Search Results for "gpu image"
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Showing 18 open source projects for "gpu image"
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CycleGAN and pix2pix in PyTorch
Image-to-Image Translation in PyTorch
...The code supports standard training and inference pipelines, and as of recent updates, compatibility with the latest Python and PyTorch versions (e.g. Python 3.11, PyTorch 2.4) as well as support for distributed/multi-GPU training for scalable workflows. Because of its flexibility, users can apply it to many tasks: e.g. style transfer between domains (e.g. season changes, art-to-photo, etc.), mapping sketches/edges to real images, image colorization, day-to-night, photo enhancement, and more. -
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COLMAP
Structure-from-Motion and Multi-View Stereo
COLMAP is a general-purpose Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipeline with a graphical and command-line interface. It offers a wide range of features for the reconstruction of ordered and unordered image collections. The software is licensed under the new BSD license. -
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PyTorch Geometric
Geometric deep learning extension library for PyTorch
...We have outsourced a lot of functionality of PyTorch Geometric to other packages, which needs to be additionally installed. These packages come with their own CPU and GPU kernel implementations based on C++/CUDA extensions. We do not recommend installation as root user on your system python. Please setup an Anaconda/Miniconda environment or create a Docker image. We provide pip wheels for all major OS/PyTorch/CUDA combinations. -
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ExCon Imager
Gigapixel GPU accelerated radio interferometric imager
ExCon can create images with a very wide field of view (more than billion pixels). It implements novel gridding and image weighting algorithms. It is well suited to make ultra deep radio interferometric images, minimizing aliasing artefacts and PSF variation. NVIDIA GPU acceleration is available. JAVA/SCALA support available. -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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TomoJ
ImageJ plugin to perform Electron Tomography
...TomoJ proposes the preprocessing and the registration of tilt-series prior to 3D reconstructions (WBP, ART, SIRT, OS-SART, compressed sensing). TomoJ is written in Java, the computations are multithreaded and reconstruction can be performed on CPU or GPU (OpenCL). registration is described in: Journal of Structural Biology: X. 2020, Volume 4. "Improvements on marker-free images alignment for electron tomography" C.O.S. Sorzano et al. https://doi.org/10.1016/j.yjsbx.2020.100037. BMC Bioinformatics. 2009 Apr 27;10:124."Marker-free image registration of electron tomography tilt-series." ... -
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PyMapStitcher-3---Cuda-Maps-Downloader
A low ram maps downloader to keep your ram free.
PyMapStitcher 3 is a desktop application for downloading, stitching, and exporting very large satellite map areas as GeoTIFF/BigTIFF files. The software supports GPU acceleration with NVIDIA CUDA and CuPy, direct GeoTIFF georeferencing, WebView-based map selection, and high-performance tile processing for large-scale mapping workflows. -
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viewpix
A Landsat 8 scene viewer
Viewpix allows the user to load all eleven bands of a Landsat 8 Level 1 data set into memory concurrently. You can scroll and view each band at full resolution. Change bands instantly with a single key press. Band 8 is 15 meters resolution, all other bands are 30m resolution. A 30m resolution gray scale scene is generated by Viewpix and is presented as band 12. Each Landsat 8 scene is roughly 190 X 180 kilometers. Viewpix was originally written as a simple platform to test GPU... -
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cphcttoolbox
Cph CT Toolbox is a selection of Computed Tomography tools
Copenhagen Computed Tomography Toolbox is a collection of applications and libraries for flexible and efficient CT reconstruction. The toolbox apps generally take a set of projections (X-ray intensity measurements) and filter and back project them in order to recreate the image or volume that the projections represent. The project includes both mostly informative CPU implementations and highly efficient GPU implementations. Regular releases are hosted at the Python Package Index. -
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Ezys
Ezys 3D medical image registration program
Ezys is a non-linear 3D medical image registration program. Ezys fully exploits the parallel computing power of inexpensive commercial graphics processing units (GPU), resulting in a very fast and accurate program capable of running on desktop PCs and even some laptops. On these systems, non-linear image registrations take less than a minute to complete. Ezys implements a diffeomorphic inverse consistent image registration algorithm with a demons-style regularization based on a non-parametric free form deformation model. ... -
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GPU Edge Detector
GPU Interactive Program For Edge detection
This is a standalone, all in one Edge Detector that is mainly running on GPU using the CUDA technology. Each algorithm also has an OpenCV counterpart which is the closest one in terms of speed. This project is partly based on the Sobel Filter sample available as part of the CUDA SDK. This project also partly uses the OpenCV library to load different types of image. This program includes: Prewitt filter, Roberts Cross, Canny edge detector and finally Sobel filter with the ability to modify some variables such as sigma in Canny and see the result in real-time. ... -
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A shareware for build realtime photoacoustic tomography image using NVidia Geforce GPU. Can work in both offline mode or online mode.
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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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birgHPCC
Rapid CUDA Cluster Deployment
...While retaining the major functions of the original birgHPC, including automated computing cluster conversion and auto slots detection, the new version (birgHPCC) is capable of creating and configuring a compute unified device architecture (CUDA) computing cluster, hence the extra “C” in the name. In addition to the increase in image size (less than 2 gigabytes) and a new Linux base (previously Debian, now Ubuntu), CUDA-capable bioinformatics software programs, such as NAMD, HOOMD-blue, VMD, GPU-HMMER and GPU-BLAST, are pre-installed in birgHPCC, along with the CUDA driver, libraries and software development kit (SDK). In short, birgHPCC is the world's first CUDA-ready, bioinformatics-based, live DVD. -
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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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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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multiDAC is intended to become a user-friendly tool for image- and videoprocessing in the field of deformation/movement analysis. It is written in C# with some C routines using CPU/GPU parallelization (e.g. CUDA) and features a plugin manager.
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OpenSARSim is builded for the simulation of synthetic aperture radar image. This software use the principle of electromagnetic field scattering to get the SAR image. Most of the computation work is based on GPU.
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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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