Educational API for 3D Vision using pose to control carton.

Overview

Pose2Carton

A educational project (e.g., using 3D pose to control 3D carton) for learning 3D vision (application of human mesh recovery) or imitation learning

Update Notes

2021/06/08: Update the requirement for your code submission on github

2021/05/20: Update the saving logic of mapping results(.pkl). In previous version, pkl will not be overwritten, so if you try mapping multiple times, the pkl will stay as it was in previous mapping. This problem is fixed now, pls ensure that your results/ is the latest version

2021/05/17: Add quick start instructions to help you dive into this project & Use custom obj loader instead of open3d

Requirements

  • code only tested on linux system (ubuntu 16.04)
  • open3d==0.11.0(if you want to try online models, use open3d 0.10.0 along with your own video recording tool to save visualization)
  • tqdm
  • opencv-python

pip install -r requirements.txt (anaconda recommended, python3)

Tutorials

Code structure

  • transfer.py: the main mapping file
  • vis.py: visualize the mapping sequence of the corresponding mesh
  • pose_samples: some samples of SMPL model for one frame
  • obj_seq_id: some samples of SMPL model for temporal sequence

Method

image

Project Result

image

Visulization

Run vis.py (to get more clear visualization, press ctrl + 1 / ctrl + 2 / ctrl + 3 ...)

image

LICENSE

The code is under Apache-2.0 License.

For EE228 students from SJTU

Please read course project requirements.

Owner
PhD candidate in machine learning, with emphasis on Human Reconstruction and VR.
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