This repo is about implementing different approaches of pose estimation and also is a sub-task of the smart hospital bed project :smile:

Last update: Oct 17, 2022

Overview

Pose-Estimation

This repo is a sub-task of the smart hospital bed project which is about implementing the task of pose estimation 😄 Many thanks to the main authors of hrnet-human-pose-estimation project - the project I'd mainly based on.

Setup

Data preparation

I used coco dataset(2017) which can be downloaded here, and the format is just like this:

${POSE_ROOT}
|-- data
`-- |-- coco
    `-- |-- annotations
        |   |-- person_keypoints_train2017.json
        |   `-- person_keypoints_val2017.json
        |-- person_detection_results
        |   |-- COCO_val2017_detections_AP_H_56_person.json
        |   |-- COCO_test-dev2017_detections_AP_H_609_person.json
        `-- images
            |-- train2017
            |   |-- 000000000009.jpg
            |   |-- 000000000025.jpg
            |   |-- 000000000030.jpg
            |   |-- ... 
            `-- val2017
                |-- 000000000139.jpg
                |-- 000000000285.jpg
                |-- 000000000632.jpg
                |-- ...

Dependencies

Here are required packages:

torch
torchvision
numpy
json_tricks
yacs>=0.1.5
Cython

You also need to install cocoapi:

git clone https://github.com/cocodataset/cocoapi.git
cd cocoapi/PythonAPI
# Install into global site-packages
make install
# Alternatively, if you do not have permissions or prefer
# not to install the COCO API into global site-packages
python3 setup.py install --user
cd ..

Usage

pip install -r requirements.txt
cd src
python3 main.py # update later

Citation

@inproceedings{sun2019deep,
  title={Deep High-Resolution Representation Learning for Human Pose Estimation},
  author={Sun, Ke and Xiao, Bin and Liu, Dong and Wang, Jingdong},
  booktitle={CVPR},
  year={2019}
}

@inproceedings{xiao2018simple,
    author={Xiao, Bin and Wu, Haiping and Wei, Yichen},
    title={Simple Baselines for Human Pose Estimation and Tracking},
    booktitle = {European Conference on Computer Vision (ECCV)},
    year = {2018}
}

This repo is about implementing different approaches of pose estimation and also is a sub-task of the smart hospital bed project :smile:

Related tags

Overview

Pose-Estimation

Setup

Data preparation

Dependencies

Usage

Citation

Owner

Max

Zero-shot Learning by Generating Task-specific Adapters

Unofficial Implementation of MLP-Mixer, gMLP, resMLP, Vision Permutator, S2MLPv2, RaftMLP, ConvMLP, ConvMixer in Jittor and PyTorch.

Awesome Weak-Shot Learning

A Structured Self-attentive Sentence Embedding

DNA-RECON { Automatic Web Reconnaissance Tool }

Experiments for Neural Flows paper

DLWP: Deep Learning Weather Prediction

SOLO and SOLOv2 for instance segmentation, ECCV 2020 & NeurIPS 2020.

Non-Metric Space Library (NMSLIB): An efficient similarity search library and a toolkit for evaluation of k-NN methods for generic non-metric spaces.

Neurons Dataset API - The official dataloader and visualization tools for Neurons Datasets.

Official Pytorch implementation of 6DRepNet: 6D Rotation representation for unconstrained head pose estimation.

Pytorch implement of 'Unmixing based PAN guided fusion network for hyperspectral imagery'

Learning to Prompt for Vision-Language Models.

Multi-Agent Reinforcement Learning for Active Voltage Control on Power Distribution Networks (MAPDN)

ChainerRL is a deep reinforcement learning library built on top of Chainer.

SwinIR: Image Restoration Using Swin Transformer

AfriBERTa: Exploring the Viability of Pretrained Multilingual Language Models for Low-resourced Languages

mlpack: a scalable C++ machine learning library --

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

Evolutionary Population Curriculum for Scaling Multi-Agent Reinforcement Learning