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Web-browser demo for openpifpaf.

Project description

openpifpafwebdemo

Build Status

Links: main repository and CVPR2019 paper.
Live demo: https://vitademo.epfl.ch
Serverless live demo: https://vita-epfl.github.io/openpifpafwebdemo/

Use Locally

Run the full pipeline (neural network and decoder) in Python and visualize the output in the browser:

pip3 install openpifpafwebdemo
python3 -m openpifpafwebdemo.server

Open a web browser at http://localhost:5000 to view the web interface.

Troubleshooting: Make sure you are using Python3 and have the latest pip and setuptools with pip install --upgrade pip setuptools. Do not clone this repository. Make sure there is no folder named openpifpafwebdemo in your current directory.

Example:

example image

API

Example using cURL:

curl -X POST -H "Content-Type: application/json" --data @test_image.json http://localhost:5000/process

which produces:

[{"coordinates": [[0.588631883263588, 0.41628291457891464, 3.5567557387194797], [0.621234196703881, 0.36160339042544365, 3.524825929280572], [0.546875, 0.375, 3.744302039019678], [0.6724068783223629, 0.44710323959589005, 3.459401266884038], [0.494683139026165, 0.4611567258834839, 3.5954212359489217], [0.78733691573143, 0.8311769068241119, 2.1321910543190827], [0.3859005756676197, 0.8252473473548889, 2.158424186304439], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0], [0.0, 0.0, 0.0]], "score": 0.26909651332876167}]

Keep-alive connection test:

curl -v -X POST -H "Content-Type: application/json" --data @test_image.json http://localhost:5000/process --next -X POST -H "Content-Type: application/json" --data @test_image.json http://localhost:5000/process 2>&1 | grep '#0'
* Connected to localhost (127.0.0.1) port 5000 (#0)
* Connection #0 to host localhost left intact
* Re-using existing connection! (#0) with host localhost
* Connected to localhost (127.0.0.1) port 5000 (#0)
* Connection #0 to host localhost left intact

Dev

To install from source and set up for development use pip install --editable ".[test]", install the frontend dependencies with npm install and then create the frontend JavaScript code with npm run build. For continuous rebuilds of the js package, use npm run watch.

Run the server process with --debug to get salted version numbers to break the browser cache for static assets and autoreload when source files change.

Citation

@InProceedings{kreiss2019pifpaf,
  author = {Kreiss, Sven and Bertoni, Lorenzo and Alahi, Alexandre},
  title = {PifPaf: Composite Fields for Human Pose Estimation},
  booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  month = {June},
  year = {2019}
}

Project details


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