Search Results for "computer adaptive testing"
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Showing 40 open source projects for "computer adaptive testing"
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BruteForceAI
Advanced LLM-powered brute-force tool combining AI intelligence
BruteForceAI is an open-source security testing tool that applies large language models to the analysis of login forms and authentication flows in web applications. At a high level, the project uses AI to inspect HTML content, identify the relevant form elements, and automate selector discovery so that a tester does not need to hand-map every field before evaluation. It combines that analysis layer with automated credential testing workflows, framing itself as a more adaptive alternative to older brute-force tooling that depends heavily on manual configuration. ... -
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Computer Science Flash Cards
Mini website for testing both general CS knowledge and enforce coding
This repository collects concise flash cards that cover the core ideas of a traditional computer science curriculum with a focus on interview readiness. The cards distill topics like time and space complexity, classic data structures, algorithmic paradigms, operating systems, networking, and databases into short, testable prompts. They are designed for spaced-repetition style study so you can cycle frequently through fundamentals until recall feels automatic. Many cards point at canonical... -
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Conda
OS-agnostic, system-level binary package manager
Conda is an open-source package management system and environment management system that runs on Windows, macOS, and Linux. Conda quickly installs, runs, and updates packages and their dependencies. Conda easily creates, saves, loads, and switches between environments on your local computer. It was created for Python programs but it can package and distribute software for any language. Conda as a package manager helps you find and install packages. If you need a package that requires a... -
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SteadyDancer
Harmonized and Coherent Human Image Animation
SteadyDancer is a research-oriented motion stabilization and dancer tracking system designed to analyze and correct motion in videos, making captured performances appear smoother and more stable while preserving expressiveness. It employs computer vision and motion modeling to estimate and reduce unwanted jitters, shakes, or camera wobbles — particularly in dance or movement sequences where traditional smoothing would distort intentional motion. By differentiating between intentional rhythmic motion and unintentional instability, SteadyDancer applies adaptive filtering that enhances video quality without flattening the core movement dynamics. ... -
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5
AI-DLC
AI-Driven Life Cycle (AI-DLC) adaptive workflow steering rules for AI
AI-DLC is an open-source workflow framework from AWS Labs designed to structure software development around AI-assisted engineering processes. The project promotes an “AI-Driven Life Cycle” methodology where coding assistants, IDE agents, and automation systems participate directly in planning, implementation, testing, and operational workflows. Rather than focusing on a single model or IDE, the framework provides reusable rules, templates, and orchestration patterns compatible with tools... -
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Neuro SAN Studio
A playground for neuro-san
Neuro SAN Studio is a development environment and playground for building, testing, and deploying multi-agent AI systems using the Neuro SAN framework. It provides a hands-on interface where users can design agent networks, run experiments, and observe how multiple agents collaborate to solve complex tasks. The platform is built around a data-driven approach, where entire agent systems can be defined using configuration files rather than extensive code, making it accessible to both... -
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Cybergod
A program that can do anything to earn money without human operators
AGI Computer Control is an experimental autonomous software system designed to operate independently and generate income without human intervention. It aims to simulate artificial general intelligence (AGI) by leveraging evolutionary algorithms, deep active inference, and other advanced AI techniques. The project explores the boundaries of machine autonomy and self-directed behavior in computational environments. -
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Windows-MCP
MCP server enabling AI agents to control and automate Windows OS
...It acts as a bridge that allows large language models to directly interact with desktop environments, enabling automated control over applications, files, and system interfaces. Windows-MCP provides capabilities such as file navigation, application management, UI interaction, and QA testing workflows, making it suitable for building autonomous desktop agents. It focuses on native interaction with Windows UI elements rather than relying on traditional computer vision techniques, which simplifies integration and improves efficiency. It includes a set of tools that simulate user inputs like keyboard and mouse actions while also capturing the current state of windows and interfaces. ... -
9
langrocks
Tools like web browser, computer access and code runner for LLMs
Langrocks is a programming language experimentation toolkit that enables developers to create, test, and optimize custom programming languages. -
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10
Sapiens
High-resolution models for human tasks
Sapiens is a research framework from Meta AI focused on embodied intelligence and human-like multimodal learning, aiming to train agents that can perceive, reason, and act in complex environments. It integrates sensory inputs such as vision, audio, and proprioception into a unified learning architecture that allows agents to understand and adapt to their surroundings dynamically. The project emphasizes long-horizon reasoning and cross-modal grounding—connecting language, perception, and... -
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E2B Desktop Sandbox
E2B Desktop Sandbox for LLMs. E2B Sandbox
...Within a sandbox, developers can launch applications like browsers, editors, or other software that an AI agent may need to interact with. This approach is particularly useful for building AI agents capable of interacting with graphical environments or performing tasks such as browsing, testing software, or automating workflows. -
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MuJoCo
Multi-Joint dynamics with Contact. A general purpose physics simulator
...The platform includes built-in interactive visualization using OpenGL and a native graphical interface for analyzing and testing simulations. Additionally, it offers extensive utility functions for physics computation, Python bindings for developers, and a Unity plug-in to enable integration with game engines and visualization tools. -
13
YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
...The project introduces Programmable Gradient Information and the GELAN architecture to improve gradient flow, parameter efficiency, and train-from-scratch performance. It provides scripts and model assets for training, testing, and running inference on detection tasks. YOLOv9 is designed for real-time detection scenarios where both accuracy and efficiency matter. It is especially relevant for researchers and engineers comparing next-generation YOLO architectures or building production computer vision systems. -
14
imgp
Multi-core image resizer and rotator. Go crunch 'em!
imgp is a command line image resizer and rotator for JPEG and PNG images. If you have tons of images you want to resize adaptively to a screen resolution or rotate by an angle using a single command, imgp is the utility for you. It can save a lot on storage too. Powered by multiprocessing, an intelligent adaptive algorithm, recursive operations, shell completion scripts, EXIF preservation (and more), imgp is a very flexible utility with well-documented easy to use options. imgp intends... -
15
OculiX
Visual Automation IDE — automate anything you see on screen
OculiX is the evolution of SikuliX, actively maintained with the full agreement of its original creator RaiMan. Automate any desktop application using image recognition (OpenCV) and OCR (Tesseract + PaddleOCR). No access to source code or DOM required — if you can see it, you can automate it. Key features: - Guided step-by-step recorder with live code preview - Image recognition via OpenCV 4.10 - Dual OCR: Tesseract (built-in) + PaddleOCR (neural, high precision) - Local and remote... -
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CO3D (Common Objects in 3D)
Tooling for the Common Objects In 3D dataset
...Each of the thousands of sequences in CO3Dv2 captures a common object (from categories like cars, chairs, or plants) from multiple real-world viewpoints. The dataset includes RGB images, depth maps, masks, and camera poses for each frame, along with pre-defined training, validation, and testing splits for both few-view and many-view reconstruction tasks. -
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surtr automation v4.0
Visual desktop automation, OCR, JSON & web automation toolkit
Surtr is a free, open-source Windows automation platform that combines computer vision, OCR, scripting, web automation, and developer tools into one powerful toolkit. Automate applications using image recognition instead of fragile screen coordinates, extract text from screenshots, receipts, and invoices with OCR, record actions into reusable scripts, build workflows visually in SurtrUI, or control everything remotely through the built-in WebUI. -
18
PyNuker
A stress testing tool written in python.
PyNuker is a network stress testing tool written in python. Because it is written in python it should run equally well on any system that has Python version 3.x installed. It infinitely(until stopped) sends a string of text via a UDP packet to a target computer or network device in an effort to flood the target with so much useless traffic that it stops responding to valid requests. -
19
VAMS
Virtual Assistant Maintenance System
Virtual Assistant Maintenance System also knowns as VAMS is an AI software application, that helps users with some computer maintenance issues. Application Requirements: Operating System: Windows 8.1/10 /11 Processor: Intel Core i5 or equivalent RAM: 4GB or higher Free Disk Space: 500MB -
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Hyperformer
Hypergraph Transformer for Skeleton-based Action Recognition
This is the official implementation of our paper "Hypergraph Transformer for Skeleton-based Action Recognition." Skeleton-based action recognition aims to recognize human actions given human joint coordinates with skeletal interconnections. By defining a graph with joints as vertices and their natural connections as edges, previous works successfully adopted Graph Convolutional networks (GCNs) to model joint co-occurrences and achieved superior performance. More recently, a limitation of... -
21
ClassyVision
An end-to-end PyTorch framework for image and video classification
Classy Vision is a PyTorch-based framework designed for large-scale training and deployment of state-of-the-art image and video classification models. Developed by Facebook Research, it serves as an end-to-end system that simplifies the process of training at scale, reducing redundancy and friction in moving from research to production. Unlike traditional computer vision libraries that focus solely on modular components, Classy Vision provides a complete and unified framework, featuring... -
22
agglo
Multi facets CASE/AGL for easy project developments
Agglo is a CASE (Computer Aided Software Engineering) or AGL (Atelier Génie Logiciel), whose aim is to facilitate installation ans use of various tools (either existing opensource tools, or agglo tools), in several facets of project development: - requirements management - unit tests - automated integration tests - toolkit for various languages (cpp, c, python, shell, xsl) other facets are to come ultimately: - coverage tests - planification - integration with hudson - code... -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
...The repository is structured around practical workflows, including training, prediction, evaluation, anchor generation, model configuration, and dataset annotation utilities. It supports VOC-style datasets and includes scripts for prediction, mAP evaluation, FPS testing, video prediction, batch prediction, and heatmap generation. The project added multi-GPU training, seed settings for reproducible results, adaptive learning rate behavior based on batch size, and both step and cosine learning rate schedules. It also supports Adam and SGD optimizer choices, image cropping, adjustable parameters, and extensive code comments. ... -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
YOLOv7 is the official implementation of the paper “YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors.” It is a PyTorch-based object detection project focused on high speed and strong accuracy for real-time computer vision. The repository provides model definitions, training scripts, testing tools, inference examples, pretrained weights, and deployment-oriented materials. YOLOv7 introduced training-time improvements that raise accuracy without increasing inference cost, which is why the project became important in real-time detection research. ... -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
...It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. The project also includes learning rate scheduling through step and cosine methods, optimizer choices between Adam and SGD, adaptive learning rate behavior based on batch size, image cropping, FPS testing, video prediction, and batch prediction. It is a practical reference for users who want a more classical two-stage detector workflow in PyTorch.
