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

Understanding Convolution for Semantic Segmentation

Official repository of OFA. Paper: Unifying Architectures, Tasks, and Modalities Through a Simple Sequence-to-Sequence Learning Framework

Learning Representations that Support Robust Transfer of Predictors

Code for the CVPR2022 paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity"

Unsupervised Discovery of Object Radiance Fields

SuperSDR: multiplatform KiwiSDR + CAT transceiver integrator

TACTO: A Fast, Flexible and Open-source Simulator for High-Resolution Vision-based Tactile Sensors

ruptures: change point detection in Python

SIR model parameter estimation using a novel algorithm for differentiated uniformization.

Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"

The repo of Feedback Networks, CVPR17

Pytorch implementation of "Neural Wireframe Renderer: Learning Wireframe to Image Translations"

Pseudo-rng-app - whos needs science to make a random number when you have pseudoscience?

Code for Dual Contrastive Learning for Unsupervised Image-to-Image Translation, NTIRE, CVPRW 2021.

Pytorch GUI(demo) for iVOS(interactive VOS) and GIS (Guided iVOS)

Implementation of the paper ''Implicit Feature Refinement for Instance Segmentation''.

Semantic Segmentation in Pytorch

Evaluating different engineering tricks that make RL work

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

FairMOT - A simple baseline for one-shot multi-object tracking