A note taker for NVDA. Allows the user to create, edit, view, manage and export notes to different formats.

Overview

Quick Notetaker add-on for NVDA

The Quick Notetaker add-on is a wonderful tool which allows writing notes quickly and easily anytime and from any app the user is using. Whether the user is watching a video for example, or participating in a meeting on Zoom, teams or Google meet, they can easily and smoothly open the notetaker and take a note. In order to create a quick note, NVDA + Alt + n key combination can be used, a floating window appears at the top left corner of the screen, so the note can be typed there.

Every note that is being Created can optionally get the active window title, and as such, the note content can get the context in which this note was created by having the note title as the active window title the user was using. This behavior can be changed from the add-on settings, where the user can decide whether the active window title is captured when creating a new note.

The Notetaker dialog

  • The note edit area: When opening the Notetaker interface the focus will be in this edit area. Writing with Markdown (a markup language to easily produce HTML content) is supported also. For more info on Markdown visit the Markdown guide page.

  • Preview note: to view the note in an HTML window.

  • Copy: to copy the note as is to the clipboard.

  • Copy HTML code: to copy the HTML code representing the note. A useful feature for those who write in Markdown.

  • A checkbox to allow saving the note as Microsoft Word also, or updating the corresponding one if it exists.

  • A save and close button.

  • A discard button to discard changes when desired. When unsaved changes exist, a warning message is displayed to the user asking if they are sure they want to exit and discard their changes.

The Notes Manager interface

Opening and closing this interface

  • NVDA + Alt + v will launch the Notes Manager interface.

  • Using either the Escape key or the close button found at the bottom of this window will close this interface.

The notes list

The notes are organized in a tabular list which includes:

  1. The note title: If the note hasn’t got the active window title, the first line of the note will be the note title displayed in this list.

  2. Last edited time stamp.

  3. A preview text of the note content.

The options available in Notes Manager interface

  • View note: to view the note in an HTML window.

  • Edit note: opens the note to be edited using Notetaker interface.

  • Copy note: copies the note content as is to the clipboard.

  • Create a Microsoft Word document: Creates a Microsoft Word document representing this note in case it has no such document.

  • Open in Microsoft Word: opens the Microsoft Word document attached to this note in case it has a one.

  • Copy HTML code: copies the HTML code representing this note. A useful feature for those who write in Markdown.

  • Delete note: displays a warning before performing the note deletion.

  • New note: the Notetaker interface can be reached from this interface to create a new note.

  • Open settings: opening the add-on settings is also possible from here.

  • Close: to close the window.

The add-on settings

The add-on settings are a part of NVDA’s settings interface. To reach those settings, the user needs to open the NVDA menu using NVDA key + n, choose preferences > settings, and then arrow down until reaching Quick Notetaker category.

Using the settings interface the user can:

  • Default documents directory: to choose the default directory where Quick Notetaker documents will be saved. The user can press the “Browse” button to change the path of this directory.

  • Ask me each time where to save the note's corresponding Microsoft Word document: a checkbox (not checked by default) – to show the dialog for choosing the location where the document will be saved on each save or update operation for the note’s Microsoft Word document if such a one exists.

  • Open the note's corresponding Microsoft Word document after saving or updating: a checkbox (not checked by default) – to allow the user to choose whether the Microsoft Word document will be opened after a save or update operation in case the note has such document.

  • Capture the active window title when creating a new note: a checkbox (checked by default) – to allow the note to get the active window title the user was using when they created the note. This title will be also the title of the Microsoft Word document for the note in case it has a one.

  • Remember the note taker window size and position: a checkbox (not checked by default) – to tell the add-on to remember the size and the position of the Notetaker dialog when creating or editing a note. As such, when the user opens the dialog next time, the position and the size will be the same as the last time the dialog was used. The default position of this dialog is at the top left corner of the screen.

  • Auto align text when editing notes (relevant for RTL languages): a checkbox (checked by default) – to control whether the text when creating or editing a note should be auto aligned according to the language used. This is mostly relevant for right to left languages. For example, if the language used is Arabic or Hebrew, then the text will be right aligned when this option is chosen, if the language is English or French, then the text will be left aligned.

Keyboard shortcuts

  • NVDA + Alt + n: to open the Notetaker interface.

  • NVDA + Alt + v: to open the Notes Manager interface.

Keyboard shortcuts in the different interfaces

Interface Command Keyboard shortcut
Notetaker Focus the note edit area Alt + n
Notetaker Align text to the right Control + r
Notetaker Align text to the left Control + l
Notetaker Preview note in an HTML window Alt + r
Notetaker Copy Alt + p
Notetaker Copy HTML code Alt + h
Notetaker Save note as a Microsoft Word document Alt + w
Notetaker Update the note corresponding Microsoft Word document Alt + w
Notetaker Save and close Alt + s
Notetaker Discard Alt + d
Notetaker Open notes Manager Alt + m
Notes Manager View note Alt + v
Notes Manager Edit note Alt + e
Notes Manager Copy note Alt + p
Notes Manager Open in Microsoft Word (if such a document exists) Alt + o
Notes Manager Create a word document for a saved note Alt + w
Notes Manager Copy HTML code Alt + h
Notes Manager Delete note Alt + d
Notes Manager New note Alt + n
Notes Manager Open settings Alt + s
Notes Manager Close the interface Alt + c
The settings interface Ask me each time where to save the note's corresponding Microsoft Word document Alt + w
The settings interface Open the note's corresponding Microsoft Word document after saving or updating Alt + o
The settings interface Capture the active window title when creating a new note Alt + c
The settings interface Remember the note taker window size and position Alt + r
The settings interface Auto align text when editing notes (relevant for RTL languages) Alt + t

Acknowledgements

  • The add-on comes bundled with Pandoc, a wonderful tool which allows converting documents between different formats. Without this tool the add-on won’t be able to offer the capabilities it offers. For more info on Pandoc visit the Pandoc homepage.

  • The add-on also relies on a Python Markdown package called markdown2. For more info on this package visit the package GitHub page.

  • A great thanks to NV Access, add-on authors, and contributors! Several parts of the add-on were inspired by your magnificent work and effort, so please keep up this brilliant ecosystem and the cooperation.

You might also like...
Manage the availability of workspaces within Frappe/ ERPNext (sidebar) based on user-roles

Workspace Permissions Manage the availability of workspaces within Frappe/ ERPNext (sidebar) based on user-roles. Features Configure foreach workspace

Transfer SemanticKITTI labeles into other dataset/sensor formats.
Transfer SemanticKITTI labeles into other dataset/sensor formats.

LiDAR-Transfer Transfer SemanticKITTI labeles into other dataset/sensor formats. Content Convert datasets (NUSCENES, FORD, NCLT) to KITTI format Minim

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.
Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy.

Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy. Now with tensorflow 1.0 support. Evaluation usa

Annotated notes and summaries of the TensorFlow white paper, along with SVG figures and links to documentation

TensorFlow White Paper Notes Features Notes broken down section by section, as well as subsection by subsection Relevant links to documentation, resou

Python/Rust implementations and notes from Proofs Arguments and Zero Knowledge

What is this? This is where I'll be collecting resources related to the Study Group on Dr. Justin Thaler's Proofs Arguments And Zero Knowledge Book. T

Export CenterPoint PonintPillars ONNX Model For TensorRT
Export CenterPoint PonintPillars ONNX Model For TensorRT

CenterPoint-PonintPillars Pytroch model convert to ONNX and TensorRT Welcome to CenterPoint! This project is fork from tianweiy/CenterPoint. I impleme

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch
NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch

NuPIC Studio is an all­-in-­one tool that allows users create a HTM neural network from scratch, train it, collect statistics, and share it among the members of the community. It is not just a visualization tool but an HTM builder, debugger and laboratory for experiments. It is ideal for newbies with little intimacy with NuPIC code as well as experts that wish a better productivity. Among its features and advantages:

All-in-one Docker container that allows a user to explore Nautobot in a lab environment.
All-in-one Docker container that allows a user to explore Nautobot in a lab environment.

Nautobot Lab This container is not for production use! Nautobot Lab is an all-in-one Docker container that allows a user to quickly get an instance of

This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape

Metashape-Utils This repository allows the user to automatically scale a 3D model/mesh/point cloud on Agisoft Metashape, given a set of 2D coordinates

Releases(v1.1)
  • v1.1(May 20, 2022)

    This release adds compatibility for NVDA 2022.1 and above, fixes a bug with displaying the note title in Notes manager, and adds German and Chinese translation. To elaborate on the bug with displaying the note title, the previous version included a bug where the whole text of the note was displayed to be the title of the note, which wasn't the intention of the developers. The bug is now fixed, the newly created notes will have their title as the first line of the note. For existing notes, the user can select the note from the notes list in Notes Manager, click "Edit note", and then click "Save and close". We made it possible to be able to edit the note even without needing to change the content to allow the user to overcome this bug.

    Source code(tar.gz)
    Source code(zip)
    quickNotetaker-1.1.nvda-addon(21.72 MB)
  • v1.0(Oct 2, 2021)

This is Official implementation for "Pose-guided Feature Disentangling for Occluded Person Re-Identification Based on Transformer" in AAAI2022

PFD:Pose-guided Feature Disentangling for Occluded Person Re-identification based on Transformer This repo is the official implementation of "Pose-gui

Tao Wang 93 Dec 18, 2022
PyQt6 configuration in yaml format providing the most simple script.

PyamlQt(ぴゃむるきゅーと) PyQt6 configuration in yaml format providing the most simple script. Requirements yaml PyQt6, ( PyQt5 ) Installation pip install Pya

Ar-Ray 7 Aug 15, 2022
Official PyTorch Implementation of GAN-Supervised Dense Visual Alignment

GAN-Supervised Dense Visual Alignment — Official PyTorch Implementation Paper | Project Page | Video This repo contains training, evaluation and visua

944 Jan 07, 2023
Implementation of ToeplitzLDA for spatiotemporal stationary time series data.

Code for the ToeplitzLDA classifier proposed in here. The classifier conforms sklearn and can be used as a drop-in replacement for other LDA classifiers. For in-depth usage refer to the learning from

Jan Sosulski 5 Nov 07, 2022
통일된 DataScience 폴더 구조 제공 및 가상환경 작업의 부담감 해소

Lucas coded by linux shell 목차 Mac버전 CookieCutter (autoenv) 1.How to Install autoenv 2.폴더 진입 시, activate 구현하기 3.폴더 탈출 시, deactivate 구현하기 4.Alias 설정하기 5

ello 3 Feb 21, 2022
Build and run Docker containers leveraging NVIDIA GPUs

NVIDIA Container Toolkit Introduction The NVIDIA Container Toolkit allows users to build and run GPU accelerated Docker containers. The toolkit includ

NVIDIA Corporation 15.6k Jan 01, 2023
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.

Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran

Swin Transformer 1.4k Dec 30, 2022
Message Passing on Cell Complexes

CW Networks This repository contains the code used for the papers Weisfeiler and Lehman Go Cellular: CW Networks (Under review) and Weisfeiler and Leh

Twitter Research 108 Jan 05, 2023
Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd.

Head Detector Code for the head detector (HeadHunter) proposed in our CVPR 2021 paper Tracking Pedestrian Heads in Dense Crowd. The head_detection mod

Ramana Sundararaman 76 Dec 06, 2022
The official PyTorch implementation of paper BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition

BBN: Bilateral-Branch Network with Cumulative Learning for Long-Tailed Visual Recognition Boyan Zhou, Quan Cui, Xiu-Shen Wei*, Zhao-Min Chen This repo

Megvii-Nanjing 616 Dec 21, 2022
LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation

LEDNet: A Lightweight Encoder-Decoder Network for Real-time Semantic Segmentation Table of Contents: Introduction Project Structure Installation Datas

Yu Wang 492 Dec 02, 2022
OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis

OpenABC-D: A Large-Scale Dataset For Machine Learning Guided Integrated Circuit Synthesis Overview OpenABC-D is a large-scale labeled dataset generate

NYU Machine-Learning guided Design Automation (MLDA) 31 Nov 22, 2022
Implementation of EMNLP 2017 Paper "Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog" using PyTorch and ParlAI

Language Emergence in Multi Agent Dialog Code for the Paper Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog Satwik Kottur, José M.

Karan Desai 105 Nov 25, 2022
Visualizer using audio and semantic analysis to explore BigGAN (Brock et al., 2018) latent space.

BigGAN Audio Visualizer Description This visualizer explores BigGAN (Brock et al., 2018) latent space by using pitch/tempo of an audio file to generat

Rush Kapoor 2 Nov 21, 2022
A PyTorch implementation of "Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning", IJCAI-21

MERIT A PyTorch implementation of our IJCAI-21 paper Multi-Scale Contrastive Siamese Networks for Self-Supervised Graph Representation Learning. Depen

Graph Analysis & Deep Learning Laboratory, GRAND 32 Jan 02, 2023
Hierarchical User Intent Graph Network for Multimedia Recommendation

Hierarchical User Intent Graph Network for Multimedia Recommendation This is our Pytorch implementation for the paper: Hierarchical User Intent Graph

6 Jan 05, 2023
Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training Consistency Shift (ICCV 2021)

Π-NAS This repository provides the evaluation code of our submitted paper: Pi-NAS: Improving Neural Architecture Search by Reducing Supernet Training

Jiqi Zhang 18 Aug 18, 2022
Pre-trained NFNets with 99% of the accuracy of the official paper

NFNet Pytorch Implementation This repo contains pretrained NFNet models F0-F6 with high ImageNet accuracy from the paper High-Performance Large-Scale

Benjamin Schmidt 133 Dec 09, 2022
implement of SwiftNet:Real-time Video Object Segmentation

SwiftNet The official PyTorch implementation of SwiftNet:Real-time Video Object Segmentation, which has been accepted by CVPR2021. Requirements Python

haochen wang 64 Dec 14, 2022
Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization Authors: Fan-yun Sun, Jordan Hoffm

Fan-Yun Sun 232 Dec 28, 2022