes utility functions, low level vision primitives as well as high level algorithms. | ||
| + | The module is being developed as power infrastructure for fast vision algorithms building | ||
| + | on GPU with some high level state of the art functionality. The CPU version of the library | ||
| + | is employs a TBB parallelization strategy. | ||
== Features == | == Features == | ||
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== HP-SEE Applications == | == HP-SEE Applications == | ||
| - | * | + | * Within the HP-SEE virtual research communities, the OpenCV library is used by the UPB |
| + | team in the development of the EagleEye project, implementing Feature Extraction from | ||
| + | Satellite Images Using Hybrid Computing Architectures – CPU-GPU. Also we can | ||
| + | envisage a joint usage of OpenCV features with the Computer Science Department from | ||
| + | the West University of Timisoara, and the Romanian Institute for Space Sciences for | ||
| + | satellite image processing and manipulation. | ||
== Resource Centers == | == Resource Centers == | ||
| - | * | + | * '''NCIT-Cluster''', RO |
== Usage by Other Projects and Communities == | == Usage by Other Projects and Communities == | ||
Revision as of 22:49, 29 June 2011
Contents |
- Web site: http://sourceforge.net/projects/opencvlibrary/
- Described version: 2.3.0
- Licensing: BSD license
- User documentation: link
- Download: link
- Source code: link
Authors/Maintainers
- Also origin, if the software comes from a specific project.
Summary
Computer vision is everywhere-in security systems, manufacturing inspection systems, medical image analysis, Unmanned Aerial Vehicles, and more. It stitches Google maps and Google Earth together, checks the pixels on LCD screens, and makes sure the stitches in your shirt are sewn properly. OpenCV provides an easy-to-use computer vision framework and a comprehensive library with more than 500 functions that can run vision code in real time. Thus OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer vision. OpenCV is written in C/C++ and Python and more recently supports GPUs. More specifically, the OpenCV GPU module is a set of classes and functions that utilize GPU computational capabilities. It is implemented using NVidia CUDA Runtime API, so only that vendor GPUs are supported. It includes utility functions, low level vision primitives as well as high level algorithms. The module is being developed as power infrastructure for fast vision algorithms building on GPU with some high level state of the art functionality. The CPU version of the library is employs a TBB parallelization strategy.
Features
- Listed features
Architectural/Functional Overview
- high level design info, how it works, performance - may be a link, or several links
Usage Overview
- If possible with small example - may be a link
Dependacies
- list of all relevant dependencies on other libraries
HP-SEE Applications
- Within the HP-SEE virtual research communities, the OpenCV library is used by the UPB
team in the development of the EagleEye project, implementing Feature Extraction from Satellite Images Using Hybrid Computing Architectures – CPU-GPU. Also we can envisage a joint usage of OpenCV features with the Computer Science Department from the West University of Timisoara, and the Romanian Institute for Space Sciences for satellite image processing and manipulation.
Resource Centers
- NCIT-Cluster, RO
Usage by Other Projects and Communities
- If any
Recommendations for Configuration and Usage
Please describe here any common settings, configurations or conventions that would make the usage of this resource (library or tool) more interoperable or scalable across the HP-SEE resources. These recommendations should include anything that is related to the resource and is agreed upon by administrators and users, or across sites and applications. These recommendations should emerge from questions or discussions opened by site administrators or application developers, at any stage, including installation, development, usage, or adaptation for another HPC centre.
Provided descriptions should describe general or site specific aspects of resource installation, configuration and usage, or describe the guidelines or convention for deploying or using the resource within the local (user/site) or temporary environment (job). Examples are:
- Common configuration settings of execution environment
- Filesystem path or local access string
- Environment variables to be set or used by applications
- Options (e.g. additional modules) that are needed or required by applications and should be present
- Minimum quantitative values (e.g. quotas) offered by the site
- Location and format of some configuration or usage hint instructing applications on proper use of the resource or site specific policy
- Key installation or configuration settings that should be set to a common value, or locally tweaked by local site admins
- Conventions for application or job bound installation and usage of the resource
