Search Results for "source code plagiarism detection"
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Showing 361 open source projects for "source code plagiarism detection"
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Anti-Plagiarism - software designed to effectively detect and thereby prevent plagiarism. It is a versatile tool to deal with World Wide Web copy-pasting information from the assignment of authorship. The goal of this program is to help reduce the impact of plagiarism on education and educational institutions. Checking documents in a format *.rtf, *.doc, *.docx, *.pdf Check the source code C, C++, C#, Java, ...
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Ralph for Claude Code
Autonomous development loop that iteratively improves projects
Ralph for Claude Code is an autonomous AI development loop framework designed to continuously iterate on a software project until predefined goals are achieved. It implements a technique that enables Claude Code to repeatedly analyze, modify, and improve a codebase through structured development cycles. It automates the process of running AI-assisted development tasks, allowing the model to progressively refine a project without constant manual intervention. Ralph introduces mechanisms to... -
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Python Code Tutorials
The Python Code Tutorials
Python Code Tutorials is a large educational repository that aggregates programming tutorials from the “The Python Code” website into a structured collection of Python projects and learning materials. The repository covers a wide range of programming topics including cybersecurity, networking, web scraping, machine learning, GUI development, and automation scripts. Each tutorial typically includes complete Python code examples and explanations that demonstrate how to build real tools and... -
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Claude Code Usage Monitor
Real-time Claude Code usage monitor with predictions and warnings
Claude Code Usage Monitor is a developer-focused terminal tool that provides real-time visibility into Claude Code token consumption and session behavior. The project is designed to help users avoid unexpectedly hitting usage caps by continuously tracking token burn rate, message counts, and estimated costs during active sessions. It presents analytics through a visually rich terminal interface built with modern Python tooling, making it easy to interpret usage trends at a glance. The system... -
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Highlight.js
JavaScript syntax highlighter with language auto-detection
Highlight.js is a syntax highlighter written in JavaScript. It works in the browser as well as on the server. It can work with pretty much any markup, doesn’t depend on any other frameworks, and has automatic language detection. Highlight.js supports over 180 languages in the core library. There are also 3rd party language definitions available to support even more languages. We strongly recommend <pre><code> wrapping for code blocks. It's quite semantic and "just works" out of the box with... -
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InsightFace
State-of-the-art 2D and 3D Face Analysis Project
State-of-the-art deep face analysis library. InsightFace is an open-source 2D&3D deep face analysis library. InsightFace is an integrated Python library for 2D&3D face analysis. InsightFace efficiently implements a wide variety of state-of-the-art algorithms for face recognition, face detection, and face alignment, which are optimized for both training and deployment. Research institutes and industrial organizations can get benefits from InsightFace library. -
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Code Quality and Security for Java
SonarSource Static Analyzer for Java Code Quality and Security
Hundreds of unique rules to find Java bugs, code smells & vulnerabilities. Sonar static analysis helps you build and maintain high-quality Java code. Covering popular build systems, standards and versions, Sonar elevates your coding game while keeping vulnerabilities at bay. With each Java version, we create dedicated rules so you learn shiny, new features and avoid pitfalls. Consistently find tricky, hard-to-spot issues in your regular expressions. Allow you to effortlessly repair your Java... -
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CutLER
Code release for Cut and Learn for Unsupervised Object Detection
CutLER is an approach for unsupervised object detection and instance segmentation that trains detectors without human-annotated labels, and the repo also includes VideoCutLER for unsupervised video instance segmentation. The method follows a “Cut-and-LEaRn” recipe: bootstrap object proposals, refine them iteratively, and train detection/segmentation heads to discover objects across diverse datasets. The codebase provides training and inference scripts, model configs, and references to... -
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RA.Aid
Develop software autonomously
RA.Aid is an AI-powered assistant designed to enhance the efficiency of software development workflows. It integrates seamlessly with various development environments, providing intelligent code suggestions, automated documentation generation, and real-time error detection. By leveraging advanced machine learning models, RA.Aid aims to reduce development time and improve code quality. -
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dlib
Toolkit for making machine learning and data analysis applications
Dlib is a modern C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems. It is used in both industry and academia in a wide range of domains including robotics, embedded devices, mobile phones, and large high performance computing environments. Dlib's open source licensing allows you to use it in any application, free of charge. Good unit test coverage, the ratio of unit test lines of code to library lines of code is... -
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Al-Khaser
Public malware techniques used in the wild: Virtual Machine, Emulation
al-khaser is an open-source proof-of-concept security tool that deliberately implements techniques commonly used by real-world malware to test and evaluate the effectiveness of antivirus and endpoint detection and response (EDR) systems. It’s written in C/C++ and designed to execute a wide range of anti-analysis, anti-debugging, anti-virtualization, timing-based evasion, and sandbox detection routines so security researchers and defenders can see how well their tools detect or ignore these... -
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Machine Learning Octave
MatLab/Octave examples of popular machine learning algorithms
This repository contains MATLAB / Octave implementations of popular machine learning algorithms, along with explanatory code and mathematical derivations, intended as educational material rather than production code. Implementations of supervised learning algorithms (linear regression, logistic regression, neural nets). The author’s goal is to help users understand how each algorithm works “from scratch,” avoiding black-box library calls. Code written so as to expose and comment on... -
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Google AI Edge Gallery
A gallery that showcases on-device ML/GenAI use cases
Gallery is a curated collection of on-device machine learning examples, demo apps, and model artifacts designed to help developers experiment with and deploy ML at the edge. The project bundles runnable samples that show how to run TensorFlow Lite/Edge TPU models (and similar lightweight runtimes) on mobile and embedded platforms, demonstrating common tasks like image classification, object detection, audio recognition, and pose estimation. Each sample is intended to be both a learning aid... -
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CDviz
View software deployment's events & states
cdviz is a developer-focused visualization and analysis tool designed to help engineers understand, monitor, and optimize codebases by providing insights into structure, performance, and execution patterns. It likely focuses on transforming complex code relationships into visual representations that improve comprehension and debugging efficiency. The system may include static analysis capabilities, enabling it to detect inefficiencies, dependencies, or architectural issues within a project.... -
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Void Editor
Open source AI IDE and Cursor alternative
Void is an open-source, AI-powered code editor built as a fork of Visual Studio Code. Designed as a fully transparent and privacy-focused alternative to Cursor or GitHub Copilot, it lets you use AI models locally or via APIs (OpenAI, Claude, Gemini, Ollama, etc.)—without routing data through proprietary servers. Developed by YC-backed startup Glass Devtools, it supports traditional coding features inherited from VS Code, enhanced with in-editor LLM capabilities—autocomplete, inline quick... -
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Random Cut Forest by AWS
An implementation of the Random Cut Forest data structure
This repository contains implementations of the Random Cut Forest (RCF) probabilistic data structure. RCFs were originally developed at Amazon to use in a nonparametric anomaly detection algorithm for streaming data. Later new algorithms based on RCFs were developed for density estimation, imputation, and forecasting. The different directories correspond to equivalent implementations in different languages, and bindings to to those base implementations, using language-specific features for... -
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changedetection.io
The best free open source website change detection and restock service
Loved by smart shoppers, data journalists, research engineers, data scientists, security researchers, and more. From simply monitoring website pages that have a change (such as watching prices, and restocking notifications), to deep inspection such as PDF text support, JSON and XML monitoring, and extensive text triggers. Monitor out-of-stock products and get alerts when those products are back in stock, get restock alerts via Discord, Slack, email, and many other platforms. Using the... -
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ML.NET
Open source and cross-platform machine learning framework for .NET
With ML.NET, you can create custom ML models using C# or F# without having to leave the .NET ecosystem. ML.NET lets you re-use all the knowledge, skills, code, and libraries you already have as a .NET developer so that you can easily integrate machine learning into your web, mobile, desktop, games, and IoT apps. ML.NET offers Model Builder (a simple UI tool) and ML.NET CLI to make it super easy to build custom ML Models. These tools use Automated ML (AutoML), a cutting edge technology that... -
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satellite-image-deep-learning
Resources for deep learning with satellite & aerial imagery
This page lists resources for performing deep learning on satellite imagery. To a lesser extent classical Machine learning (e.g. random forests) are also discussed, as are classical image processing techniques. Note there is a huge volume of academic literature published on these topics, and this repository does not seek to index them all but rather list approachable resources with published code that will benefit both the research and developer communities. If you find this work useful... -
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rebroswer-patches
Patches for Puppeteer and Playwright to reduce automation detection
rebrowser-patches is an open source collection of patches designed to improve the stealth capabilities of browser automation frameworks. It focuses primarily on enhancing Puppeteer and Playwright by modifying parts of their source code that may reveal automation activity to websites. Many modern websites rely on bot detection mechanisms that identify automation through behavioral or technical signals, and these patches aim to reduce those detection vectors. ... -
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QMK Toolbox
A Toolbox companion for QMK Firmware
This is a collection of flashing tools packaged into one app. It supports auto-detection and auto-flashing of firmware to keyboards. Make sure your newly-flashed keyboard is working as expected. No-fuss installation of drivers for all supported bootloaders on Windows. Debug your code using QMK's Console feature. -
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DeepDetect
Deep Learning API and Server in C++14 support for Caffe, PyTorch
The core idea is to remove the error sources and difficulties of Deep Learning applications by providing a safe haven of commoditized practices, all available as a single core. While the Open Source Deep Learning Server is the core element, with REST API, and multi-platform support that allows training & inference everywhere, the Deep Learning Platform allows higher level management for training neural network models and using them as if they were simple code snippets. Ready for applications of image tagging, object detection, segmentation, OCR, Audio, Video, Text classification, CSV for tabular data and time series. ... -
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Context7 Platform
Up-to-date code documentation for LLMs and AI code editors
Context7 is a system that aims to inject fresh, version-specific documentation and code snippets into language model prompts, thereby avoiding reliance on outdated training data or hallucinated APIs. It’s designed to integrate with tools that support the Model Context Protocol (MCP), such as Cursor, Windsurf, and other LLM clients. When a user writes a prompt and appends something like “use context7,” the system detects the libraries or frameworks being asked about, fetches the latest... -
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Umi-OCR
OCR software, free and offline
...The software supports flexible usage patterns including screenshot capture OCR, batch processing of large sets of images or documents, PDF parsing, QR code detection, and layout-aware paragraph output. Users can interact with Umi-OCR through a graphical interface, command-line options, or HTTP interfaces, making it adaptable to both casual desktop usage and programmatic automation. Because the project is open source, developers can inspect, modify, and extend its capabilities, and plugins allow for different recognition engines or enhanced features. -
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Exclusively Dark Image Dataset
ExDARK dataset is the largest collection of low-light images
...It contains 7,363 images captured across ten different low-light scenarios, ranging from extremely dark environments to twilight. Each image is annotated with both image-level labels and object-level bounding boxes for 12 object categories, making it suitable for detection and classification tasks. The dataset was created to address the lack of large-scale low-light datasets available for research in object detection, recognition, and enhancement. It has been widely used in studies of low-light image enhancement, deep learning approaches, and domain adaptation for vision models. Researchers can also explore its associated source code for low-light image enhancement tasks, making it an essential resource for advancing work in night-time and low-light visual recognition.
