Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

Last update: Jan 17, 2022

Overview

Pose Detection

Project Description:

Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

Requirements:

Following modules need to be installed for it to work properly:

Mediapipe
Cv2

OpenCV:

OpenCV is a huge open-source library for computer vision, machine learning, and image processing. OpenCV supports a wide variety of programming languages like Python, C++, Java, etc. It can process images and videos to identify objects, faces, or even the handwriting of a human.

It can be installed using "pip install opencv-python"

Mediapipe:

MediaPipe is a framework for building multimodal (eg. video, audio, any time series data), cross platform (i.e Android, iOS, web, edge devices) applied ML pipelines.

It can be installed using "pip install mediapipe"

Contact Me:

Owner

Hassan Shahzad

I am a passionate Software Developer who is always aspiring to learn more. Practice makes perfect and I am always working on improving my skills and myself.

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Human pose estimation from video plays a critical role in various applications such as quantifying physical exercises, sign language recognition, and full-body gesture control.

Related tags

Overview

Pose Detection

Project Description:

Requirements:

OpenCV:

Mediapipe:

Contact Me:

Owner

Hassan Shahzad

Object detection (YOLO) with pytorch, OpenCV and python

a generic C++ library for image analysis

MetaBalance: Improving Multi-Task Recommendations via Adapting Gradient Magnitudes of Auxiliary Tasks

Unified Pre-training for Self-Supervised Learning and Supervised Learning for ASR

DTCN SMP Challenge - Sequential prediction learning framework and algorithm

External Attention Network

Cross-Task Consistency Learning Framework for Multi-Task Learning

CPF: Learning a Contact Potential Field to Model the Hand-object Interaction

A Jupyter notebook to play with NVIDIA's StyleGAN3 and OpenAI's CLIP for a text-based guided image generation.

A Flow-based Generative Network for Speech Synthesis

BLEURT is a metric for Natural Language Generation based on transfer learning.

Quantization library for PyTorch. Support low-precision and mixed-precision quantization, with hardware implementation through TVM.

Official pytorch implementation of the AAAI 2021 paper Semantic Grouping Network for Video Captioning

Python scripts form performing stereo depth estimation using the high res stereo model in PyTorch .

Get a Grip! - A robotic system for remote clinical environments.

Omniverse sample scripts - A guide for developing with Python scripts on NVIDIA Ominverse

[WWW 2021] Source code for "Graph Contrastive Learning with Adaptive Augmentation"

Official implementation of the ICCV 2021 paper "Conditional DETR for Fast Training Convergence".

A curated list of automated deep learning (including neural architecture search and hyper-parameter optimization) resources.

Elucidating Robust Learning with Uncertainty-Aware Corruption Pattern Estimation