Search Results for "idl image processing" - Page 4
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Showing 125 open source projects for "idl image processing"
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GPUImage 2
Framework for GPU-accelerated video and image processing
GPUImage 2 is the second generation of the GPUImage framework, an open source project for performing GPU-accelerated image and video processing on Mac, iOS, and now Linux. The original GPUImage framework was written in Objective-C and targeted Mac and iOS, but this latest version is written entirely in Swift and can also target Linux and future platforms that support Swift code. The objective of the framework is to make it as easy as possible to set up and perform realtime video processing or machine vision against image or video sources. ... -
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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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cocolib / light field suite
CUDA library for continuous optimization and light field analysis
Library for continuous convex optimization in image analysis, together with a command line tool and Matlab interface. Implements several recent algorithms for inverse problems and image segmentation with total variation regularizers and vectorial multilabel transition costs. Also included is a suite for variational light field analysis, which ties into the HCI light field benchmark set and givens reference implementations for a number of our recently published algorithms. *** NOTE: ... -
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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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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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MARF is a general cross-platform framework with a collection of algorithms for audio (voice, speech, and sound) and natural language text analysis and recognition along with sample applications (identification, NLP, etc.) of its use, implemented in Java.
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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.
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ANNGD
Artificial neural network gender detection
ANNGD is a artificial neural network gender detection application. The detection is made in real time images captured by webcam by opencv library. The package include applications to image pre-processing and artificial neural network back-propagation training. -
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ApproxAdderLib
Library of Approximate Adders
...To the best of our knowledge, this is the first open-source library of approximate adders that facilitates reproducible comparisons and further research and development in this direction across various layers of design abstraction. This work is a result of collaborative effort between Chair for Embedded Systems (CES) at Karlsruhe Institute of Technology (KIT), Germany and Vision Image and Signal Processing (VISpro) Lab at SEECS-NUST, Pakistan. -
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jmathstudio - Java Image/Signal toolkit
Java toolkit for discrete Image and Signal processing.
JMathStudio is a Java based digital image and signal processing toolkit/library. It is simple to use, portable, light (~300 Kb), extendable and free. Full source code available at https://github.com/bhavyaajani/jmathstudio Android compatible JMathStudio is available @ https://sourceforge.net/projects/jmathstudio-android/ -
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matImage
An image processing and analysis library for Matlab
MatImage is a Matlab library for image processing and analysis in 2D and 3D. It contains more than 250 fonctions for image enhancement, filtering, analysis, or visualisation, as well as for creating basic test shapes. It is built as a complement of the Mathworks image processing toolbox (IPT). Project is being transfered to GitHub: http://github.com/dlegland/matImage -
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node-imagemagick
Imagemagick module for NodeJS
node-imagemagick is a Node.js module that wraps the popular ImageMagick command-line image processing tools, giving JavaScript developers the ability to perform powerful image manipulation tasks from within Node applications. Instead of reimplementing image algorithms in JavaScript, it shells out to the underlying ImageMagick binaries, enabling resizing, cropping, format conversion, compositing, and other transformations with the same proven engine used by many backend systems. ...
