8000 GitHub - bllxk/freemocap: Free like Freedom

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Name		Name	Last commit message	Last commit date
Latest commit History 180 Commits
.github		.github
docs		docs
freemocap-0.0.17/freemocap		freemocap-0.0.17/freemocap
freemocap		freemocap
freemocap_blender_addon		freemocap_blender_addon
.codecov.yml		.codecov.yml
.coveragerc		.coveragerc
.flake8		.flake8
.gitattributes		.gitattributes
.gitignore		.gitignore
.travis.yml		.travis.yml
2021-06-12_FreeMoCap_Clips_16MB.mp4		2021-06-12_FreeMoCap_Clips_16MB.mp4
AUTHORS.rst		AUTHORS.rst
CONTRIBUTING.rst		CONTRIBUTING.rst
FreeMoCap_SampleVideo.mp4		FreeMoCap_SampleVideo.mp4
LICENSE		LICENSE
MANIFEST.in		MANIFEST.in
README.md		README.md
README.rst		README.rst
charuco_board_image.png		charuco_board_image.png
charuco_board_image_highRes.png		charuco_board_image_highRes.png
freemocap_runme_script.py		freemocap_runme_script.py
freemocap_test.py		freemocap_test.py
github_deploy_key_jonmatthis_freemocap.enc		github_deploy_key_jonmatthis_freemocap.enc
out.mp4		out.mp4
parameters.yaml		parameters.yaml
requirements-dev.txt		requirements-dev.txt
requirements.txt		requirements.txt
runme_FreeMoCap.py		runme_FreeMoCap.py
setup.cfg		setup.cfg
setup.py		setup.py
versioneer.py		versioneer.py

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用两个摄像头实时分析人的骨骼动作

This is all very much a work in progress! More to come!

(FYI - This still isn't really in a state that's usable for outside users yet 😅)

( We're working on it though! Stay tuned!)

< 769A div class="markdown-heading" dir="auto">

Installation

Open an Anaconda Prompt (in Windows, or any terminal on Mac/Linux) and enter the following comands

conda create -n freemocap-env python=3.7

conda activate freemocap-env

pip install freemocap -v

ipython

import freemocap as fmc
fmc.RunMe() #this is where the magic happens. Also, as of 2021-07-08, is likely going to be pretty crashy/buggy

2021-06-12_FreeMoCap_Clips_16MB.mp4

Prerequisites -

Install Anaconda
- https://www.anaconda.com/products/individual#Downloads
Install CUDA
- https://developer.nvidia.com/cuda-downloads
Install OpenPose (Windows Portable Demo)
- https://github.com/CMU-Perceptual-Computing-Lab/openpose/releases/tag/v1.6.0
  - This can be complicated, so I'll need to add more instructions here!
Install ffmpeg (to save the final animation)
- https://www.wikihow.com/Install-FFmpeg-on-Windows
Two or more USB webcams attached to viable USB ports
- (USB hubs typically don't work)

Each recording must (for now) start with an unobstructed view of a Charuco board generated with python commands (or equivalent):

 import cv2
 
 aruco_dict = cv2.aruco.Dictionary_get(cv2.aruco.DICT_4X4_250) #note `cv2.aruco` can be installed via `pip install opencv-contrib-python`
 
 board = cv2.aruco.CharucoBoard_create(7, 5, 1, .8, aruco_dict)
 
 charuco_board_image = board.draw((2000,2000)) #`2000` is the resolution of the resulting image. Increase this number if printing a large board (bigger is better! Esp for large spaces!
 
 cv2.imwrite('charuco_board_image.png',charuco_board_image)

Follow the GitHub Repository and/or Join the Discord (https://discord.gg/HX7MTprYsK) for updates!