Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

Last update: Dec 29, 2022

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Deep Learning openpifpaf

Overview

openpifpaf

Continuously tested on Linux, MacOS and Windows:
New 2021 paper:

OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association
Sven Kreiss, Lorenzo Bertoni, Alexandre Alahi, 2021.

Many image-based perception tasks can be formulated as detecting, associating and tracking semantic keypoints, e.g., human body pose estimation and tracking. In this work, we present a general framework that jointly detects and forms spatio-temporal keypoint associations in a single stage, making this the first real-time pose detection and tracking algorithm. We present a generic neural network architecture that uses Composite Fields to detect and construct a spatio-temporal pose which is a single, connected graph whose nodes are the semantic keypoints (e.g., a person's body joints) in multiple frames. For the temporal associations, we introduce the Temporal Composite Association Field (TCAF) which requires an extended network architecture and training method beyond previous Composite Fields. Our experiments show competitive accuracy while being an order of magnitude faster on multiple publicly available datasets such as COCO, CrowdPose and the PoseTrack 2017 and 2018 datasets. We also show that our method generalizes to any class of semantic keypoints such as car and animal parts to provide a holistic perception framework that is well suited for urban mobility such as self-driving cars and delivery robots.

Previous CVPR 2019 paper.

Guide

Detailed documentation is in our OpenPifPaf Guide. For developers, there is also the DEV Guide which is the same guide but based on the latest code in the main branch.

Examples

Image credit: "Learning to surf" by fotologic which is licensed under CC-BY-2.0.
Created with:

pip3 install openpifpaf matplotlib
python3 -m openpifpaf.predict docs/coco/000000081988.jpg --image-output

Here is the tutorial for body, foot, face and hand keypoints. Example:

Image credit: Photo by Lokomotive74 which is licensed under CC-BY-4.0.
Created with:

python -m openpifpaf.predict guide/wholebody/soccer.jpeg \
  --checkpoint=shufflenetv2k30-wholebody --line-width=2 --image-output

Here is the tutorial for car keypoints. Example:

Image credit: Photo by Ninaras which is licensed under CC-BY-SA 4.0.

Created with:

python -m openpifpaf.predict guide/images/peterbourg.jpg \
  --checkpoint shufflenetv2k16-apollo-24 -o images \
  --instance-threshold 0.05 --seed-threshold 0.05 \
  --line-width 4 --font-size 0

Here is the tutorial for animal keypoints (dogs, cats, sheep, horses and cows). Example:

python -m openpifpaf.predict guide/images tappo_loomo.jpg \
  --checkpoint=shufflenetv2k30-animalpose \
  --line-width=6 --font-size=6 --white-overlay=0.3 \
  --long-edge=500

Commercial License

This software is available for licensing via the EPFL Technology Transfer Office (https://tto.epfl.ch/, [email protected]).

Comments

when i try to run v0.14.0 from source code, it raise ImportError.

I clone the source code from github, then i want to run the openpifpaf/src/openpifpaf/predict.py file.And it raise error.I tracked down the issue and found that the error came from cpp_extension.register_ops()。

extfinder = importlib.machinery.FileFinder(lib_dir, loader_details) ext_specs = extfinder.find_spec("_cpp") if ext_specs is None: raise ImportError

It needs some openpifpaf._cpp files where i found in setup.py. I want to run from the source code, and i do not know how to build this openpifpaf._cpp file,please help!!

opened by KingArtherTT 1
Openpifpaf MPII PlugIn

Train an openpifpaf model with the MPII dataset. Same code as a plugin and reference can be found here: https://github.com/DuncanZauss/openpifpaf_mpii

opened by DuncanZauss 0

Releases(v0.14.0)

v0.14.0(Feb 14, 2022)
create openpifpaf-vita package, with separate development from openpifpaf

deploy openpifpaf-vita guide

Source code(tar.gz)
Source code(zip)

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Official implementation of "OpenPifPaf: Composite Fields for Semantic Keypoint Detection and Spatio-Temporal Association" in PyTorch.

Related tags

Overview

openpifpaf

Guide

Examples

Commercial License

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Comments

when i try to run v0.14.0 from source code, it raise ImportError.

Openpifpaf MPII PlugIn

Releases(v0.14.0)

v0.14.0(Feb 14, 2022)

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