Search Results for "gpu processing" - Page 2
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Showing 43 open source projects for "gpu processing"
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openExposureFusion
HDR images generation from bracketed LDR images
Create HDR images from a series of images taken with different exposures. Use your GPU to accelerate the process and view the results in real time. OpenCL support is REQUIRED. -
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gpuip
Framework for Image Processing on the GPU
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away3d-core-fp11
Away3D engine for Flash Player 11
Away3D Core FP11 is a real-time 3D graphics engine for Flash Player 11 that leverages Stage3D for GPU acceleration. It provides a powerful framework for rendering 3D models, animations, lighting, and materials within ActionScript 3 applications. Ideal for interactive media, games, and visualizations, Away3D simplifies working with 3D scenes in Flash and supports common file formats like OBJ and MD5. -
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HIPAcc
Heterogeneous Image Processing Acceleration (HIPACC) Framework
HIPAcc development has moved to github: https://github.com/hipacc HIPAcc allows to design image processing kernels and algorithms in a domain-specific language (DSL). From this high-level description, low-level target code for GPU accelerators is generated using source-to-source translation. As back ends, the framework supports CUDA, OpenCL, and Renderscript. HIPAcc allows programmers to develop imaging applications while providing high productivity, flexibility and portability as well as competitive performance: the same algorithm description serves as basis for targeting different GPU accelerators and low-level languages. -
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OpenShader
Open architecture GPU simulator and implementation
Documentation, simulator, compiler, and Verilog implementation of a completely open-architecture graphics processing unit. This design is intended for academic and commercial purposes. The first step is to develop a detailed GPU simulator and compiler. The second step is to implement the GPU in synthesizable Verilog. The third step is to develop a feedback loop between the simulator and implementation, allowing power, performance, and reliability aspects of the hardware to feed back into ever more detailed and accurate simulations of a complete GPU. ... -
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LBP in multiple platforms
LBP implementation in multiple computing platforms (ARM,GPU, DSP...)
...When selecting a suitable LBP implementation platform, the specific application and its requirements in terms of performance, size, energy efficiency, cost and developing time has to be carefully considered. This is a software toolbox that collects software implementations of the Local Binary Pattern operator in several platforms: - OpenCL for CPU & GPU - OpenCL for GPU (branchless) - C code optimized for ARM - OpenGL ES 2.0 shaders mobile GPUs - C code for TI C64x DSP core (branchless) - C code for TTA processor synthesis If you use the code somewhere, please cite: Bordallo López M., Nieto A., Boutellier J., Hannuksela J., and Silvén O. "Evaluation of real-time LBP computing in multiple architectures," Journal of Real Time Image Processing, 2014 -
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A simple rendering, image processing engine. Includes a framework width (multiplatform) event handling, plugin management, a templated based math library and some exotic features like general linear camera, gpu based (OpenGL) image process...
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Qaquarelle is the opensource Qt4-based graphical editor, whose goal is to provide the native way of painting with emulated traditional instruments, including the full support of tablet input and OpenGL-based processing in GPU.
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A gathering of state-of-the-art tools for GPU based image processing. They are the sourcecode for related research articles, and provide the basis for own experimentation. All are being implemented forNVidia GPUs in Linux, hence the name "nvision" ;)
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BrokenFinger is a collection of demo 3D programs showing latest implementation in the areas of: Document Object Model, GPU Bound Processing, and Procedural Modeling(e.g. CGA Shape).
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proGPUKLT is a library for the Processing programming language and environment that wraps a GPU-implementation of the Kanade-Lucas-Tomasi feature tracker used for computer vision applications.
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An OS/hardware vendor independent GPU accelerated image and video processing library written in C. Interface allows easy combination and manipulation of customizable filters. Works with an active OpenGL context.
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This project uses massively parallel Graphics Processing Units(GPU) for neural network(Backpropagation) purposes.
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GLEWpy aims to bring advanced OpenGL extensions to Python. This allows the Python OpenGL developer to use features such as fragment/vertex shaders and image processing on the GPU. It serves as a compliment to PyOpenGL and toolkits such as GLUT and SDL.
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Jorik is about using graphics processing units in general purpose (GPGPU) computations: parallel sorting, dynamic PDE and image processing. Jorik is written on C++/DirectX/HSLS, supports both ATI and nVidia cards. It suits for not-gaming GPU benchmarking.
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GPUVision is a framework for creating GPU based general purpose programs, image processing programs, and computer vision programs in C++. Supported libraries include matrix operations, graph partitioning, kernels, corner detection, edge detection etc.
