Module Pool¶

DeepClaw maintains a module pool of algorithms and end-to-end robot learning models by integrating some state-of-the-art research results in computer vision and robotics. The codes are placed under deepclaw/modules/.

Computation on server¶

As the running environment for each method is different, DeepClaw adopts concepts from cloud robotics. We put the running environments for end-to-end methods which requires heavy computations in a docker container on the server, and deploy the robot control and basic computations on a user computer.

Currently we have two servers: Goldenboy and Serbreeze. Currently they are running Ubuntu16.04 and cuda9.0. We plan to upgrade them to Ubuntu18.04 and cuda10 soon.

Each user is assigned to have one GPU card by setting environment varible CUDA_VISIBLE_DEVICES. Please don't change it by yourself. If you need more computation resources, please contact us.

	Goldenby	Serbreeze
Memory	251.8G	125.8 GiB
Processor	Intel® Xeon(R) CPU E5-2698 v4 @ 2.20GHz × 40	Intel® Xeon(R) CPU E5-2650 v4 @ 2.20GHz × 48
GPU	Tesla V100 32G x4	GeForce GTX 1080Ti 12G x4
Storage	7.6TB SSD	240G SSD (/home), 960GB SSD+8TB HD (/media/amax/)
Users	Standard: user-1, user-2, user-3	Standard: student1, student2, student3
IP	10.20.123.35	10.20.73.134

List of modules¶

Segmentation¶

Method	Object classes	weights
Contour detector	NA	NA

Recognition¶

Object Detection¶

Method	Object classes	weights
Efficientdet	204 waste classes	link extract code: frra