red0orange/pytorch_contactnet

PyTorch implementation of Contact-GraspNet

Pytorch Contact-GraspNet

Pytorch implementation of Contact-GraspNet. Original Tensorflow implementation can be found at: https://github.com/NVlabs/contact_graspnet

DISCLAIMER: This is research code I'm using as a stepping stone toward a different project - your mileage may vary. I'll update this repo periodically but am not actively maintaining it.

General notes

The train file is a little broken and will be updated soon along with tools to evaluate the model in Pybullet and on a real world setup. Stay tuned for a cleaner datloader + instructions for interfacing with ACRONYM as well.

Right now, a current checkpoint of the weights that I've been using is in /checkpoints/current.pth and can be loaded and used as seen in the demo file.

Demo file

To see a demo of the predictions, first download the requirements: pip3 install -r requirements.txt We're doing our visualizations in MeshCat. In a separate tab, start a meshcat server with meshcat-server

From here you can run python3 eval.py

To visualize different thresholds, use the --threshold argument such as --threshold=0.8

To visualize different cluttered scenes (rendered in pyrender from ACRONYM), use the argument --scene and manually feed in a file name such as --scene=002330.npz. Sorry that this is so inconvenient right now. Your possible files are:

• 002330.npz
• 004086.npz
• 005274.npz

Happy grasping!