Interactive convnet features visualization for Keras

Overview

Quiver

Gitter chat

Interactive convnet features visualization for Keras

gzqll3

The quiver workflow

Video Demo

  1. Build your model in keras

    model = Model(...)
  2. Launch the visualization dashboard with 1 line of code

    quiver_engine.server.launch(model, classes=['cat','dog'], input_folder='./imgs')
  3. Explore layer activations on all the different images in your input folder.

Quickstart

Installation

    pip install quiver_engine

If you want the latest version from the repo

    pip install git+git://github.com/keplr-io/quiver.git

Usage

Take your keras model, launching Quiver is a one-liner.

    from quiver_engine import server
    server.launch(model)

This will launch the visualization at localhost:5000

Options

    server.launch(
        model, # a Keras Model

        classes, # list of output classes from the model to present (if not specified 1000 ImageNet classes will be used)

        top, # number of top predictions to show in the gui (default 5)

        # where to store temporary files generatedby quiver (e.g. image files of layers)
        temp_folder='./tmp',

        # a folder where input images are stored
        input_folder='./',

        # the localhost port the dashboard is to be served on
        port=5000,
        # custom data mean
        mean=[123.568, 124.89, 111.56],
        # custom data standard deviation
        std=[52.85, 48.65, 51.56]
    )

Development

Building from master

Check out this repository and run

cd quiver_engine
python setup.py develop

Building the Client

    cd quiverboard
    npm install
    export QUIVER_URL=localhost:5000 # or whatever you set your port to be
    npm start

Note this will run your web application with webpack and hot reloading. If you don't care about that, or are only in this section because pip install somehow failed for you, you should tell it to simply build the javascript files instead

    npm run deploy:prod

Credits

  • This is essentially an implementation of some ideas of deepvis and related works.
  • A lot of the pre/pos/de processing code was taken from here and other writings of fchollet.
  • The dashboard makes use of react-redux-starter-kit

Citing Quiver

misc{bianquiver,
  title={Quiver},
  author={Bian, Jake},
  year={2016},
  publisher={GitHub},
  howpublished={\url{https://github.com/keplr-io/quiver}},
}
Bias and Fairness Audit Toolkit

The Bias and Fairness Audit Toolkit Aequitas is an open-source bias audit toolkit for data scientists, machine learning researchers, and policymakers

Data Science for Social Good 513 Jan 06, 2023
Implementation of linear CorEx and temporal CorEx.

Correlation Explanation Methods Official implementation of linear correlation explanation (linear CorEx) and temporal correlation explanation (T-CorEx

Hrayr Harutyunyan 34 Nov 15, 2022
Pytorch implementation of convolutional neural network visualization techniques

Convolutional Neural Network Visualizations This repository contains a number of convolutional neural network visualization techniques implemented in

Utku Ozbulak 7k Jan 03, 2023
A collection of research papers and software related to explainability in graph machine learning.

A collection of research papers and software related to explainability in graph machine learning.

AstraZeneca 1.9k Dec 26, 2022
Interpretability and explainability of data and machine learning models

AI Explainability 360 (v0.2.1) The AI Explainability 360 toolkit is an open-source library that supports interpretability and explainability of datase

1.2k Dec 29, 2022
Python implementation of R package breakDown

pyBreakDown Python implementation of breakDown package (https://github.com/pbiecek/breakDown). Docs: https://pybreakdown.readthedocs.io. Requirements

MI^2 DataLab 41 Mar 17, 2022
pytorch implementation of "Distilling a Neural Network Into a Soft Decision Tree"

Soft-Decision-Tree Soft-Decision-Tree is the pytorch implementation of Distilling a Neural Network Into a Soft Decision Tree, paper recently published

Kim Heecheol 262 Dec 04, 2022
tensorboard for pytorch (and chainer, mxnet, numpy, ...)

tensorboardX Write TensorBoard events with simple function call. The current release (v2.1) is tested on anaconda3, with PyTorch 1.5.1 / torchvision 0

Tzu-Wei Huang 7.5k Jan 07, 2023
A game theoretic approach to explain the output of any machine learning model.

SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allo

Scott Lundberg 18.3k Jan 08, 2023
A Practical Debugging Tool for Training Deep Neural Networks

Cockpit is a visual and statistical debugger specifically designed for deep learning!

31 Aug 14, 2022
Auralisation of learned features in CNN (for audio)

AuralisationCNN This repo is for an example of auralisastion of CNNs that is demonstrated on ISMIR 2015. Files auralise.py: includes all required func

Keunwoo Choi 39 Nov 19, 2022
Visualizer for neural network, deep learning, and machine learning models

Netron is a viewer for neural network, deep learning and machine learning models. Netron supports ONNX, TensorFlow Lite, Keras, Caffe, Darknet, ncnn,

Lutz Roeder 20.9k Dec 28, 2022
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.

ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi

ModelChimp 124 Dec 21, 2022
Logging MXNet data for visualization in TensorBoard.

Logging MXNet Data for Visualization in TensorBoard Overview MXBoard provides a set of APIs for logging MXNet data for visualization in TensorBoard. T

Amazon Web Services - Labs 327 Dec 05, 2022
Code for "High-Precision Model-Agnostic Explanations" paper

Anchor This repository has code for the paper High-Precision Model-Agnostic Explanations. An anchor explanation is a rule that sufficiently “anchors”

Marco Tulio Correia Ribeiro 735 Jan 05, 2023
Algorithms for monitoring and explaining machine learning models

Alibi is an open source Python library aimed at machine learning model inspection and interpretation. The focus of the library is to provide high-qual

Seldon 1.9k Dec 30, 2022
Pytorch Feature Map Extractor

MapExtrackt Convolutional Neural Networks Are Beautiful We all take our eyes for granted, we glance at an object for an instant and our brains can ide

Lewis Morris 40 Dec 07, 2022
⬛ Python Individual Conditional Expectation Plot Toolbox

⬛ PyCEbox Python Individual Conditional Expectation Plot Toolbox A Python implementation of individual conditional expecation plots inspired by R's IC

Austin Rochford 140 Dec 30, 2022
Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

Summary Explorer is a tool to visually explore the state-of-the-art in text summarization.

Webis 42 Aug 14, 2022
python partial dependence plot toolbox

PDPbox python partial dependence plot toolbox Motivation This repository is inspired by ICEbox. The goal is to visualize the impact of certain feature

Li Jiangchun 722 Dec 30, 2022