Replicating Results¶
Numerous publications in the larger Dex-Net project utilize GQ-CNNs, particularly Dex-Net 2.0, Dex-Net 2.1, Dex-Net 3.0, Dex-Net 4.0, and FC-GQ-CNN. One of the goals of the gqcnn library is to provide the necessary code and instructions for replicating the results of these papers. Thus, we have provided a number of replication scripts under the scripts/ directory.
There are two ways to replicate results:
Use a pre-trained model: Download a pre-trained GQ-CNN model and run an example policy.
Train from scratch: Download the raw dataset, train a GQ-CNN model, and run an example policy using the model you just trained.
We highly encourage method 1. Note that method 2 is computationally expensive as training takes roughly 24 hours on a Nvidia Titan Xp GPU. Furthermore, the raw datasets are fairly large in size.
- Please keep in mind that GQ-CNN models are sensitive to the following parameters used during dataset generation:
The robot gripper
The depth camera
The distance between the camera and workspace.
As a result, we cannot guarantee performance of our pre-trained models on other physical setups.
For more information about the pre-trained models and sample inputs for the example policy, see Pre-trained Models and Sample Inputs.
Using a Pre-trained Model¶
First download the pre-trained models.
$ ./scripts/downloads/models/download_models.sh
Dex-Net 2.0¶
Evaluate the pre-trained GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_2.0_examples.sh
Dex-Net 2.1¶
Evaluate the pre-trained GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_2.1_examples.sh
Dex-Net 3.0¶
Evaluate the pre-trained GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_3.0_examples.sh
Dex-Net 4.0¶
To evaluate the pre-trained parallel jaw GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_4.0_pj_examples.sh
To evaluate the pre-trained suction GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_4.0_suction_examples.sh
FC-GQ-CNN¶
To evaluate the pre-trained parallel jaw FC-GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_4.0_fc_pj_examples.sh
To evaluate the pre-trained suction FC-GQ-CNN model.
$ ./scripts/policies/run_all_dex-net_4.0_fc_suction_examples.sh
Training from Scratch¶
Dex-Net 2.0¶
First download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_2.0.sh
Then train a GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_2.0.sh
Finally, evaluate the trained GQ-CNN.
$ ./scripts/policies/run_all_dex-net_2.0_examples.sh
Dex-Net 2.1¶
First download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_2.1.sh
Then train a GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_2.1.sh
Finally, evaluate the trained GQ-CNN.
$ ./scripts/policies/run_all_dex-net_2.1_examples.sh
Dex-Net 3.0¶
First download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_3.0.sh
Then train a GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_3.0.sh
Finally, evaluate the trained GQ-CNN.
$ ./scripts/policies/run_all_dex-net_3.0_examples.sh
Dex-Net 4.0¶
To replicate the Dex-Net 4.0 parallel jaw results, first download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_4.0_pj.sh
Then train a GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_4.0_pj.sh
Finally, evaluate the trained GQ-CNN.
$ ./scripts/policies/run_all_dex-net_4.0_pj_examples.sh
To replicate the Dex-Net 4.0 suction results, first download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_4.0_suction.sh
Then train a GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_4.0_suction.sh
Finally, evaluate the trained GQ-CNN.
$ ./scripts/policies/run_all_dex-net_4.0_suction_examples.sh
FC-GQ-CNN¶
To replicate the FC-GQ-CNN parallel jaw results, first download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_4.0_fc_pj.sh
Then train a FC-GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_4.0_fc_pj.sh
Finally, evaluate the trained FC-GQ-CNN.
$ ./scripts/policies/run_all_dex-net_4.0_fc_pj_examples.sh
To replicate the FC-GQ-CNN suction results, first download the appropriate dataset.
$ ./scripts/downloads/datasets/download_dex-net_4.0_fc_suction.sh
Then train a FC-GQ-CNN from scratch.
$ ./scripts/training/train_dex-net_4.0_fc_suction.sh
Finally, evaluate the trained FC-GQ-CNN.
$ ./scripts/policies/run_all_dex-net_4.0_fc_suction_examples.sh