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easymocap_win_install

Repository to help installing easymocp on windows

The video tutorial for installation of Easymocap on windows system. https://www.patreon.com/posts/easymocap-raw-04-50646448

The video with the calibration to use on Easymocap https://www.patreon.com/posts/easymocap-raw-04-50646809

To do the manual calibration you can use the labelme package

install it using

pip install labelme

if you are a linux user, maybe this command will be better to install labelme (thanks to HacktopS https://twitter.com/HacktopS for the tip)

sudo apt-get install labelme

Attention

There is a huge thing that the tutorial We've done is missing, to say that you should run the installation script for easymocp

https://github.com/zju3dv/EasyMocap/blob/master/doc/installation.md#3-install

that says to run this line python3 setup.py develop --user

IMPORT Information

The new version of easymocap, has the option to create the data needed to import in the addon MOCAP_IMPORT, you just have to add this command --write_smpl_full when running easymocap.

For example, it you used to run this: python apps/demo/mv1p.py 0_input/sample --out 1_output/sample/smplx2 --undis --sub_vis 1 7 13 19 --body bodyhandface --model smplx --gender male

You will have to run this: python apps/demo/mv1p.py 0_input/sample --out 1_output/sample/smplx2 --undis --sub_vis 1 7 13 19 --body bodyhandface --model smplx --gender male --write_smpl_full

And in Mocap import, you will hve to import the folder SMPL_FULL

Installing Pythorch 1.4

Steps to Install PyTorch 1.4.0

[Optional] Check if CUDA is installed

It is strongly recommended that you have CUDA 10.1 installed. Because PyTorch 1.4.0 does not support CUDA 10.2 or CUDA 11.0. Click here to install CUDA 10.1.

Once/If you have it installed, you can check its version here.

[For conda on Ubuntu/Linux and Windows 10]

Run conda install and specify PyTorch version 1.4.0

CUDA 10.2 is not officially supported, you have to install CUDA 10.1.

CUDA 10.1: conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.1 -c pytorch

CUDA 10.0: conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=10.0 -c pytorch

CUDA 9.2: conda install pytorch==1.4.0 torchvision==0.5.0 cudatoolkit=9.2 -c pytorch

CPU Only (your PyTorch code will run slower):

conda install pytorch==1.4.0 torchvision==0.5.0 cpuonly -c pytorch

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