Search Results for "image processing" - Page 4
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Showing 146 open source projects for "image processing"
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LTI-Lib is an object oriented computer vision library written in C++ for Windows/MS-VC++ and Linux/gcc. It provides lots of functionality to solve mathematical problems, many image processing algorithms, some classification tools and much more...
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ImageProcessor
Wrapper around System.Drawing for the processing of image files
A .NET library for on-the-fly processing of images. ImageProcessor is a collection of lightweight libraries written in C# that allows you to manipulate images on-the-fly using .NET 4.5+. It consists of two main libraries ImageProcessor, for desktop and application use and ImageProcessor.Web, a dynamic image processing extension built for ASP.NET. It’s lighting fast, extensible, easy to use, comes bundled with some great features and is fully open source. -
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WePY
Framework that allows programs to support componentized development
...Through polyfill, the mini program perfectly supports Promise and solves callback troubles. Features such as Generator Function / Class / Async Function can be used to greatly improve development efficiency. Support a variety of plug-in processing, such as file compression, image compression, content replacement, etc., easy to expand and easy to use. -
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PRMLT
Matlab code of machine learning algorithms in book PRML
...This package requires Matlab R2016b or latter, since it utilizes a new Matlab syntax called Implicit expansion (a.k.a. broadcasting). It also requires Statistics Toolbox (for some simple random number generator) and Image Processing Toolbox (for reading image data). The code is extremely compact. Minimizing code length is a major goal. As a result, the core of the algorithms can be easily spotted. Many tricks for speeding up Matlab code are applied (e.g. vectorization, matrix factorization, etc.). Usually, functions in this package are orders faster than Matlab builtin ones (e.g. kmeans). ... -
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imgIX
A plugin for integrating imgix into Jekyll sites
...Visual media technology is cumbersome, complex, and ever-evolving. We streamline it so you can control your workflow. Poor loading speed hurt conversions and SEO. Improve your performance with robust media processing. Future-proof your visual media, so your customers get the best experience anywhere, on any platform. Upload, search, edit, and organize all cloud assets. See real-time insights. Intelligent, automated compression that eliminates unnecessary bytes. Fast image and video loading with a globally distributed CDN. Encode, stream, and manage videos for a rich and smooth viewing experience. ... -
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ConcatPDF
PDF Concatenation Tool
ConcatPDF is the tool to concatenate PDF files. It can concatenate, extract, encrypt, decrypt, configure PDF files, convert image files to PDF. GUI version and CUI version are both available. iText.NET is iText porting on .NET Framework by J#. This library allows you to generate PDF, (X)HTML, XML, RTF files on Microsoft.NET Framework including ASP.NET. -
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Simd
High performance image processing library in C++
The Simd Library is a free open source image processing library, designed for C and C++ programmers. It provides many useful high performance algorithms for image processing such as: pixel format conversion, image scaling and filtration, extraction of statistic information from images, motion detection, object detection (HAAR and LBP classifier cascades) and classification, neural network. -
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smartcrop
smartcrop finds good image crops for arbitrary crop sizes
...It supports different aspect ratios and can be customized to prioritize certain features depending on the use case. smartcrop is designed to be efficient and easy to integrate into applications that require automated image processing. It can be used in web services, content management systems, or media pipelines. Overall, smartcrop provides an intelligent approach to image cropping that improves visual quality. -
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iText®, a JAVA PDF library
PDF Library for Developers
iText is an open-source PDF library available for Java and .NET (C#). iText allows you to effortlessly generate and manipulate standards-compliant PDF documents with a powerful and feature-rich SDK. With iText, you can create archivable and accessible PDFs, split and merge documents, fill and flatten forms, digitally sign documents, and more. iText add-ons enable additional functionality, such as PDF creation from HTML templates, secure redaction, OCR, and much more. The latest... -
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Tiramisu
Polyhedral compiler for expressing fast and portable data algorithms
...It provides a simple C++ API for expressing algorithms (Tiramisu expressions) and how these algorithms should be optimized by the compiler. Tiramisu can be used in areas such as linear and tensor algebra, deep learning, image processing, stencil computations and machine learning. The Tiramisu compiler is based on the polyhedral model thus it can express a large set of loop optimizations and data layout transformations. Currently, it targets (1) multicore X86 CPUs, (2) Nvidia GPUs, (3) Xilinx FPGAs (Vivado HLS) and (4) distributed machines (using MPI). ... -
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Keras resources
Directory of tutorials and open-source code repositories
...It aggregates a wide range of resources, including beginner guides, advanced tutorials, code examples, and third-party tools, all organized into a single reference hub. The repository covers diverse topics such as image classification, natural language processing, reinforcement learning, and generative models, providing both theoretical and practical insights. It also includes links to external projects built with Keras, demonstrating real-world applications of deep learning techniques. The structure is designed for easy navigation, allowing users to quickly find relevant materials based on their skill level or area of interest. ... -
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Accord.NET Framework
Machine learning, computer vision, statistics and computing for .NET
The Accord.NET Framework is a .NET machine learning framework combined with audio and image processing libraries completely written in C#. It is a complete framework for building production-grade computer vision, computer audition, signal processing and statistics applications even for commercial use. A comprehensive set of sample applications provide a fast start to get up and running quickly, and extensive documentation and a wiki help fill in the details. -
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Starling Filters
A collection of filters for use with the Starling AS3 framework
Starling-Filters is an open-source collection of filter effects for the Starling AS3 framework. These filters allow developers using Starling (a GPU accelerated 2D rendering framework in Flash/AIR) to apply image processing / visual effects (e.g. blur, glow, etc.) in their Starling-based applications. The repo has versions for Starling 2.0 (on master) and older filters archived for Starling 1.x. A collection of filters for use with the Starling AS3 framework. The master branch contains filters for use with Starling 2.0. -
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CognitionMaster
object-based image analysis framework
Wienert S, Heim D, Kotani M, Lindequist B, Stenzinger A, Ishii M, Hufnagl P, Beil M, Dietel M, Denkert C, Klauschen F. CognitionMaster: an object-based image analysis framework. Diagn Pathol 2013, 8:34 -
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fast-neural-style
Feedforward style transfer
The fast-neural-style project is an implementation of neural style transfer techniques optimized for real-time image processing. It uses convolutional neural networks to apply artistic styles to images, enabling users to transform photos into stylized outputs inspired by famous artworks. Unlike earlier approaches that required expensive optimization per image, this project leverages feed-forward networks to achieve fast inference, making style transfer practical for real-world applications. ... -
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The Camellia library is an open source and cross-platform image processing library, written in plain C. It includes a lot of speed-optimized imaging functions (filtering, morpho, labeling, motion detection, warping, color conversion, project/backproject)
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WrapImaJ
Multi-platform API for Image Processing systems in Life Sciences
WrapImaJ purposes to be a multi-platform wrapper for different Image Processing systems for: - using the Java programming language. The purpose of WrapImaJ is not to combine an exhaustive collection of all functionalities of different imaging system, but to offer a simple, concise Application Programming Interface (API) - allowing to develop imaging software, the source code of which is independent from the underlying imaging system on which it relies. -
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Gallop
A framework for build smooth asynchronous iOS APP
...Easily draw text frame bouding, drawing the hollow words, sets the text vertical Alignment property, etc Easy to parse the expression in the text, like http(s) link, @ user, # theme #, phone number. Fast to sets the image corner radius property and blur processing, can be processed directly after the image. -
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CSSgram
CSS library for Instagram filters
...What we're doing is adding filters to the images, as well as applying color and/or gradient overlays via various blending techniques to mimic filter effects. This means less manual image processing and more fun filter effects on the web! We are using pseudo-elements (i.e. :before and :after) to create the filter effects, so you must apply these filters on a containing element (i.e. not a content-block like <img>. The recommendation is to wrap your images in a <figure> tag. If you use custom naming in your CSS architecture, you can add the .scss files for the provided styles within your project and then @extend the filter effects within your style definitions. ... -
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tracking.js
A modern approach for Computer Vision on the web
The tracking.js library brings different computer vision algorithms and techniques into the browser environment. By using modern HTML5 specifications, we enable you to do real-time color tracking, face detection and much more, all that with a lightweight core (~7 KB) and intuitive interface. To get started, download the project. This project includes all of the tracking.js examples, source code dependencies you'll need to get started. Unzip the project somewhere on your local drive. The... -
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PyCNN
Image Processing with Cellular Neural Networks in Python
Image Processing with Cellular Neural Networks in Python. Cellular Neural Networks (CNN) are a parallel computing paradigm that was first proposed in 1988. Cellular neural networks are similar to neural networks, with the difference that communication is allowed only between neighboring units. Image Processing is one of its applications. -
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CRFasRNN
Semantic image segmentation method described in the ICCV 2015 paper
CRF-RNN is a deep neural architecture that integrates fully connected Conditional Random Fields (CRFs) with Convolutional Neural Networks (CNNs) by reformulating mean-field CRF inference as a Recurrent Neural Network. This fusion enables end-to-end training via backpropagation for semantic image segmentation tasks, eliminating the need for separate, offline post-processing steps. Our work allows computers to recognize objects in images, what is distinctive about our work is that we also recover the 2D outline of objects. Currently we have trained this model to recognize 20 classes. This software allows you to test our algorithm on your own images – have a try and see if you can fool it, if you get some good examples you can send them to us. ... -
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Awesome Recurrent Neural Networks
A curated list of resources dedicated to RNN
A curated list of resources dedicated to recurrent neural networks (closely related to deep learning). Provides a wide range of works and resources such as a Recurrent Neural Network Tutorial, a Sequence-to-Sequence Model Tutorial, Tutorials by nlintz, Notebook examples by aymericdamien, Scikit Flow (skflow) - Simplified Scikit-learn like Interface for TensorFlow, Keras (Tensorflow / Theano)-based modular deep learning library similar to Torch, char-rnn-tensorflow by sherjilozair, char-rnn... -
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DeepDream
This repository contains IPython Notebook with sample code
...The notebook shows how to take a trained vision model and iteratively amplify patterns the network detects, producing the hallmark surreal, hallucinatory visuals. It walks through loading a pretrained network, selecting layers and channels to maximize, computing gradients with respect to the input image, and applying multi-scale “octave” processing to reveal fine and coarse patterns. The code is intentionally compact and exploratory, encouraging users to tweak layers, step sizes, and scales to influence the aesthetic. Although minimal, it illustrates important concepts like feature visualization, activation maximization, and the effect of different receptive fields on the final image. -
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UPDATE March 14, 2018 Repository and tracking officially moved to github. https://github.com/opticks-org/opticks Sourceforge mailing lists are still in use. Opticks is an open source remote sensing application and development framework.
