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

Convert game ISO and archives to CD CHD for emulation on Linux.

Cooperative multi-agent reinforcement learning for high-dimensional nonequilibrium control

Single object tracking and segmentation.

A mini-course offered to Undergrad chemistry students

CTRL-C: Camera calibration TRansformer with Line-Classification

Reliable probability face embeddings

A certifiable defense against adversarial examples by training neural networks to be provably robust

The open-source and free to use Python package miseval was developed to establish a standardized medical image segmentation evaluation procedure

A Review of Deep Learning Techniques for Markerless Human Motion on Synthetic Datasets

A real-time approach for mapping all human pixels of 2D RGB images to a 3D surface-based model of the body

Learning Calibrated-Guidance for Object Detection in Aerial Images

The implement of papar "Enhanced Graph Learning for Collaborative Filtering via Mutual Information Maximization"

PyTorch implementation of MSBG hearing loss model and MBSTOI intelligibility metric

Toolkit for collecting and applying prompts

Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)

UV matrix decompostion using movielens dataset

PyTorch implementation of the paper Dynamic Data Augmentation with Gating Networks

Computing Shapley values using VAEAC

A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.

Personal implementation of paper "Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval"