Object Tracking and Detection Using OpenCV

Overview

Object-Tracking-and-Detection-Using-OpenCV

Object tracking is one such application of computer vision where an object is detected in a video, otherwise interpreted as a set of frames, and the object’s trajectory is estimated. For instance, you have a video of a baseball match, and you want to track the ball’s location constantly throughout the video.

OpenCV-based object tracking

Object tracking using OpenCV is a popular method that is extensively used in the domain. OpenCV has a number of built-in functions specifically designed for the purpose of object tracking. Some object trackers in OpenCV include MIL, CSRT, GOTURN, and MediandFlow. Selecting a specific tracker depends on the application you are trying to design. Each tracker has its advantages and disadvantages, and a single type of tracker is not desired in all the applications.

Owner
Happy N. Monday
Wavelet Transform | Machine Learning | Computer Vision | Deep Learning | Image Processing | AI
Happy N. Monday
A Comparative Framework for Multimodal Recommender Systems

Cornac Cornac is a comparative framework for multimodal recommender systems. It focuses on making it convenient to work with models leveraging auxilia

Preferred.AI 671 Jan 03, 2023
Framework for joint representation learning, evaluation through multimodal registration and comparison with image translation based approaches

CoMIR: Contrastive Multimodal Image Representation for Registration Framework 🖼 Registration of images in different modalities with Deep Learning 🤖

Methods for Image Data Analysis - MIDA 55 Dec 09, 2022
Implementation of Barlow Twins paper

barlowtwins PyTorch Implementation of Barlow Twins paper: Barlow Twins: Self-Supervised Learning via Redundancy Reduction This is currently a work in

IgorSusmelj 86 Dec 20, 2022
MQBench: Towards Reproducible and Deployable Model Quantization Benchmark

MQBench: Towards Reproducible and Deployable Model Quantization Benchmark We propose a benchmark to evaluate different quantization algorithms on vari

494 Dec 29, 2022
Find-Lane-Line - Use openCV library and Python to detect the road-lane-line

Find-Lane-Line This project is to use openCV library and Python to detect the road-lane-line. Data Pipeline Step one : Color Selection Step two : Cann

Kenny Cheng 3 Aug 17, 2022
Python scripts form performing stereo depth estimation using the CoEx model in ONNX.

ONNX-CoEx-Stereo-Depth-estimation Python scripts form performing stereo depth estimation using the CoEx model in ONNX. Stereo depth estimation on the

Ibai Gorordo 8 Dec 29, 2022
A dataset for online Arabic calligraphy

Calliar Calliar is a dataset for Arabic calligraphy. The dataset consists of 2500 json files that contain strokes manually annotated for Arabic callig

ARBML 114 Dec 28, 2022
Source for the paper "Universal Activation Function for machine learning"

Universal Activation Function Tensorflow and Pytorch source code for the paper Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal acti

4 Dec 03, 2022
Complementary Patch for Weakly Supervised Semantic Segmentation, ICCV21 (poster)

CPN (ICCV2021) This is an implementation of Complementary Patch for Weakly Supervised Semantic Segmentation, which is accepted by ICCV2021 poster. Thi

Ferenas 20 Dec 12, 2022
OpenVINO黑客松比赛项目

Window_Guard OpenVINO黑客松比赛项目 英文名称:Window_Guard 中文名称:窗口卫士 硬件 树莓派4B 8G版本 一个磁石开关 USB摄像头(MP4视频文件也可以) 软件(库) OpenVINO RPi 使用方法 本项目使用的OPenVINO是是2021.3版本,并使用了

Tango 6 Jul 04, 2021
Official implementation of VQ-Diffusion

Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis

Microsoft 592 Jan 03, 2023
Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Official re-implementation of the Calibrated Adversarial Refinement model described in the paper Calibrated Adversarial Refinement for Stochastic Semantic Segmentation

Elias Kassapis 31 Nov 22, 2022
PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos

PyKale is a PyTorch library for multimodal learning and transfer learning as well as deep learning and dimensionality reduction on graphs, images, texts, and videos. By adopting a unified pipeline-ba

PyKale 370 Dec 27, 2022
Revisting Open World Object Detection

Revisting Open World Object Detection Installation See INSTALL.md. Dataset Our n

58 Dec 23, 2022
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

Reminder ST-GCN has transferred to MMSkeleton, and keep on developing as an flexible open source toolbox for skeleton-based human understanding. You a

sijie yan 1.1k Dec 25, 2022
DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

Microsoft 8.4k Jan 01, 2023
Specification language for generating Generalized Linear Models (with or without mixed effects) from conceptual models

tisane Tisane: Authoring Statistical Models via Formal Reasoning from Conceptual and Data Relationships TL;DR: Analysts can use Tisane to author gener

Eunice Jun 11 Nov 15, 2022
Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Video Object Segmentation.

Training Script for Reuse-VOS This code implementation of CVPR 2021 paper : Learning Dynamic Network Using a Reuse Gate Function in Semi-supervised Vi

HYOJINPARK 22 Jan 01, 2023
A PyTorch implementation for V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

A PyTorch implementation of V-Net Vnet is a PyTorch implementation of the paper V-Net: Fully Convolutional Neural Networks for Volumetric Medical Imag

Matthew Macy 606 Dec 21, 2022
Code and data of the Fine-Grained R2R Dataset proposed in paper Sub-Instruction Aware Vision-and-Language Navigation

Fine-Grained R2R Code and data of the Fine-Grained R2R Dataset proposed in the EMNLP2020 paper Sub-Instruction Aware Vision-and-Language Navigation. C

YicongHong 34 Nov 15, 2022