Showing 92 open source projects for "convolution"

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  • 1
    ImageFiltering.jl

    ImageFiltering.jl

    Julia implementations of multidimensional array convolution

    Julia implementations of multidimensional array convolution and nonlinear stencil operations. ImageFiltering implements blurring, sharpening, gradient computation, and other linear filtering operations, as well nonlinear filters like min/max.
    Downloads: 0 This Week
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  • 2
    MNN

    MNN

    MNN is a blazing fast, lightweight deep learning framework

    MNN is a highly efficient and lightweight deep learning framework. It supports inference and training of deep learning models, and has industry leading performance for inference and training on-device. At present, MNN has been integrated in more than 20 apps of Alibaba Inc, such as Taobao, Tmall, Youku, Dingtalk, Xianyu and etc., covering more than 70 usage scenarios such as live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity...
    Downloads: 10 This Week
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  • 3
    Watermark-Removal

    Watermark-Removal

    Machine learning image inpainting task that removes watermarks

    ...The system analyzes an image containing a watermark and attempts to reconstruct the underlying visual content so that the watermark is removed while preserving the original appearance of the image. The project uses neural network models inspired by research in contextual attention and gated convolution, which are methods commonly applied to image restoration tasks. Through these techniques, the model learns to identify regions of the image affected by the watermark and generate realistic replacements for the missing visual information. The repository contains code for preprocessing images, training the model, and running inference on images to automatically remove watermark artifacts.
    Downloads: 4 This Week
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  • 4
    CUTLASS

    CUTLASS

    CUDA Templates for Linear Algebra Subroutines

    CUTLASS is a collection of CUDA C++ template abstractions for implementing high-performance matrix-multiplication (GEMM) and related computations at all levels and scales within CUDA. It incorporates strategies for hierarchical decomposition and data movement similar to those used to implement cuBLAS and cuDNN. CUTLASS decomposes these "moving parts" into reusable, modular software components abstracted by C++ template classes. These thread-wide, warp-wide, block-wide, and device-wide...
    Downloads: 0 This Week
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  • 5
    DSP.jl

    DSP.jl

    Filter design, periodograms, window functions

    DSP.jl provides a number of common digital signal processing routines in Julia.
    Downloads: 0 This Week
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  • 6
    Make-A-Video - Pytorch (wip)

    Make-A-Video - Pytorch (wip)

    Implementation of Make-A-Video, new SOTA text to video generator

    ...The gist of the paper comes down to, take a SOTA text-to-image model (here they use DALL-E2, but the same learning points would easily apply to Imagen), make a few minor modifications for attention across time and other ways to skimp on the compute cost, do frame interpolation correctly, get a great video model out. Passing in images (if one were to pretrain on images first), both temporal convolution and attention will be automatically skipped. In other words, you can use this straightforwardly in your 2d Unet and then port it over to a 3d Unet once that phase of the training is done.
    Downloads: 0 This Week
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  • 7
    Astropy

    Astropy

    Repository for the Astropy core package

    The Astropy Project is a community effort to develop a common core package for Astronomy in Python and foster an ecosystem of interoperable astronomy packages. Astropy is a Python library for use in astronomy. Learn Astropy provides a portal to all of the Astropy educational material through a single dynamically searchable web page. It allows you to filter tutorials by keywords, search for filters, and make search queries in tutorials and documentation simultaneously. The Anaconda Python...
    Downloads: 1 This Week
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  • 8
    Compute Library

    Compute Library

    The Compute Library is a set of computer vision and machine learning

    The Compute Library is a set of computer vision and machine learning functions optimized for both Arm CPUs and GPUs using SIMD technologies. The library provides superior performance to other open-source alternatives and immediate support for new Arm® technologies e.g. SVE2.
    Downloads: 0 This Week
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  • 9
    bild

    bild

    Image processing algorithms in pure Go

    ...It uses packages from the standard library whenever possible to reduce dependency use and development abstractions. All operations return image types from the standard library. Package convolution provides the functionality to create and apply a kernel to an image. Package effect provides the functionality to manipulate images to achieve various looks. Package histogram provides basic histogram types and functions to analyze RGBA images. Package paint provides functions to edit a group of pixels on an image. Package parallel provides helper functions for the dispatching of parallel jobs.
    Downloads: 0 This Week
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  • 10
    libvips

    libvips

    A fast image processing library with low memory needs

    ...Compared to similar libraries, libvips runs quickly and uses little memory. libvips is licensed under the LGPL 2.1+. It has around 300 operations covering arithmetic, histograms, convolution, morphological operations, frequency filtering, colour, resampling, statistics and others. It supports a large range of numeric types, from 8-bit int to 128-bit complex. Images can have any number of bands. It supports a good range of image formats, including JPEG, JPEG2000, JPEG-XL, TIFF, PNG, WebP, HEIC, AVIF, FITS, Matlab, OpenEXR, PDF, SVG, HDR, PPM / PGM / PFM, CSV, GIF, Analyze, NIfTI, DeepZoom, and OpenSlide. ...
    Downloads: 4 This Week
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  • 11
    Pytorch-toolbelt

    Pytorch-toolbelt

    PyTorch extensions for fast R&D prototyping and Kaggle farming

    A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses: BinaryFocalLoss, Focal, ReducedFocal, Lovasz, Jaccard and Dice losses, Wing Loss and more. Extras for Catalyst library (Visualization of batch predictions, additional metrics). ...
    Downloads: 1 This Week
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  • 12
    MIVisionX

    MIVisionX

    Set of comprehensive computer vision & machine intelligence libraries

    MIVisionX toolkit is a set of comprehensive computer vision and machine intelligence libraries, utilities, and applications bundled into a single toolkit. AMD MIVisionX delivers highly optimized open-source implementation of the Khronos OpenVX™ and OpenVX™ Extensions along with Convolution Neural Net Model Compiler & Optimizer supporting ONNX, and Khronos NNEF™ exchange formats. The toolkit allows for rapid prototyping and deployment of optimized computer vision and machine learning inference workloads on a wide range of computer hardware, including small embedded x86 CPUs, APUs, discrete GPUs, and heterogeneous servers. ...
    Downloads: 0 This Week
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  • 13

    Freeverb3_vst

    Freeverb3 DSP VST effect plugins

    The Freeverb3VST is a package of VST DSP effect plugins utilizing the Freeverb3 signal processing library. Many types of audio processing effects including high quality reverbs and impulse response convolution processors are available.
    Downloads: 29 This Week
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  • 14
    ASH-Toolset

    ASH-Toolset

    Headphone Correction and Spatial Audio on Headphones

    The Audio Spatialisation for Headphones Toolset is an application for headphone correction and binaural synthesis of spatial audio systems on headphones Visit the wiki for information on how it works: https://sourceforge.net/p/ash-toolset/wiki/Documentation/
    Downloads: 19 This Week
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  • 15

    libsombrero

    Astronomical object/structure detection from 1D and 2D data sets.

    Sombrero is a fast wavelet image processing and object detection C library for astronomical images. Sombrero is named after the "Mexican Hat" shape of the wavelet masks used in image convolution and is released under the GNU LGPL library.
    Downloads: 0 This Week
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  • 16

    Creatools Piano XS

    Sample based piano virtual instrument

    Is the third generation of a free and opensource virtual piano project built on HISE open source framework. It is built and developed with an aim to make a contribution towards free music education and creative freedom and it is therefore licensed under GPLv3 license. for more info: https://musictop69.wixsite.com/creatools
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    Downloads: 4 This Week
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  • 17

    BoofCV

    BoofCV is an open source Java library for real-time computer vision.

    ...Written from scratch for ease of use and high performance, it provides both basic and advanced features needed for creating a computer vision system. Functionality include optimized low level image processing routines (e.g. convolution, interpolation, gradient) to high level functionality such as image stabilization. Released under an Apache 2.0 license for both academic and commercial use.
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    Downloads: 14 This Week
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  • 18
    spaGO

    spaGO

    Self-contained Machine Learning and Natural Language Processing lib

    A Machine Learning library written in pure Go designed to support relevant neural architectures in Natural Language Processing. Spago is self-contained, in that it uses its own lightweight computational graph both for training and inference, easy to understand from start to finish. The core module of Spago relies only on testify for unit testing. In other words, it has "zero dependencies", and we are committed to keeping it that way as much as possible. Spago uses a multi-module workspace to...
    Downloads: 0 This Week
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  • 19

    libdspl-2.0

    libdspl-2.0 is opensource cross-platform digital signal processing alg

    libdspl-2.0 — opensource cross-platform digital signal processing algorithm library, written in C language. Distributed under LGPL v3 license. This allows to use this library in all applications with dynamic linking.
    Downloads: 0 This Week
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  • 20
    Convolution Filter Editor
    CFE is a postcardware written in plain C language. Cfe is a software, allowing the creation of convolution filters like SOBEL, LAPLACE, ROBINSON... It allows filters ranging from 3x3 up to 29x29. CFE speaks French, English, German, Italian and Spanish and has its own slideshow. The filter editor has 18 features such as mirrors, shiftings and rotations. There are no menus, all commands are directly accessible with the mouse. When a filter is created, you can give it a rating ranging from 1 to 5 stars. ...
    Downloads: 2 This Week
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  • 21
    texturize

    texturize

    Generate photo-realistic textures based on source images

    ...It's useful in the context of computer graphics if you want to make variations on a theme or expand the size of an existing texture. This software is powered by deep learning technology, using a combination of convolution networks and example-based optimization to synthesize images. We're building texturize as the highest-quality open source library available! The examples are available as notebooks, and you can run them directly in-browser thanks to Jupyter and Google Colab.
    Downloads: 0 This Week
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  • 22
    T81 558

    T81 558

    Applications of Deep Neural Networks

    ...Deep learning allows a neural network to learn hierarchies of information in a way that is like the function of the human brain. This course will introduce the student to classic neural network structures, Convolution Neural Networks (CNN), Long Short-Term Memory (LSTM), Gated Recurrent Neural Networks (GRU), General Adversarial Networks (GAN) and reinforcement learning. Application of these architectures to computer vision, time series, security, natural language processing (NLP), and data generation will be covered. High-Performance Computing (HPC) aspects will demonstrate how deep learning can be leveraged both on graphical processing units (GPUs), as well as grids.
    Downloads: 0 This Week
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  • 23
    DiffEqOperators.jl

    DiffEqOperators.jl

    Linear operators for discretizations of differential equations

    ...For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. The cases of 1, 2, and 3 dimensions with an evenly spaced grid are optimized with a convolution routine from NNlib.jl. Care is taken to give efficiency by avoiding unnecessary allocations, using purpose-built stencil compilers, allowing GPUs and parallelism, etc. Any operator can be concretized as an Array, a BandedMatrix or a sparse matrix.
    Downloads: 0 This Week
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  • 24
    ASRT Speech Recognition

    ASRT Speech Recognition

    A Deep-Learning-Based Chinese Speech Recognition System

    ASRT is an end-to-end deep-learning Chinese ASR system built with TensorFlow/Keras, using convolution + CTC and a Max-Entropy HMM language model. It provides a REST/gRPC server backend and client SDKs in multiple languages (Python, Java, Go, Windows). Notably lightweight, it performs well without needing GPU acceleration and runs across platforms, targeting developers and researchers building Chinese voice interfaces.
    Downloads: 0 This Week
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  • 25
    MeshCNN in PyTorch

    MeshCNN in PyTorch

    Convolutional Neural Network for 3D meshes in PyTorch

    MeshCNN is a deep learning framework designed specifically for processing 3D triangular mesh data using convolutional neural networks. Unlike traditional CNNs that operate on images or voxel grids, MeshCNN performs convolution operations directly on the edges of mesh structures. This design allows the model to capture geometric relationships between mesh elements while preserving the underlying topology of 3D shapes. The framework introduces specialized layers such as edge-based convolution, mesh pooling, and mesh unpooling operations that enable hierarchical feature learning on mesh surfaces. ...
    Downloads: 0 This Week
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