PyTorch-Simple-AffordanceNet

The code is developed to simply and implement AffordanceNet in PyTorch (AffordanceNet was developed in Caffe). Here is the original paper for AffordanceNet.

I based this work on TorchVision and PyTorch-Simple-MaskRCNN.

I used pytorch-simple-affnet with the following repos:

1. LabelFusion for generating real images.
2. NDDS for generating synthetic images.
3. arl-affpose-dataset-utils a custom dataset that I generated.
4. densefusion for predicting an object 6-DoF pose.
5. arl-affpose-ros-node: for deploying our network for 6-DoF pose estimation with our ZED camera.
6. barrett-wam-arm for robotic grasping experiments. Specifically barrett_tf_publisher and barrett_trac_ik.

In the sample below we see the differences between traditional Object Instance Segmentation (left) and Object-based Affordance Detection (right).