Search Results for "object detection"
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Showing 64 open source projects for "object detection"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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DeltaForce-OBS-Locker
Delta Action OBS Lock Plugin
DeltaForce-OBS-Locker is a research-oriented repository around OBS-based computer vision experiments for the game Delta Force. The project includes desktop and mobile components and discusses image recognition, rendering capture, simulated input, and real-time detection ideas. Its README states that a YOLOv14-based real-time object detection framework was integrated into the desktop side for visual recognition experiments. The project also references fisheye or wide-angle correction, small-object detection, and mobile demonstration code. Because the repository is closely tied to gameplay automation and competitive-game assistance, it should be treated as an educational computer vision case study rather than a fair-play gaming tool. ... -
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trackers
Multi-object tracking algorithms
trackers is a plug-and-play multi-object tracking library designed to work with virtually any object detection model, enabling developers to follow objects across video frames with minimal setup. The library provides clean, modular implementations of leading tracking algorithms and can be used either from the command line or embedded directly into Python pipelines. It supports inputs such as videos, webcams, RTSP streams, or image directories and produces annotated tracking outputs that include labels and trajectories. ... -
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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. -
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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. ... -
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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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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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Albumentations
Fast image augmentation library and an easy-to-use wrapper
...Albumentations efficiently implements a rich variety of image transform operations that are optimized for performance, and does so while providing a concise, yet powerful image augmentation interface for different computer vision tasks, including object classification, segmentation, and detection. Albumentations supports different computer vision tasks such as classification, semantic segmentation, instance segmentation, object detection, and pose estimation. Albumentations works well with data from different domains: photos, medical images, satellite imagery, manufacturing and industrial applications, Generative Adversarial Networks. ... -
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YOLOv9
Learning What You Want to Learn Using Programmable Gradient Info
YOLOv9 is the official implementation of the paper “YOLOv9: Learning What You Want to Learn Using Programmable Gradient Information.” It is a modern object detection repository focused on improving how deep networks preserve useful information during training. 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. ... -
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fuite
A tool for finding memory leaks in web apps
Fuite is a command-line tool for detecting JavaScript memory leaks in web applications through automated Chrome testing. It launches Chromium with Puppeteer and repeatedly runs user interactions to identify objects that accumulate across iterations. The analyzer checks heap objects, event listeners, DOM nodes, arrays, maps, sets, and plain objects. Its default scenario navigates internal links and returns to the starting page, which works well for client-rendered applications. Custom... -
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anti-slop
Opinionated Oxlint rules for rejecting low-evidence TypeScript
Anti-slop is an opinionated Oxlint rule set for rejecting low-evidence TypeScript and JavaScript patterns. It is designed to be copied into a repository and customized rather than consumed as a fixed npm dependency. Its rules target practices such as chained type assertions, unsafe dictionary types, broad object parameters, ad hoc runtime type checks, module mocking, and contracts that return unknown. Type assertions can be required to include a safety comment explaining the checked... -
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Dlib is a C++ toolkit containing machine learning algorithms and tools for creating complex software in C++ to solve real world problems.
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autotools-idl is a patch for automake and some autoconf scripts that adds support for IDL and C++ ORBs. It provides full support for compiling IDL files to C++ stubs and skeletons. The autoconf scripts provide unified detection of different C++ ORBs.
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ZenoTest
Automated UI testing for Windows apps – fast, stable, simple.
ZenoTest is a powerful and lightweight tool for automating Windows desktop UI testing. It supports a wide range of technologies including WPF, WinForms, Qt, and native applications, without requiring plugins or framework-specific integrations. With its intelligent object recognition, ZenoTest reliably identifies UI elements even when layouts change, ensuring stable and maintainable test cases. The built-in recorder and C-like scripting language make it easy to create, customize, and reuse... -
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gSOAP Toolkit
Development toolkit for Web Services and XML data bindings for C & C++
The gSOAP toolkit is an extensive suite of portable C and C++ software to develop XML Web services with powerful type-safe XML data bindings. Easy-to-use code-generator tools allow you to directly integrate XML data in C and C++. Serializes native application data in XML. Includes WSDL/XSD schema binding and auto-coding tools, stub/skeleton compiler, Web server integration with Apache module and IIS extension, high-performance XML processing with schema validation, fast MIME/MTOM streaming,... -
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WhichBrowser
Browser sniffing gone too far — A useragent parser library for PHP
This is an extremely complicated and almost completely useless browser-sniffing library. Useless because you shouldn't use browser sniffing. So stop right now and go read something about feature detecting instead. I'm serious. Go away. You'll thank me later. There is always an exception to the rule. There are valid reasons to do browser sniffing: to improve the user experience or to gather intelligence about which browsers are used on your website. My website is html5test.com and I wanted to... -
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LifeAI is an artificial intelligence system that can be applied to robotics, games, or business. It simulates key processes of our minds, such as organizing data into concepts and categories, planning actions based on their predicted outcome, and communication. LifeAI was designed to be simple, but powerful and flexible enough to have many applications.
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ImageAI
A python library built to empower developers
ImageAI is an easy-to-use Computer Vision Python library that empowers developers to easily integrate state-of-the-art Artificial Intelligence features into their new and existing applications and systems. It is used by thousands of developers, students, researchers, tutors and experts in corporate organizations around the world. You will find features supported, links to official documentation as well as articles on ImageAI. ImageAI is widely used around the world by professionals,... -
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Darknet YOLO
Real-Time Object Detection for Windows and Linux
This is YOLO-v3 and v2 for Windows and Linux. YOLO (You only look once) is a state-of-the-art, real-time object detection system of Darknet, an open source neural network framework in C. YOLO is extremely fast and accurate. It uses a single neural network to divide a full image into regions, and then predicts bounding boxes and probabilities for each region. This project is a fork of the original Darknet project. -
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PyTorch Transfer-Learning-Library
Transfer Learning Library for Domain Adaptation, Task Adaptation, etc.
TLlib is an open-source and well-documented library for Transfer Learning. It is based on pure PyTorch with high performance and friendly API. Our code is pythonic, and the design is consistent with torchvision. You can easily develop new algorithms or readily apply existing algorithms. We appreciate all contributions. If you are planning to contribute back bug-fixes, please do so without any further discussion. If you plan to contribute new features, utility functions or extensions, please... -
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Official YOLOv7
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art
...It supports multiple model sizes and related tasks such as object detection and instance segmentation through associated branches or weights. It is useful for researchers, engineers, and developers building detection systems for video, edge devices, robotics, analytics, and industrial vision. -
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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. ... -
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YOLOV4 Pytorch
This is a source code for YoloV4-pytorch that can be used to train you
YOLOV4 Pytorch is a PyTorch implementation of the YOLOv4 object detection model for training and running custom detection systems. 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. -
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YOLOV3 Pytorch
This is a source code for yolo3-pytorch
YOLOV3 Pytorch is a PyTorch implementation of the YOLOv3 object detection model built for training, prediction, and evaluation. The repository provides a complete workflow for users who want to train their own object detector with VOC-style data or use pretrained weights. It includes utilities for annotation conversion, anchor generation, image prediction, video prediction, batch prediction, FPS measurement, heatmap output, and mAP evaluation. -
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Flashlight library
A C++ standalone library for machine learning
Flashlight is a fast, flexible machine learning library written entirely in C++ by Facebook AI Research and the creators of Torch, TensorFlow, Eigen, and Deep Speech. Native support in C++ and simple extensibility make Flashlight a powerful research framework that's hackable to its core and enables fast iteration on new experimental setups and algorithms with little unopinionated and without sacrificing performance. In a single repository, Flashlight provides apps for research across... -
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Faster-Rcnn
This is a pytorch implementation library of faster-rcnn
Faster-Rcnn is a PyTorch implementation of the Faster R-CNN two-stage object detection model. It is designed for training and evaluating detectors on VOC-format datasets, including VOC07+12 and custom datasets arranged with VOC-style annotations and images. The repository includes scripts for training, prediction, evaluation, annotation generation, and model summary inspection. It supports backbone options through pretrained VGG and ResNet weights, making it useful for comparing feature extractors. ...
