Python interface for the DIGIT tactile sensor

Overview

DIGIT-INTERFACE

License: CC BY-NC 4.0 PyPI DIGIT-logo

Python interface for the DIGIT tactile sensor.

For updates and discussions please join the #DIGIT channel at the www.touch-sensing.org community.

Installation

The preferred way of installation is through PyPi:

pip install digit-interface

Alternatively, you can manually clone the repository and install the package using:

git clone https://github.com/facebookresearch/digit-interface.git 
cd digit-interface
pip install -r requirements.txt
python setup.py install

If you cannot access the device by serial number on your system follow adding DIGIT udev Rule

Usage

The default connection method to the DIGIT tactile sensor is through the unique device serial number. The serial number is found on the back of each DIGIT. See List all connected DIGIT's to find device serial numbers which are connected to the host.

Once you have the device serial number, reading data from the sensor should be as easy as

from digit_interface.digit import Digit
 
d = Digit("D12345") # Unique serial number
d.connect()
d.show_view()
d.disconnect()

Upon connection each DIGIT device initializes with a default stream resolution of VGA: 640x480 at 30fps

Further Usage

List all connected DIGIT's:

To list all connected DIGIT's and display sensor information:

from digit_interface.digit_handler import DigitHandler

digits = DigitHandler.list_digits()
Obtain a single frame:
from digit_interface.digit import Digit

d = Digit("D12345") # Unique serial number
d.connect()
frame = d.get_frame()
List supported stream formats:

Additional streams are supported, these streams vary in resolution and frames per second.

To list the available stream formats:

from digit_interface.digit_handler import DigitHandler

print("Supported streams: \n {}".format(DigitHandler.STREAMS))
Change resolution:
d.set_resolution(DigitHandler.STREAMS["QVGA"])
Change FPS,

Based on supported fps for each respective resolution. All streams support pre-defined resolutions which can be found in DigitHandler.STREAMS

d.set_fps(DigitHandler.STREAMS["QVGA"]["fps"]["15fps"])

Adding DIGIT udev Rule

Add your user to the plugdev group,

adduser username plugdev

Copy udev rule,

sudo cp ./udev/50-DIGIT.rules /lib/udev/rules.d/

Reload rules,

sudo udevadm control --reload
sudo udevadm trigger

Replug the DIGIT device into host.

License

This code is licensed under CC-by-NC, as found in the LICENSE file.

Citing

If you use this project in your research, please cite this paper:

@Article{Lambeta2020DIGIT,
  author  = {Lambeta, Mike and Chou, Po-Wei and Tian, Stephen and Yang, Brian and Maloon, Benjamin and Victoria Rose Most and Stroud, Dave and Santos, Raymond and Byagowi, Ahmad and Kammerer, Gregg and Jayaraman, Dinesh and Calandra, Roberto},
  title   = {{DIGIT}: A Novel Design for a Low-Cost Compact High-Resolution Tactile Sensor with Application to In-Hand Manipulation},
  journal = {IEEE Robotics and Automation Letters (RA-L)},
  year    = {2020},
  volume  = {5},
  number  = {3},
  pages   = {3838--3845},
  doi     = {10.1109/LRA.2020.2977257},
}
Owner
Facebook Research
Facebook Research
Official Pytorch Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images.

IAug_CDNet Official Implementation of Adversarial Instance Augmentation for Building Change Detection in Remote Sensing Images. Overview We propose a

53 Dec 02, 2022
Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks

Implementation for On Provable Benefits of Depth in Training Graph Convolutional Networks Setup This implementation is based on PyTorch = 1.0.0. Smal

Weilin Cong 8 Oct 28, 2022
Code for CVPR2019 paper《Unequal Training for Deep Face Recognition with Long Tailed Noisy Data》

Unequal-Training-for-Deep-Face-Recognition-with-Long-Tailed-Noisy-Data. This is the code of CVPR 2019 paper《Unequal Training for Deep Face Recognition

Zhong Yaoyao 68 Jan 07, 2023
It's A ML based Web Site build with python and Django to find the breed of the dog

ML-Based-Dog-Breed-Identifier This is a Django Based Web Site To Identify the Breed of which your DOG belogs All You Need To Do is to Follow These Ste

Sanskar Dwivedi 2 Oct 12, 2022
Example Of Fine-Tuning BERT For Named-Entity Recognition Task And Preparing For Cloud Deployment Using Flask, React, And Docker

Example Of Fine-Tuning BERT For Named-Entity Recognition Task And Preparing For Cloud Deployment Using Flask, React, And Docker This repository contai

Nikita 12 Dec 14, 2022
Official PyTorch Implementation of Learning Architectures for Binary Networks

Learning Architectures for Binary Networks An Pytorch Implementation of the paper Learning Architectures for Binary Networks (BNAS) (ECCV 2020) If you

Computer Vision Lab. @ GIST 25 Jun 09, 2022
ADSPM: Attribute-Driven Spontaneous Motion in Unpaired Image Translation

ADSPM: Attribute-Driven Spontaneous Motion in Unpaired Image Translation This repository provides a PyTorch implementation of ADSPM. Requirements Pyth

24 Jul 24, 2022
Unified tracking framework with a single appearance model

Paper: Do different tracking tasks require different appearance model? [ArXiv] (comming soon) [Project Page] (comming soon) UniTrack is a simple and U

ZhongdaoWang 300 Dec 24, 2022
Physics-informed Neural Operator for Learning Partial Differential Equation

PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol

107 Jan 02, 2023
Chinese Advertisement Board Identification(Pytorch)

Chinese-Advertisement-Board-Identification. We use YoloV5 to extract the ROI of the location of the chinese word. Next, we sort the bounding box and recognize every chinese words which we extracted.

Li-Wei Hsiao 12 Jul 21, 2022
Implementation for Shape from Polarization for Complex Scenes in the Wild

sfp-wild Implementation for Shape from Polarization for Complex Scenes in the Wild project website | paper Code and dataset will be released soon. Int

Chenyang LEI 41 Dec 23, 2022
Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction

Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction Requirements The code has been tested running under Python 3.7.4, with the foll

zshicode 84 Jan 01, 2023
A high-level Python library for Quantum Natural Language Processing

lambeq About lambeq is a toolkit for quantum natural language processing (QNLP). Documentation: https://cqcl.github.io/lambeq/ User support: lambeq-su

Cambridge Quantum 315 Jan 01, 2023
rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.

Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.

Google Research 529 Jan 01, 2023
DA2Lite is an automated model compression toolkit for PyTorch.

DA2Lite (Deep Architecture to Lite) is a toolkit to compress and accelerate deep network models. ⭐ Star us on GitHub — it helps!! Frameworks & Librari

Sinhan Kang 7 Mar 22, 2022
Experimental solutions to selected exercises from the book [Advances in Financial Machine Learning by Marcos Lopez De Prado]

Advances in Financial Machine Learning Exercises Experimental solutions to selected exercises from the book Advances in Financial Machine Learning by

Brian 1.4k Jan 04, 2023
PyTorch code of paper "LiVLR: A Lightweight Visual-Linguistic Reasoning Framework for Video Question Answering"

LiVLR-VideoQA We propose a Lightweight Visual-Linguistic Reasoning framework (LiVLR) for VideoQA. The overview of LiVLR: Evaluation on MSRVTT-QA Datas

JJ Jiang 7 Dec 30, 2022
Collection of NLP model explanations and accompanying analysis tools

Thermostat is a large collection of NLP model explanations and accompanying analysis tools. Combines explainability methods from the captum library wi

126 Nov 22, 2022
Deep Unsupervised 3D SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment.

(ACMMM 2021 Oral) SfM Face Reconstruction Based on Massive Landmark Bundle Adjustment This repository shows two tasks: Face landmark detection and Fac

BoomStar 51 Dec 13, 2022
Data-depth-inference - Data depth inference with python

Welcome! This readme will guide you through the use of the code in this reposito

Marco 3 Feb 08, 2022