Closed anushl9o5 closed 1 year ago
Hello anushl9o5,
The dataset preparation setup is a bit complicated. I just uploaded another directory named "MakeDataForOptimization".
The basic idea was to first get the 2D heatmap and joint depths with the Mo2Cap2 method (or xR-egopose). Then get the egocentric camera pose for each sequence with the OpenVSLAM (or any other camera pose localization method).
The camera poses and body heatmaps/depths are combined into a pkl file, and the human body poses predictions can be further optimized by "optimize_whole_sequence.py".
Do not hesitate to contact me if you have any further questions about my work.
Best,
Jian Wang
Ok sounds good! I'm setting up your repo to run on your data as a first step. I will be running on custom data shortly after that. I'll bring up any issues I face
@yt4766269 are there any scripts available to visualize the results from - https://github.com/yt4766269/GlobalEgoMocap#optimize-the-motion-sequences-in-proposed-dataset
I'm trying to retrain the VAE and I have this error FileNotFoundError: [Errno 2] No such file or directory: '/HPS/ScanNet/static00/SURREAL/smpl_data/seq_names.npy'
For the visualization, see utils/skeleton.py, joints_to_mesh function to convert joints to mesh and visualize it with open3d. For training the vae, I am not available today and I will deal with that asap.
I uploaded new versions of train_globa.sh and train_local.sh Now they should work.
Great thanks!
What is the path for this /home/jianwang/ScanNet/static00/EgocentricAMASS
?
Follow up:
I get the following error when I point it to the directory mentioned here https://github.com/yt4766269/GlobalEgoMocap#train-the-motion-vae
Error: ValueError: num_samples should be a positive integer value, but got num_samples=0
Can you show the complete call stack?
please see recent updates under:
https://github.com/yt4766269/GlobalEgoMocap/blob/main/networks/README.md#motion-vae
Hey! I'm interested in running your paper for a base lining effort.
Can you please clarify what you mean by this? https://github.com/yt4766269/GlobalEgoMocap/blob/main/README.md#prepare-the-data-for-optimization