v0.3.0

Fixed bug introduced by adding quality in Grasp definition
Configurable IoU threshold
Configurable network input size
Added trained models for Jacquard dataset

v0.2.2

Bugfix in ResidualBlock
Updated default params

v0.2.1

Refactored models to reduce duplicate code
Added trained models

v0.2.0

Here are key updates in this release:
Configurable GR-ConvNets
Configurable IOU threshold in evaluation
Updated train/val split method to RandomSampler based method
Support for configurable optimizer
Updated logging to single directory
Save training logs and args
Updated evaluate.py to support multiple networks

v0.1.0

Implementation of the Generative Residual Convolutional Neural Network (GR-ConvNet) from the paper:
Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network

Supports:
Model Training
Model Evaluation
Cornell and Jacquard Datasets
Calibration Task
Grasp Generator Task