# Real-Time Object Detection And Tracking

> Search results for `real-time object detection and tracking` on awesome-repositories.com. 113 total matches; showing the first 50.

Explore on the web: https://awesome-repositories.com/q/real-time-object-detection-and-tracking

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## Results

- [abhineet123/deep-learning-for-tracking-and-detection](https://awesome-repositories.com/repository/abhineet123-deep-learning-for-tracking-and-detection.md) (2,508 ⭐) — This project is a curated research repository and structured index focused on deep learning techniques for object detection and tracking. It serves as a centralized archive for academic papers, datasets, and software implementations, providing a cohesive resource for studying methodologies used in image and video analysis.

The repository distinguishes itself through a systematic approach to knowledge management, utilizing hierarchical file organization and metadata-driven tagging to categorize technical literature. By indexing domain-specific datasets and cross-referencing academic resources,
- [eduardolundgren/tracking.js](https://awesome-repositories.com/repository/eduardolundgren-tracking-js.md) (9,472 ⭐) — tracking.js is a browser computer vision library written in JavaScript for performing real-time image analysis and object tracking directly within a web browser. It functions as a real-time object tracker, a color tracking tool, and a face detection utility.

The library enables the detection and monitoring of specific color ranges, human faces, and known visual patterns across consecutive video frames. It extracts visual features and descriptors from images to identify distinct landmarks for matching and tracking.

The project covers broad computer vision capabilities, including the ability t
- [corentinj/real-time-voice-cloning](https://awesome-repositories.com/repository/corentinj-real-time-voice-cloning.md) (59,918 ⭐) — This project is a neural text-to-speech engine and voice cloning toolkit designed to generate synthetic speech that mimics the vocal characteristics of a target speaker. It functions as a real-time audio synthesizer, utilizing a deep learning pipeline to convert written text into high-fidelity speech output with minimal latency.

The system employs a transfer learning framework that leverages pre-trained speaker verification models to adapt synthesis to new, unseen vocal identities. By using an encoder-based speaker embedding process, the toolkit maps variable-length audio samples into a laten
- [awesome-selfhosted/awesome-selfhosted](https://awesome-repositories.com/repository/awesome-selfhosted-awesome-selfhosted.md) (299,516 ⭐) — This project is a community-curated directory of open-source software designed for deployment in private server environments and home labs. It serves as a comprehensive resource for discovering independent, self-hosted alternatives to mainstream cloud services, enabling users to maintain full data ownership and control over their digital infrastructure.

The directory is structured through a hierarchical taxonomy that organizes a vast collection of applications into logical categories, ranging from media management and data analytics to private communication and team productivity tools. It dis
- [ailab-cvc/yolo-world](https://awesome-repositories.com/repository/ailab-cvc-yolo-world.md) (6,425 ⭐) — YOLO-World is a vision-language framework and open-vocabulary object detection model. It identifies objects in images and video based on free-form text prompts without requiring predefined category labels.

The system enables the identification of arbitrary objects by fusing image features with text embeddings. It includes a specialized tool for automated image labeling, which generates bounding box annotations for custom datasets using text-based prompts.

The project provides a deployment pipeline for converting models into quantized ONNX and TFLite formats, supporting real-time inference on
- [fastshift/x-track](https://awesome-repositories.com/repository/fastshift-x-track.md) (6,250 ⭐) — X-Track is a firmware project for an embedded bicycle computer that combines GPS-based speed and ride metrics with offline map navigation. It functions as a GPS bicycle speedometer, displaying speed, distance, altitude, and other ride data on a handlebar-mounted screen, while also serving as an offline map viewer that renders locally stored map tiles without an internet connection.

The project distinguishes itself by including a firmware emulator that runs the embedded code on a PC, enabling development and testing without physical hardware. It also provides GPS-based clock calibration to aut
- [ckormanyos/real-time-cpp](https://awesome-repositories.com/repository/ckormanyos-real-time-cpp.md) (796 ⭐) — Real-Time-C++
- [amusi/awesome-object-detection](https://awesome-repositories.com/repository/amusi-awesome-object-detection.md) (7,499 ⭐) — Awesome Object Detection based on handong1587 github: https://handong1587.github.io/deep_learning/2015/10/09/object-detection.html
- [mrousavy/react-native-vision-camera](https://awesome-repositories.com/repository/mrousavy-react-native-vision-camera.md) (9,479 ⭐) — This project is a cross-platform mobile camera framework and real-time computer vision library. It provides a high-performance interface for mobile applications to handle hardware control, media capture, and live camera frame processing.

The framework includes a dedicated system for running AI models and custom analysis on live camera streams using high-performance worklets. It also functions as a real-time detection and decoding system for QR codes and barcodes.

Broad capabilities cover the capture of high-resolution photos and videos with controls for zoom, HDR, and frame rates. The projec
- [microsoft/airsim](https://awesome-repositories.com/repository/microsoft-airsim.md) (17,956 ⭐) — AirSim is a high-fidelity simulation platform designed for the development and testing of autonomous vehicles. Built as a plugin for game engines, it provides a physics-based environment that models vehicle dynamics and sensor data, serving as a foundation for robotics research, computer vision training, and reinforcement learning.

The platform distinguishes itself through its support for hardware-in-the-loop and software-in-the-loop testing, allowing developers to validate control logic and firmware against real-world signals or concurrent processes. It offers extensive programmatic control
- [serengil/deepface](https://awesome-repositories.com/repository/serengil-deepface.md) (22,226 ⭐) — Deepface is a comprehensive deep learning library for facial recognition and demographic analysis. It provides a modular pipeline that handles the entire lifecycle of facial processing, including detection, geometric alignment, and the transformation of facial images into high-dimensional numerical vector embeddings for identity verification and similarity comparison.

The library distinguishes itself through a model ensemble approach, which combines predictions from multiple pre-trained neural networks to improve classification accuracy and reduce bias. It also integrates advanced security fe
- [praveen-palanisamy/multiple-object-tracking-lidar](https://awesome-repositories.com/repository/praveen-palanisamy-multiple-object-tracking-lidar.md) (891 ⭐) — C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
- [clickhouse/clickhouse](https://awesome-repositories.com/repository/clickhouse-clickhouse.md) (48,229 ⭐) — ClickHouse is a high-performance, columnar analytical database designed for real-time query execution and large-scale data aggregation. It functions as a distributed data warehouse capable of processing petabytes of information, while also providing an embedded engine that integrates directly into applications for native query capabilities without external dependencies. The system is built to handle high-throughput ingestion and complex analytical workloads, delivering millisecond-level latency for interactive dashboards and operational monitoring.

The platform distinguishes itself through ad
- [ultralytics/yolov3](https://awesome-repositories.com/repository/ultralytics-yolov3.md) (10,571 ⭐) — This is a real-time object detection framework built on the YOLOv3 architecture, implemented in PyTorch. It provides a complete pipeline for identifying and localizing objects in images and video using a single neural network pass, combining a Darknet-53 backbone with multi-scale feature pyramids and anchor-based bounding box prediction.

The framework extends beyond basic detection to include instance segmentation, human pose estimation, and multi-object tracking across video frames. It offers a model export toolkit that converts trained models through ONNX to CoreML, TensorFlow Lite, and Ten
- [roboflow/trackers](https://awesome-repositories.com/repository/roboflow-trackers.md) (2,565 ⭐) — This project is a multi-object tracking library and computer vision toolkit designed to maintain consistent identity IDs for objects across video frames. It provides a motion-based object tracking system that converts raw detections into stable temporal tracks, enabling the analysis of object movement and behavior over time.

The toolkit distinguishes itself through advanced identity maintenance, utilizing Kalman filters for linear motion tracking and sparse optical flow for camera motion estimation. It features multi-stage object association to recover occluded objects and non-linear motion t
- [kuanhungchen/awesome-tiny-object-detection](https://awesome-repositories.com/repository/kuanhungchen-awesome-tiny-object-detection.md) (0 ⭐) — A curated list of ``Tiny Object Detection`` papers and related resources.
- [roboflow-ai/zero-shot-object-tracking](https://awesome-repositories.com/repository/roboflow-ai-zero-shot-object-tracking.md) (383 ⭐) — Object tracking using Roboflow Inference API and Zero-Shot (CLIP) Deep SORT. Read more in our Zero-Shot Object Tracking announcement post.
- [roboflow/rf-detr](https://awesome-repositories.com/repository/roboflow-rf-detr.md) (5,643 ⭐) — RF-DETR is a Python library for training and deploying object detection, instance segmentation, and keypoint detection models built on a vision transformer architecture. It provides a unified command-line interface and Python API for the full workflow, from fine-tuning pretrained checkpoints on custom datasets to running inference on images, video files, and live camera streams.

The project supports training on datasets in COCO or YOLO format, with automatic format detection and configurable augmentation pipelines. Models can be exported to ONNX, TFLite, or TensorRT for deployment across edge
- [graphiteeditor/graphite](https://awesome-repositories.com/repository/graphiteeditor-graphite.md) (24,258 ⭐) — Graphite is a node-based visual design environment that integrates vector illustration, raster image processing, and motion graphics generation into a single platform. It utilizes a functional reactive pipeline and a data-flow execution model to propagate state changes through a graph of interconnected nodes, allowing users to construct complex, automated design workflows.

The platform distinguishes itself through a context-aware evaluation engine that injects runtime metadata—such as coordinate data and loop indices—directly into the node graph. This enables the creation of procedural geomet
- [getstream/vision-agents](https://awesome-repositories.com/repository/getstream-vision-agents.md) (6,029 ⭐)
- [kubeshark/kubeshark](https://awesome-repositories.com/repository/kubeshark-kubeshark.md) (11,954 ⭐) — Kubeshark is a network observability platform designed for Kubernetes environments, functioning as an eBPF-powered engine for cluster-wide traffic analysis. It captures, indexes, and visualizes network activity and API calls directly from the kernel, providing deep visibility into service-to-service communication without requiring sidecar proxies or manual code instrumentation.

The platform distinguishes itself through its ability to perform protocol-aware traffic dissection and user-space cryptographic hooking, which allows for the inspection of encrypted traffic and the reconstruction of ap
- [timeclick-software/time-tracking-tools](https://awesome-repositories.com/repository/timeclick-software-time-tracking-tools.md) (1 ⭐) — Time tracking software is essential for businesses that need accurate payroll, employee monitoring, and workforce productivity insights.
- [rafaelpadilla/object-detection-metrics](https://awesome-repositories.com/repository/rafaelpadilla-object-detection-metrics.md) (5,098 ⭐) — This project is an object detection evaluation library and benchmarking tool designed to calculate precision, recall, and average precision for computer vision models. It provides a suite of utilities for parsing bounding box coordinates from text files and calculating spatial overlap to determine detection accuracy.

The toolkit features a command line interface for comparing ground truth files against model predictions. It includes a precision-recall curve generator to visualize the relationship between precision and recall across different confidence thresholds and an intersection over unio
- [ultralytics/yolov5](https://awesome-repositories.com/repository/ultralytics-yolov5.md) (57,528 ⭐) — YOLOv5 is a comprehensive computer vision framework designed for end-to-end deep learning, specializing in real-time object detection, image classification, and instance segmentation. It provides a unified toolkit that manages the entire lifecycle of a model, from initial dataset configuration and hyperparameter tuning to high-speed inference and deployment. The framework utilizes a modular neural architecture, allowing users to swap backbone and head components to tailor models for specific visual tasks.

What distinguishes this project is its focus on production-ready deployment and model ef
- [google/mediapipe](https://awesome-repositories.com/repository/google-mediapipe.md) (35,673 ⭐) — MediaPipe is a cross-platform machine learning framework designed for building and deploying pipelines that process live and streaming media. It provides a system for connecting processing components into custom machine learning chains to analyze real-time audio and video streams.

The framework includes a suite of pre-trained models for tasks such as hand, face, and pose tracking, along with tools for retraining and customizing these models with specific datasets. It also features a dedicated benchmarker for measuring the execution speed and accuracy of machine learning models directly within
- [msracver/relation-networks-for-object-detection](https://awesome-repositories.com/repository/msracver-relation-networks-for-object-detection.md) (1,104 ⭐) — Relation Networks for Object Detection
- [microsoft/onnxruntime](https://awesome-repositories.com/repository/microsoft-onnxruntime.md) (19,347 ⭐) — This project is a cross-platform machine learning inference engine designed to execute pre-trained models across diverse operating systems and hardware environments. It functions as a standardized execution framework that manages the entire lifecycle of model inference, from loading and graph optimization to hardware-accelerated execution and generative sequence management.

The runtime distinguishes itself through a highly modular architecture that decouples model logic from hardware-specific kernels. By utilizing an execution provider abstraction, it enables developers to offload computation
- [hybridgroup/gocv](https://awesome-repositories.com/repository/hybridgroup-gocv.md) (7,463 ⭐) — GoCV is a computer vision library and Go language binding for OpenCV. It serves as an image processing toolkit and deep learning inference engine, providing programmatic access to a wide range of algorithms for image manipulation, object detection, and video analysis.

The project differentiates itself through high-performance native bindings and hardware acceleration. It utilizes a foreign function interface to map Go calls to C++ functions and includes a hardware-agnostic backend dispatch to route neural network tasks to computation engines such as CUDA and OpenVINO.

The library covers a br
- [honojs/hono](https://awesome-repositories.com/repository/honojs-hono.md) (30,994 ⭐) — Hono is a lightweight web framework built on Web Standard APIs that executes across JavaScript runtimes including Cloudflare Workers, Deno, Bun, and Node.js.
- [maudzung/super-fast-accurate-3d-object-detection](https://awesome-repositories.com/repository/maudzung-super-fast-accurate-3d-object-detection.md) (1,125 ⭐) — Super Fast and Accurate 3D Object Detection based on 3D LiDAR Point Clouds (The PyTorch implementation)
- [livekit/livekit](https://awesome-repositories.com/repository/livekit-livekit.md) (19,358 ⭐) — LiveKit is a comprehensive framework for building and orchestrating real-time, multimodal AI agents that interact with users through voice, video, and text. It provides a centralized, event-driven architecture to manage the entire lifecycle of automated participants, from initialization and session state management to graceful shutdown. By utilizing a selective forwarding unit, the platform efficiently routes media streams between participants and agents, ensuring low-latency communication and secure, token-based authentication for all connections.

The platform distinguishes itself through it
- [rangilyu/nanodet](https://awesome-repositories.com/repository/rangilyu-nanodet.md) (6,222 ⭐) — NanoDet-Plus⚡Super fast and lightweight anchor-free object detection model. 🔥Only 980 KB(int8) / 1.8MB (fp16) and run 97FPS on cellphone🔥
- [itseez/opencv](https://awesome-repositories.com/repository/itseez-opencv.md) (89,221 ⭐) — OpenCV is an open-source computer vision library and visual analysis toolkit. It provides a framework for processing static images and dynamic video frames to analyze visual data and extract information using deep learning.

The project functions as a real-time image processing framework, enabling the execution of vision algorithms on live video streams for immediate analysis and data processing.

The toolkit covers a broad range of capabilities including image pattern recognition, real-time video analysis, and visual data extraction. It also supports automated visual inspection for detecting
- [blakeblackshear/frigate](https://awesome-repositories.com/repository/blakeblackshear-frigate.md) (33,778 ⭐) — Frigate is a self-hosted network video recorder that functions as a private, local AI-powered vision engine. It manages video streams by performing real-time object detection, tracking, and classification directly on local hardware, ensuring that security monitoring and activity recording remain independent of cloud services.

The system distinguishes itself through a modular, hardware-accelerated video pipeline that offloads intensive decoding and machine learning inference to dedicated GPUs, NPUs, or specialized accelerators like Coral TPUs and Hailo modules. It utilizes state-based object t
- [d2l-ai/d2l-en](https://awesome-repositories.com/repository/d2l-ai-d2l-en.md) (29,001 ⭐) — This project is an educational platform and research toolkit designed to teach deep learning through a combination of mathematical theory, visual diagrams, and executable code. It provides a comprehensive environment for building, training, and evaluating neural networks, grounding complex concepts in interactive computational notebooks that allow for hands-on experimentation.

The framework distinguishes itself by interleaving theoretical foundations—including linear algebra, calculus, and probability—with practical implementations across multiple industry-standard libraries. It supports flex
- [ashishpatel26/real-time-ml-project](https://awesome-repositories.com/repository/ashishpatel26-real-time-ml-project.md) (762 ⭐) — A curated list of applied machine learning and data science notebooks and libraries across different industries.
- [qqwweee/keras-yolo3](https://awesome-repositories.com/repository/qqwweee-keras-yolo3.md) (7,116 ⭐) — This project is an object detection framework implementing the YOLOv3 architecture using Keras and TensorFlow. It functions as a deep learning vision model and computer vision toolset designed to locate and classify multiple entities within images and video streams using bounding boxes.

The system includes a multi-GPU inference engine to distribute computational loads across several graphics processing units. It also provides a pipeline for creating custom object detectors by retraining pre-trained weights on annotated datasets to recognize user-defined object classes.

The framework covers m
- [langchain-ai/langchainjs](https://awesome-repositories.com/repository/langchain-ai-langchainjs.md) (17,818 ⭐) — LangChain.js is a framework for building, executing, and monitoring stateful agentic applications. It provides an orchestration engine that models workflows as directed graphs, allowing developers to connect language models, data sources, and external tools into modular, multi-step processes.

The platform distinguishes itself through its focus on stateful execution and human-in-the-loop control. It manages agent lifecycles by persisting execution state across threads, enabling fault tolerance and the ability to pause workflows at designated breakpoints for manual review or modification. This
- [paddlepaddle/paddledetection](https://awesome-repositories.com/repository/paddlepaddle-paddledetection.md) (14,243 ⭐) — PaddleDetection is an object detection framework designed for the end-to-end development, training, and deployment of computer vision models. It provides a comprehensive library of modular neural network architectures and pipelines that support object detection, instance segmentation, and multi-object tracking tasks.

The project distinguishes itself through a configuration-driven approach that decouples model components like backbones and heads, allowing for the flexible assembly of custom vision workflows. It incorporates advanced techniques such as anchor-free detection logic, joint detecti
- [jamesm0rr1s/add-and-track-custom-issues](https://awesome-repositories.com/repository/jamesm0rr1s-add-and-track-custom-issues.md) (4 ⭐) — Add & Track Custom Issues is a Burp Suite extension that allows users to add and track manual findings that the automated scanner was unable to identify.
- [liquidgalaxylab/steam-celestial-satellite-tracker-in-real-time](https://awesome-repositories.com/repository/liquidgalaxylab-steam-celestial-satellite-tracker-in-real-time.md) (2 ⭐) — Steam Celestial Satellite tracker in real time
- [wongkinyiu/yolov9](https://awesome-repositories.com/repository/wongkinyiu-yolov9.md) (9,534 ⭐) — YOLOv9 is a real-time computer vision framework and deep learning model designed for image classification, object detection, and instance segmentation. It functions as both a vision model and a trainer, allowing for the optimization of neural network weights on custom datasets using single or multiple GPUs.

The framework utilizes programmable gradient information to perform high-speed identification and location of multiple objects within images and video streams. It extends beyond bounding box detection to provide instance segmentation and panoptic segmentation, which labels every pixel in a
- [doctrine/orm](https://awesome-repositories.com/repository/doctrine-orm.md) (10,172 ⭐) — Doctrine ORM is a PHP object-relational mapper that connects application objects to relational database tables. It uses the data mapper and identity map patterns to decouple the in-memory object model from the database schema, allowing developers to manage data persistence without writing manual SQL.

The project features a dedicated object-oriented query language and programmatic builder for retrieving data based on entities rather than tables. It implements a unit-of-work system to track object changes during a request and synchronize them via atomic transactions.

The capability surface inc
- [kalyanmurapaka45/rock-and-mine-detection](https://awesome-repositories.com/repository/kalyanmurapaka45-rock-and-mine-detection.md) (7 ⭐) — This GitHub repository contains a Machine Learning model for predicting whether an object is a rock or a mine. Leveraging a dataset of object characteristics, this project offers accurate classification capabilities.
- [atlassian/react-beautiful-dnd](https://awesome-repositories.com/repository/atlassian-react-beautiful-dnd.md) (34,049 ⭐) — This project is a declarative drag-and-drop library designed for building accessible and fluid interface interactions within web applications. It provides a component-based interface for managing complex list reordering and spatial relationships between elements, utilizing a specialized state container to coordinate movement logic.

The library distinguishes itself through a focus on accessibility, maintaining a live connection between visual drag states and the browser accessibility tree to support screen readers and keyboard navigation. It optimizes performance by bypassing standard componen
- [thu-mig/yolov10](https://awesome-repositories.com/repository/thu-mig-yolov10.md) (11,316 ⭐) — YOLOv10 is a PyTorch computer vision library and real-time vision framework designed for locating and identifying multiple objects in images and video streams. It functions as an end-to-end object detector that optimizes for high-speed deployment and detection precision.

The project is distinguished by an NMS-free detection architecture that predicts a single bounding box per object, eliminating the need for non-maximum suppression post-processing to reduce inference latency. It further optimizes for edge hardware through scalable weights and a quantization-friendly structure that facilitates
- [gaomingqi/track-anything](https://awesome-repositories.com/repository/gaomingqi-track-anything.md) (6,936 ⭐) — Track-Anything is an AI-driven video object segmentation and tracking system. It utilizes the Segment Anything Model to isolate and mask multiple objects across video frames, providing tools for automated mask propagation and background-filling inpainting.

The system distinguishes itself through a multi-object segmentation pipeline that can follow several distinct targets simultaneously. It includes a video inpainting utility to remove tracked objects and replace them with synthesized background content, as well as temporal mask refinement to correct tracking drift.

The project covers broad
- [dotheevo/selfhosted-apps-docker](https://awesome-repositories.com/repository/dotheevo-selfhosted-apps-docker.md) (2,833 ⭐) — This project is a curated collection of deployment files and configurations for hosting a wide variety of open-source services on a home server. It primarily utilizes Docker and Docker Compose to automate the orchestration, lifecycle management, and deployment of containerized applications.

The repository provides a comprehensive suite for self-hosted infrastructure, covering network management tools, media streaming, and home automation. It includes specialized configurations for securing internal services via reverse proxies, WireGuard VPN tunnels, and automated SSL/TLS certificate manageme
- [dbt-labs/dbt-core](https://awesome-repositories.com/repository/dbt-labs-dbt-core.md) (13,051 ⭐) — dbt-core is a command-line framework for transforming data within a warehouse using modular SQL and version control. It functions as a data transformation engine that enables users to define data structures and business logic through declarative configuration files, which the system then compiles into executable code. By managing complex data dependencies through a directed acyclic graph, it ensures that transformation tasks execute in the correct order while maintaining a manifest-driven state to track lineage and execution history.

The project distinguishes itself through an adapter-based d
- [jamesm0rr1s/burpsuite-add-and-track-custom-issues](https://awesome-repositories.com/repository/jamesm0rr1s-burpsuite-add-and-track-custom-issues.md) (4 ⭐) — Add & Track Custom Issues is a Burp Suite extension that allows users to add and track manual findings that the automated scanner was unable to identify.