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Ideally positioned at the end of <body>. (Available only from version 3.1 and more) By default, FuckAdBlock is instantiated automatically. To block this automatic instantiation, simply create a variable "fuckAdBlock" with a value (null, false, ...) before importing the script.
Arachni is a feature-full, modular, high-performance Ruby framework aimed towards helping penetration testers and administrators evaluate the security of web applications. It is smart, it trains itself by monitoring and learning from the web application's behavior during the scan process and is able to perform meta-analysis using a number of factors in order to correctly assess the trustworthiness of results and intelligently identify (or avoid) false-positives.
Meet detekt, a static code analysis tool for the Kotlin programming language. It operates on the abstract syntax tree provided by the Kotlin compiler. Visit https://arturbosch.github.io/detekt/ for installation guides, release notes, migration guides, rule descriptions and configuration options.
Simple Node.js API for robust face detection and face recognition. This a Node.js wrapper library for the face detection and face recognition tools implemented in dlib. Installing the package will build dlib for you and download the models. Note, this might take some time.
SOD is an embedded, modern cross-platform computer vision and machine learning software library that expose a set of APIs for deep-learning, advanced media analysis & processing including real-time, multi-class object detection and model training on embedded systems with limited computational resource and IoT devices. SOD was built to provide a common infrastructure for computer vision applications and to accelerate the use of machine perception in open source as well commercial products.
A python library built to empower developers to build applications and systems with self-contained Deep Learning and Computer Vision capabilities using simple and few lines of code. Built with simplicity in mind, ImageAI supports a list of state-of-the-art Machine Learning algorithms for image prediction, custom image prediction, object detection, video detection, video object tracking and image predictions trainings. ImageAI currently supports image prediction and training using 4 different Machine Learning algorithms trained on the ImageNet-1000 dataset. ImageAI also supports object detection, video detection and object tracking using RetinaNet, YOLOv3 and TinyYOLOv3 trained on COCO dataset. Eventually, ImageAI will provide support for a wider and more specialized aspects of Computer Vision including and not limited to image recognition in special environments and special fields.
I use DavidRM Journal for managing my research data for its excellent hierarchical organization, cross-linking and tagging capabilities. I make available a Journal entry export file that contains tagged and categorized collection of papers, articles and notes about computer vision and deep learning that I have collected over the last few years.