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STVIR avatar

STVIR/pysot

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View on GitHub↗
4,600 stele·1,109 fork-uri·Python·Apache-2.0·5 vizualizări

Pysot

pysot este un framework de computer vision conceput pentru urmărirea obiectelor unice (single object tracking). Oferă o platformă pentru implementarea și evaluarea algoritmilor care localizează și urmăresc obiecte țintă specifice în secvențe de cadre video.

Proiectul include implementări ale arhitecturii SiamRPN pentru localizarea bazată pe rețeaua de propunere a regiunilor și modelul SiamMask, care combină urmărirea cu generarea de măști binare pentru a oferi segmentarea la nivel de pixel a obiectelor.

Framework-ul conține, de asemenea, un toolkit de evaluare a urmăririi vizuale utilizat pentru a măsura acuratețea și fiabilitatea algoritmilor de urmărire față de seturile de date standard din industrie.

Features

  • Video Object Tracking - Implements a framework for following a specific target across video frames using computer vision algorithms.
  • SiamMask Models - Implements a model that combines tracking with binary mask generation for pixel-level object segmentation.
  • Siamese Region Proposal Networks - Implements the SiamRPN architecture for high-accuracy region proposal network based object localization.
  • Object Tracking Frameworks - Provides a comprehensive platform for implementing and evaluating single object tracking and video segmentation algorithms.
  • Instance Segmentation Tracking - Combines object tracking with binary masking to isolate and follow the exact shape of target objects.
  • Siamese - Implements a specialized architecture based on Siamese Region Proposal Networks for fast object localization.
  • Visual Tracking Evaluation - Implements frameworks and metrics for measuring the precision of point trajectories and visibility masks in tracking models.
  • Computer Vision - High-performance codebase for visual tracking research.
  • Computer Vision and Image Processing - High-performance codebase for visual tracking research.

Istoric stele

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Întrebări frecvente

Ce face stvir/pysot?

pysot este un framework de computer vision conceput pentru urmărirea obiectelor unice (single object tracking). Oferă o platformă pentru implementarea și evaluarea algoritmilor care localizează și urmăresc obiecte țintă specifice în secvențe de cadre video.

Care sunt principalele funcționalități ale stvir/pysot?

Principalele funcționalități ale stvir/pysot sunt: Video Object Tracking, SiamMask Models, Siamese Region Proposal Networks, Object Tracking Frameworks, Instance Segmentation Tracking, Siamese, Visual Tracking Evaluation, Computer Vision.

Care sunt câteva alternative open-source pentru stvir/pysot?

Alternativele open-source pentru stvir/pysot includ: open-mmlab/mmdetection — This project is a modular research toolkit designed for developing, training, and evaluating deep learning models for… nwojke/deep_sort — DeepSORT is a real-time multi-object tracking framework designed to maintain consistent identities of multiple objects… open-mmlab/mmtracking — mmtracking is a PyTorch video perception framework designed for training and deploying computer vision models that… foundationvision/bytetrack — ByteTrack is a multi-object tracking framework that implements the ByteTrack algorithm, an ECCV 2022 method designed… facebookresearch/sam2 — This project is a foundation model and research toolkit designed for promptable object segmentation and temporal… muhammadmoinfaisal/yolov8-deepsort-object-tracking — This project is a computer vision pipeline that integrates object detection and tracking to monitor moving objects…

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