Showing 10 open source projects for "image forgery detection"

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  • 1
    ML.NET

    ML.NET

    Open source and cross-platform machine learning framework for .NET

    ...ML.NET has been designed as an extensible platform so that you can consume other popular ML frameworks (TensorFlow, ONNX, Infer.NET, and more) and have access to even more machine learning scenarios, like image classification, object detection, and more.
    Downloads: 0 This Week
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  • 2
    SSRFmap

    SSRFmap

    Automatic SSRF fuzzer and exploitation tool

    SSRFmap is a specialized security tool designed to automate the detection and exploitation of Server Side Request Forgery (SSRF) vulnerabilities. It takes as input a Burp request file and a user-specified parameter to fuzz, enabling you to fast-track the identification of SSRF attack surfaces. It includes multiple exploitation “modules” for common SSRF-based attacks or pivoting techniques, such as DNS zone transfers, MySQL/Postgres command execution, Docker API info leaks, and network scans. ...
    Downloads: 0 This Week
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  • 3
    Posturr

    Posturr

    A macOS app that blurs your screen when you slouch

    Posturr is a macOS application that uses computer vision and machine learning — specifically Apple’s Vision framework — to monitor a user’s posture in real time and encourage healthier habits by visually responding when poor posture is detected. Running locally on the Mac, the app accesses the built-in camera to detect when you slouch or sit incorrectly, and when it recognizes sustained slouching, it applies a progressive visual blur to the screen as a subtle but effective cue to straighten...
    Downloads: 0 This Week
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  • 4
    Jittor

    Jittor

    Jittor is a high-performance deep learning framework

    ...A powerful op compiler and tuner are integrated into Jittor. It allowed us to generate high-performance code specialized for your model. Jittor also contains a wealth of high-performance model libraries, including image recognition, detection, segmentation, generation, differentiable rendering, geometric learning, reinforcement learning, etc. The front-end language is Python. Module Design and Dynamic Graph Execution is used in the front-end, which is the most popular design for deep learning framework interface. The back-end is implemented by high-performance languages, such as CUDA, C++. ...
    Downloads: 0 This Week
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  • 5
    Darknet

    Darknet

    Convolutional Neural Networks

    Darknet is an open source neural network framework written in C and CUDA, developed by Joseph Redmon. It is best known as the original implementation of the YOLO (You Only Look Once) real-time object detection system. Darknet is lightweight, fast, and easy to compile, making it suitable for research and production use. The repository provides pre-trained models, configuration files, and tools for training custom object detection models. With GPU acceleration via CUDA and OpenCV integration, it achieves high performance in image recognition tasks. ...
    Downloads: 36 This Week
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  • 6
    Gluon CV Toolkit

    Gluon CV Toolkit

    Gluon CV Toolkit

    ...It features training scripts that reproduce SOTA results reported in latest papers, a large set of pre-trained models, carefully designed APIs and easy-to-understand implementations and community support. From fundamental image classification, object detection, semantic segmentation and pose estimation, to instance segmentation and video action recognition. The model zoo is the one-stop shopping center for many models you are expecting. GluonCV embraces a flexible development pattern while is super easy to optimize and deploy without retaining a heavyweight deep learning framework.
    Downloads: 0 This Week
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  • 7
    TensorFlow Object Counting API

    TensorFlow Object Counting API

    The TensorFlow Object Counting API is an open source framework

    The TensorFlow Object Counting API is an open source framework built on top of TensorFlow and Keras that makes it easy to develop object counting systems. Please contact if you need professional object detection & tracking & counting project with super high accuracy and reliability! You can train TensorFlow models with your own training data to built your own custom object counter system! If you want to learn how to do it, please check one of the sample projects, which cover some of the...
    Downloads: 0 This Week
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  • 8
    GPUImage 2

    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. ...
    Downloads: 7 This Week
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  • 9
    GPUImage

    GPUImage

    iOS framework for GPU-based image and video processing

    The GPUImage framework is a BSD-licensed iOS library that lets you apply GPU-accelerated filters and other effects to images, live camera video, and movies. In comparison to Core Image (part of iOS 5.0), GPUImage allows you to write your own custom filters, supports deployment to iOS 4.0, and has a slightly simpler interface. However, it currently lacks some of the more advanced features of Core Image, such as facial detection. GPUImage uses OpenGL ES 2.0 shaders to perform image and video manipulation much faster than could be done in CPU-bound routines. ...
    Downloads: 0 This Week
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  • 10
    Content adaptation platform that adapts internet content to any mobile device in real time. Includes features such as device detection, image transcoding, DOM manipulation, XML/RSS feed support and much more.
    Downloads: 0 This Week
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