Making GLAMR actually work and solving all errors!

[take2rohit]

Thanks for such an awesome work. There were errors in the code and dependencies related to Hybrik and GLAMR. There were also missing files. I have tried to resolve all the problems and tried to document all the known errors here. Hope it helps.

The below steps works on Nvidia RTX 2080Ti, Driver Version: 530.30.02, CentOS Linux 7 (Core)

Complete conda and pip dependency can be found at environment.yml

Installing Hybrik environment

conda create -n hybrik python=3.9
conda activate hybrik
conda install pytorch=1.13.0 torchvision pytorch-cuda=11.6 -c pytorch -c nvidia
conda install -c fvcore -c iopath -c conda-forge fvcore iopath
conda install -c bottler nvidiacub
# Anaconda Cloud
conda install pytorch3d -c pytorch3d 

Errors related to opendr

You are likely to encounter missing _constants.py error. You can resolve this here.

• Clone the repo https://github.com/mattloper/opendr.git, and checkout to v0.78
• Download the OSMesa.Linux.x86_64.zip from link http://files.is.tue.mpg.de/mloper/opendr/osmesa/OSMesa.Linux.x86_64.zip and put this file in opendr/contexts directory.
• Modify the line which import _constants.py to absolute path (from opendr.contexts._constants import *) in opendr/contexts/ctx_base.pyx
• Finally run python setup.py build and python setup.py install

Missing downloads

• Downloading pretrained_w_cam.pth: https://drive.google.com/uc?id=16Y_MGUynFeEzV8GVtKTE5AtkHSi3xsF9 pre trained Hybrik weights
• Run the below code to download the remaining models

set -e
unzip spec-github-data.zip
mkdir data/dataset_folders
rm spec-github-data.zip
mkdir -p $HOME/.torch/models/
mv data/yolov3.weights $HOME/.torch/models/

Credits

• How are the predicted 54 joint points converted into the pose parameters required for SMPL? #34 (comment)
• Installation: Environment Setup | File/ Directory Structure Jeff-sjtu/HybrIK#186
• Quick Demo Problem about opendr microsoft/MeshTransformer#35 (comment)

[Khrylx]

Thank you!!

[IsshikiHugh]

Thank you for you PR and it does save me a lot of time!
However, I think modification here may not be suitable.
In the issue you mentioned, the answerer said that "This probably happens because you use the hrnet version of HybrIK which produces 3x3 rotation matrices, not quaternions". And in my case, I do receive quaternions as the output, which means modification here actually make my code fail.