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

Overview

NuPIC Studio Logo NuPIC Studio *nix Build Status

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:

  • Users can open, save, or change their "HTM projects" or of other developers. A typical project contains data to be trained, neural network configuration, statistics, etc, which can be shared to be analysed or integrated with other projects.
  • The HTM engine is the own original NuPIC libray (Python distribution). This means no port, no bindings, no re-implementation, etc. So any changes in the original nupic source can be immediatedly viewed. This helps users that wish test improvements like new encoders or even hierarchy, attention, and motor integration.

Screenshot

For more information, see numenta.org or the NuPIC Studio wiki.

Installation

Currently supported platforms:

  • Windows
  • Linux (32/64bit)
  • Mac OSX

Dependencies:

  • Python (2.7 or later)
  • PIP
  • NuPIC
  • NumPy
  • PyQt5

User instructions

If you want only use it, simply do this:

pip install nupic_studio

Note: Dear *nix users, if you get a "permission denied" error when using pip, you may add the --user flag to install to a location in your home directory, which should resolve any permissions issues. Doing this, you may need to add this location to your PATH and PYTHONPATH. Alternatively, you can run pip with 'sudo'.

Once it is installed, you can execute the app using:

nupic_studio

and then click on Open Project button to open any example to getting started with NuPIC.

Developer instructions

If you want develop, debug, or simply test NuPIC Studio, clone it and follow the instructions:

Using command line

This assumes the NUPIC_STUDIO environment variable is set to the directory where the NuPIC Studio source code exists.

cd $NUPIC_STUDIO
python setup.py build
python setup.py develop

Using an IDE

The following instructions will work in the most Python IDEs:

  • Open your IDE.
  • Open a project specifying the $NUPIC_STUDIO repository folder as location.
  • Click with mouse right button on setup.py file listed on project files and select Run command on pop-up menu. This will call the build process. Check output panel to see the result.
  • If the build was successful, just click on program.py and voilà!

If you don't have a favourite Python IDE, this article can help you to choose one: http://pedrokroger.net/choosing-best-python-ide/

Owner
HTM Community
Home for community-led HTM repositories.
HTM Community
[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding

[AAAI 2022] Negative Sample Matters: A Renaissance of Metric Learning for Temporal Grounding Official Pytorch implementation of Negative Sample Matter

Multimedia Computing Group, Nanjing University 69 Dec 26, 2022
Detect roadway lanes using Python OpenCV for project during the 5th semester at DHBW Stuttgart for lecture in digital image processing.

Find Line Detection (Image Processing) Identifying lanes of the road is very common task that human driver performs. It's important to keep the vehicl

LMF 4 Jun 21, 2022
DeRF: Decomposed Radiance Fields

DeRF: Decomposed Radiance Fields Daniel Rebain, Wei Jiang, Soroosh Yazdani, Ke Li, Kwang Moo Yi, Andrea Tagliasacchi Links Paper Project Page Abstract

UBC Computer Vision Group 24 Dec 02, 2022
Official PyTorch implementation of "The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person Pose Estimation" (ICCV 21).

CenterGroup This the official implementation of our ICCV 2021 paper The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person P

Dynamic Vision and Learning Group 43 Dec 25, 2022
Orthogonal Over-Parameterized Training

The inductive bias of a neural network is largely determined by the architecture and the training algorithm. To achieve good generalization, how to effectively train a neural network is of great impo

Weiyang Liu 11 Apr 18, 2022
Automatic Number Plate Recognition using Contours and Convolution Neural Networks (CNN)

Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in

Adithya M 2 Jun 28, 2022
A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows"

OutliersSlidingWindows A Java implementation of the experiments for the paper "k-Center Clustering with Outliers in Sliding Windows" Dataset generatio

PaoloPellizzoni 0 Jan 05, 2022
This is the official repository for our paper: ''Pruning Self-attentions into Convolutional Layers in Single Path''.

Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti

Zhuang AI Group 77 Dec 26, 2022
PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners

Masked Autoencoders: A PyTorch Implementation This is a PyTorch/GPU re-implementation of the paper Masked Autoencoders Are Scalable Vision Learners: @

Meta Research 4.8k Jan 04, 2023
This porject is intented to build the most accurate model for predicting the porbability of loan default

Estimating-Loan-Default-Probability IBA ML2 Mid-project / Kaggle Competition This porject is intented to build the most accurate model for predicting

Adil Gahramanov 1 Jan 24, 2022
Pytorch implementation of RED-SDS (NeurIPS 2021).

Recurrent Explicit Duration Switching Dynamical Systems (RED-SDS) This repository contains a reference implementation of RED-SDS, a non-linear state s

Abdul Fatir 10 Dec 02, 2022
The dataset of tweets pulling from Twitters with keyword: Hydroxychloroquine, location: US, Time: 2020

HCQ_Tweet_Dataset: FREE to Download. Keywords: HCQ, hydroxychloroquine, tweet, twitter, COVID-19 This dataset is associated with the paper "Understand

2 Mar 16, 2022
RP-GAN: Stable GAN Training with Random Projections

RP-GAN: Stable GAN Training with Random Projections This repository contains a reference implementation of the algorithm described in the paper: Behna

Ayan Chakrabarti 20 Sep 18, 2021
Optimizing DR with hard negatives and achieving SOTA first-stage retrieval performance on TREC DL Track (SIGIR 2021 Full Paper).

Optimizing Dense Retrieval Model Training with Hard Negatives Jingtao Zhan, Jiaxin Mao, Yiqun Liu, Jiafeng Guo, Min Zhang, Shaoping Ma This repo provi

Jingtao Zhan 99 Dec 27, 2022
Analysis of Smiles through reservoir sampling & RDkit

Analysis of Smiles through reservoir sampling and machine learning (under development). This is a simple project that includes two Jupyter files for t

Aurimas A. Nausėdas 6 Aug 30, 2022
Automatically creates genre collections for your Plex media

Plex Auto Genres Plex Auto Genres is a simple script that will add genre collection tags to your media making it much easier to search for genre speci

Shane Israel 63 Dec 31, 2022
Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection

DDMP-3D Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021. Instroduction T

Li Wang 32 Nov 09, 2022
LinkNet - This repository contains our Torch7 implementation of the network developed by us at e-Lab.

LinkNet This repository contains our Torch7 implementation of the network developed by us at e-Lab. You can go to our blogpost or read the article Lin

e-Lab 158 Nov 11, 2022
Deployment of PyTorch chatbot with Flask

Chatbot Deployment with Flask and JavaScript In this tutorial we deploy the chatbot I created in this tutorial with Flask and JavaScript. This gives 2

Patrick Loeber (Python Engineer) 107 Dec 29, 2022
Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis"

StrengthNet Implementation of "StrengthNet: Deep Learning-based Emotion Strength Assessment for Emotional Speech Synthesis" https://arxiv.org/abs/2110

RuiLiu 65 Dec 20, 2022