Matplotlib Image labeller for classifying images

Overview

mpl-image-labeller

Binder Documentation Status

License PyPI Python Version

Use Matplotlib to label images for classification. Works anywhere Matplotlib does - from the notebook to a standalone gui!

For more see the documentation.

Install

pip install mpl-image-labeller

Key features

  • Simple interface
  • Uses keys instead of mouse
  • Only depends on Matplotlib
    • Works anywhere - from inside Jupyter to any supported GUI framework
  • Displays images with correct aspect ratio
  • Easily configurable keymap
  • Smart interactions with default Matplotlib keymap
  • Callback System (see examples/callbacks.py)

single class per image

gif of usage for labelling images of cats and dogs

multiple classes per image

gif of usage for labelling images of cats and dogs

Usage

import matplotlib.pyplot as plt
import numpy as np

from mpl_image_labeller import image_labeller

images = np.random.randn(5, 10, 10)
labeller = image_labeller(
    images, classes=["good", "bad", "meh"], label_keymap=["a", "s", "d"]
)
plt.show()

accessing the axis You can further modify the image (e.g. add masks over them) by using the plotting methods on axis object accessible by labeller.ax.

Lazy Loading Images If you want to lazy load your images you can provide a function to give the images. This function should take the integer idx as an argument and return the image that corresponds to that index. If you do this then you must also provide N_images in the constructor to let the object know how many images it should expect. See examples/lazy_loading.py for an example.

Controls

  • <- move one image back
  • -> move one image forward

To label images use the keys defined in the label_keymap argument - default 0, 1, 2...

Get the labels by accessing the labels property.

Overwriting default keymap

Matplotlib has default keybindings that it applied to all figures via rcparams.keymap that allow for actions such as s to save or q to quit. If you inlcude one of these keys as a shortcut for labelling as a class then that default keymap will be disabled for that figure.

Related Projects

This is not the first project to implement easy image labelling but seems to be the first to do so entirely in Matplotlib. The below projects implement varying degrees of complexity and/or additional features in different frameworks.

You might also like...
This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models are Pix2Pix, Pix2PixHD, CycleGAN and PointWise.

RGB2NIR_Experimental This repository contains several image-to-image translation models, whcih were tested for RGB to NIR image generation. The models

Official implement of Paper:A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening  images
Official implement of Paper:A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sening images

A deeply supervised image fusion network for change detection in high resolution bi-temporal remote sensing images 深度监督影像融合网络DSIFN用于高分辨率双时相遥感影像变化检测 Of

The first dataset of composite images with rationality score indicating whether the object placement in a composite image is reasonable.
The first dataset of composite images with rationality score indicating whether the object placement in a composite image is reasonable.

Object-Placement-Assessment-Dataset-OPA Object-Placement-Assessment (OPA) is to verify whether a composite image is plausible in terms of the object p

For auto aligning, cropping, and scaling HR and LR images for training image based neural networks

ImgAlign For auto aligning, cropping, and scaling HR and LR images for training image based neural networks Usage Make sure OpenCV is installed, 'pip

Rename Images with Auto Generated Neural Image Captions

Recaption Images with Generated Neural Image Caption Example Usage: Commandline: Recaption all images from folder /home/feng/Downloads/images to folde

A python-image-classification web application project, written in Python and served through the Flask Microframework. This Project implements the VGG16 covolutional neural network, through Keras and Tensorflow wrappers, to make predictions on uploaded images.
Image-to-Image Translation with Conditional Adversarial Networks (Pix2pix) implementation in keras

pix2pix-keras Pix2pix implementation in keras. Original paper: Image-to-Image Translation with Conditional Adversarial Networks (pix2pix) Paper Author

Learning Continuous Image Representation with Local Implicit Image Function
Learning Continuous Image Representation with Local Implicit Image Function

LIIF This repository contains the official implementation for LIIF introduced in the following paper: Learning Continuous Image Representation with Lo

Comments
Releases(1.1.2)
  • 1.1.2(Nov 18, 2022)

  • 1.1.1(Nov 12, 2021)

    What's Changed

    • add github actions test by @ianhi in https://github.com/ianhi/mpl-image-labeller/pull/20
    • Autoscale cmaps + add tests by @ianhi in https://github.com/ianhi/mpl-image-labeller/pull/21
    • Updated callbacks example to show how to adjust overlay extent

    Full Changelog: https://github.com/ianhi/mpl-image-labeller/compare/1.1.0...1.1.1

    Source code(tar.gz)
    Source code(zip)
  • 1.1.0(Nov 1, 2021)

    What's Changed

    • Added ability for user to set the title https://github.com/ianhi/mpl-image-labeller/pull/15
    • Updated text positioning for single class labeller

    Full Changelog: https://github.com/ianhi/mpl-image-labeller/compare/1.0.0...1.1.0

    Source code(tar.gz)
    Source code(zip)
  • 1.0.0(Oct 30, 2021)

  • 0.5.0(Oct 29, 2021)

    • Fixed xlims getting messed up when zooming in https://github.com/ianhi/mpl-image-labeller/pull/9
    • Allow passing imshow_kwargs https://github.com/ianhi/mpl-image-labeller/commit/27afa0bf9633c5f59e2d3089f9fef789147e2b3c
    Source code(tar.gz)
    Source code(zip)
  • 0.4.0(Oct 29, 2021)

  • 0.3.0(Oct 27, 2021)

  • 0.2.0(Oct 27, 2021)

    Full Changelog: https://github.com/ianhi/mpl-image-labeller/compare/0.1.1...0.2.0

    Fixes:

    init_labels is respected

    new features:

    1. ax is not accesible through the .ax attribute
    2. images can now be a callable

    Thanks to @jrussell25 for suggesting these improvements

    Source code(tar.gz)
    Source code(zip)
  • 0.1.1(Oct 27, 2021)

Owner
Ian Hunt-Isaak
The embodiment of entropy - He/Him
Ian Hunt-Isaak
The ARCA23K baseline system

ARCA23K Baseline System This is the source code for the baseline system associated with the ARCA23K dataset. Details about ARCA23K and the baseline sy

4 Jul 02, 2022
Writeups for the challenges from DownUnderCTF 2021

cloud Challenge Author Difficulty Release Round Bad Bucket Blue Alder easy round 1 Not as Bad Bucket Blue Alder easy round 1 Lost n Found Blue Alder m

DownUnderCTF 161 Dec 31, 2022
GANimation: Anatomically-aware Facial Animation from a Single Image (ECCV'18 Oral) [PyTorch]

GANimation: Anatomically-aware Facial Animation from a Single Image [Project] [Paper] Official implementation of GANimation. In this work we introduce

Albert Pumarola 1.8k Dec 28, 2022
Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition"

CLIPstyler Official Pytorch implementation of "CLIPstyler:Image Style Transfer with a Single Text Condition" Environment Pytorch 1.7.1, Python 3.6 $ c

201 Dec 29, 2022
The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate.

The lightweight PyTorch wrapper for high-performance AI research. Scale your models, not the boilerplate. Website • Key Features • How To Use • Docs •

Pytorch Lightning 21.1k Jan 08, 2023
ML From Scratch

ML from Scratch MACHINE LEARNING TOPICS COVERED - FROM SCRATCH Linear Regression Logistic Regression K Means Clustering K Nearest Neighbours Decision

Tanishq Gautam 66 Nov 02, 2022
Source code for our paper "Do Not Trust Prediction Scores for Membership Inference Attacks"

Do Not Trust Prediction Scores for Membership Inference Attacks Abstract: Membership inference attacks (MIAs) aim to determine whether a specific samp

<a href=[email protected]"> 3 Oct 25, 2022
Patch-Based Deep Autoencoder for Point Cloud Geometry Compression

Patch-Based Deep Autoencoder for Point Cloud Geometry Compression Overview The ever-increasing 3D application makes the point cloud compression unprec

17 Dec 05, 2022
Rethinking of Pedestrian Attribute Recognition: A Reliable Evaluation under Zero-Shot Pedestrian Identity Setting

Pytorch Pedestrian Attribute Recognition: A strong PyTorch baseline of pedestrian attribute recognition and multi-label classification.

Jian 79 Dec 18, 2022
Perfect implement. Model shared. x0.5 (Top1:60.646) and 1.0x (Top1:69.402).

Shufflenet-v2-Pytorch Introduction This is a Pytorch implementation of faceplusplus's ShuffleNet-v2. For details, please read the following papers:

423 Dec 07, 2022
Efficient 3D Backbone Network for Temporal Modeling

VoV3D is an efficient and effective 3D backbone network for temporal modeling implemented on top of PySlowFast. Diverse Temporal Aggregation and

102 Dec 06, 2022
A library for hidden semi-Markov models with explicit durations

hsmmlearn hsmmlearn is a library for unsupervised learning of hidden semi-Markov models with explicit durations. It is a port of the hsmm package for

Joris Vankerschaver 69 Dec 20, 2022
Subdivision-based Mesh Convolutional Networks

Subdivision-based Mesh Convolutional Networks The official implementation of SubdivNet in our paper, Subdivion-based Mesh Convolutional Networks Requi

Zheng-Ning Liu 181 Dec 28, 2022
Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks

Classification of Long Sequential Data using Circular Dilated Convolutional Neural Networks arXiv preprint: https://arxiv.org/abs/2201.02143. Architec

19 Nov 30, 2022
Implementation of "Selection via Proxy: Efficient Data Selection for Deep Learning" from ICLR 2020.

Selection via Proxy: Efficient Data Selection for Deep Learning This repository contains a refactored implementation of "Selection via Proxy: Efficien

Stanford Future Data Systems 70 Nov 16, 2022
COIN the currently largest dataset for comprehensive instruction video analysis.

COIN Dataset COIN is the currently largest dataset for comprehensive instruction video analysis. It contains 11,827 videos of 180 different tasks (i.e

86 Dec 28, 2022
Scale-aware Automatic Augmentation for Object Detection (CVPR 2021)

SA-AutoAug Scale-aware Automatic Augmentation for Object Detection Yukang Chen, Yanwei Li, Tao Kong, Lu Qi, Ruihang Chu, Lei Li, Jiaya Jia [Paper] [Bi

DV Lab 182 Dec 29, 2022
[TNNLS 2021] The official code for the paper "Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement"

CSDNet-CSDGAN this is the code for the paper "Learning Deep Context-Sensitive Decomposition for Low-Light Image Enhancement" Environment Preparing pyt

Jiaao Zhang 17 Nov 05, 2022
Lolviz - A simple Python data-structure visualization tool for lists of lists, lists, dictionaries; primarily for use in Jupyter notebooks / presentations

lolviz By Terence Parr. See Explained.ai for more stuff. A very nice looking javascript lolviz port with improvements by Adnan M.Sagar. A simple Pytho

Terence Parr 785 Dec 30, 2022
a project for 3D multi-object tracking

a project for 3D multi-object tracking

155 Jan 04, 2023