Search Results for "images" - Page 3

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Simply put, CSSgram is a library for editing your images with Instagram-like filters directly using CSS. 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 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...

...You can modify the structure (paragraphs, lines, words...) create, delete, edit text nodes, modify their container box by mouse, and run a spellchecker. The program does not directly read the DjVu files, it requires exported XML text data and images. When using without a webserver, you can open and save local files, but cannot take advantages of auto-save and spell checking. Note that current SVN version has much more features than V1.0!

...Enable this functionality by adding a data property, data-ab-css-background to the element. selector String (default: 'img[data-adaptive-background="1"]') a CSS selector which denotes which images to grab/process. Ideally, this selector would start with img, to ensure we only grab and try to process actual images. parent falsy (default: null) a CSS selector which denotes which parent to apply the background color to. By default, the color is applied to the parent one level up the DOM tree.

...It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. The library allows you to formulate and solve Neural Networks in Javascript. If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. The compilation script simply concatenates files in src/ and then minifies the result.

This project develops a web-based (JSP) Fuzzy Rule-Based Expert System for analyzing ECG (electro cardio gram) signals & diagnosing Tachi-Arrhythmias. Proj. main blocks: inference engine, knowledgebase, KB editor, explanation, and feature extraction.

Sample application showcasing usage of technologies such as: * OSGi R7 Promises for asynchronous generation of transcriptions and linguistic analyses * OSGi R7 Push Stream and JAX RS Server Sent Events for push notifications of processing status * Apache Camel 2.23.1 and RabbitMQ 3.7 for asynchronous communication between services * JPA 2.1 and Hibernate 5.2.12, along with OSGi R7 JPA and Transaction Control services, for persistence layer * OSGi R7 HTTP and JAX RS Whiteboard for registering servlets, resources and REST controllers * OSGi R7 Configurator, Configuration Admin and Metatype services for automatic configuration of components * OSGi R7 Declarative Services for dependency injection * Maven automated build of Docker images * Maven automated deployment into Kubernetes cluster * RabbitMQ message broker as a StatefulSet * CockroachDB relational database as a StatefulSet See 'Code' tab for detailed information