Libraries, tools and tasks created and used at DeepMind Robotics.

Related tags

Deep Learningrobotics
Overview

DeepMind Robotics

Libraries, tools and tasks created and used at DeepMind Robotics.

Package overview

Package Summary
Transformations Rigid body transformations
Geometry Scene and Robot geometry primitives
Vision Visual blob detection and tracking
AgentFlow Reinforcement Learning agent composition library
Manipulation "RGB" object meshes for manipulation tasks
MoMa Manipulation environment definition library, for simulated and real robots
Controllers QP-optimization based cartesian controller
Controller Bindings Python bindings for the controller
Least Squares QP QP task definition and solver

Installation

These libraries are distributed on PyPI, the packages are:

  • dm_robotics-transformations
  • dm_robotics-geometry
  • dm_robotics-vision
  • dm_robotics-agentflow
  • dm_robotics-manipulation
  • dm_robotics-moma
  • dm_robotics-controllers

Dependencies

MoMa, Manipulation and Controllers depend on MuJoCo, the other packages do not. See the individual packages for more information on their dependencies.

Building

To build and test the libraries, run build.sh. This script assumes:

  • MuJoCo is installed and licensed.
  • dm_control is installed.
  • cmake version >= 3.20.2 is installed.
  • Python 3.6 ,3.7 or 3.8 and system headers are installed.
  • GCC version 9 or later is installed.
  • numpy is installed.

The Python libraries are tested with tox, the C++ code is built and tested with cmake.

Tox's distshare mechanism is used to share the built source distribution packages between the packages.

Owner
DeepMind
DeepMind
Complete-IoU (CIoU) Loss and Cluster-NMS for Object Detection and Instance Segmentation (YOLACT)

Complete-IoU Loss and Cluster-NMS for Improving Object Detection and Instance Segmentation. Our paper is accepted by IEEE Transactions on Cybernetics

290 Dec 25, 2022
This is a deep learning-based method to segment deep brain structures and a brain mask from T1 weighted MRI.

DBSegment This tool generates 30 deep brain structures segmentation, as well as a brain mask from T1-Weighted MRI. The whole procedure should take ~1

Luxembourg Neuroimaging (Platform OpNeuroImg) 2 Oct 25, 2022
The dynamics of representation learning in shallow, non-linear autoencoders

The dynamics of representation learning in shallow, non-linear autoencoders The package is written in python and uses the pytorch implementation to ML

Maria Refinetti 4 Jun 08, 2022
Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow

Mask R-CNN for Object Detection and Segmentation This is an implementation of Mask R-CNN on Python 3, Keras, and TensorFlow. The model generates bound

Matterport, Inc 22.5k Jan 04, 2023
Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face Manipulation" published in CVPR 2020.

FFD Source Code Provided is code that demonstrates the training and evaluation of the work presented in the paper: "On the Detection of Digital Face M

88 Nov 22, 2022
Official PyTorch implementation of GDWCT (CVPR 2019, oral)

This repository provides the official code of GDWCT, and it is written in PyTorch. Paper Image-to-Image Translation via Group-wise Deep Whitening-and-

WonwoongCho 135 Dec 02, 2022
SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches

SketchEdit: Mask-Free Local Image Manipulation with Partial Sketches [Paper]  [Project Page]  [Interactive Demo]  [Supplementary Material]        Usag

215 Dec 25, 2022
A Python package for generating concise, high-quality summaries of a probability distribution

GoodPoints A Python package for generating concise, high-quality summaries of a probability distribution GoodPoints is a collection of tools for compr

Microsoft 28 Oct 10, 2022
The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

The official implementation of NeurIPS 2021 paper: Finding Optimal Tangent Points for Reducing Distortions of Hard-label Attacks

machen 11 Nov 27, 2022
Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Retrieval.

Targeted Trojan-Horse Attacks on Language-based Image Retrieval Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Re

fine 7 Aug 23, 2022
SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks (Scientific Reports)

SkipGNN: Predicting Molecular Interactions with Skip-Graph Networks Molecular interaction networks are powerful resources for the discovery. While dee

Kexin Huang 49 Oct 15, 2022
A minimalist tool to display a network graph.

A tool to get a minimalist view of any architecture This tool has only be tested with the models included in this repo. Therefore, I can't guarantee t

Thibault Castells 1 Feb 11, 2022
Convert scikit-learn models to PyTorch modules

sk2torch sk2torch converts scikit-learn models into PyTorch modules that can be tuned with backpropagation and even compiled as TorchScript. Problems

Alex Nichol 101 Dec 16, 2022
eXPeditious Data Transfer

xpdt: eXPeditious Data Transfer About xpdt is (yet another) language for defining data-types and generating code for serializing and deserializing the

Gianni Tedesco 3 Jan 06, 2022
[CVPRW 21] "BNN - BN = ? Training Binary Neural Networks without Batch Normalization", Tianlong Chen, Zhenyu Zhang, Xu Ouyang, Zechun Liu, Zhiqiang Shen, Zhangyang Wang

BNN - BN = ? Training Binary Neural Networks without Batch Normalization Codes for this paper BNN - BN = ? Training Binary Neural Networks without Bat

VITA 40 Dec 30, 2022
Shape-Adaptive Selection and Measurement for Oriented Object Detection

Source Code of AAAI22-2171 Introduction The source code includes training and inference procedures for the proposed method of the paper submitted to t

houliping 24 Nov 29, 2022
[CVPR 2021] Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach

Rethinking Text Segmentation: A Novel Dataset and A Text-Specific Refinement Approach This is the repo to host the dataset TextSeg and code for TexRNe

SHI Lab 174 Dec 19, 2022
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation

Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target i

NanYoMy 13 Oct 09, 2022
HashNeRF-pytorch - Pure PyTorch Implementation of NVIDIA paper on Instant Training of Neural Graphics primitives

HashNeRF-pytorch Instant-NGP recently introduced a Multi-resolution Hash Encodin

Yash Sanjay Bhalgat 616 Jan 06, 2023
Multi agent DDPG algorithm written in Python + Pytorch

Multi agent DDPG algorithm written in Python + Pytorch. It also includes a Jupyter notebook, Tennis.ipynb, as a showcase.

Rogier Wachters 2 Feb 26, 2022