Skip to main content

Simple package that leverages IPython and HTML for more efficient, reach and interactive plotting of images in Jupyter Notebooks

Project description

IPyPlot is a small python package offering fast and efficient plotting of images inside Jupyter Notebooks cells. It's using IPython with HTML for faster, richer and more interactive way of displaying big number of images.

Displaying huge numbers of images with Python in Notebooks always was a big pain for me as I always used matplotlib for that task and never have I even considered if it can be done faster, easier or more efficiently.
Especially in one of my recent projects I had to work with a vast number of document images in a very interactive way which led me to forever rerunning notebook cells and waiting for countless seconds for matplotlib to do it's thing..
My frustration grew up to a point were I couldn't stand it anymore and started to look for other options..
Best solution I found involved using IPython.display function in connection with simple HTML. Using that approach I built a simple python package called IPyPlot which finally helped me cure my frustration and saved a lot of my time

Getting Started

Checkout the examples below and gear-images-examples.ipynb notebook which holds end to end examples for using IPyPlot.

Installation

IPyPlot can be installed directly from this repo using pip:

pip install git+https://github.com/karolzak/ipyplot

or through PyPI

pip install ipyplot

Usage examples

IPyPlot offers 3 main functions which can be used for displaying images in notebooks:

To start working with IPyPlot you need to simply import it like this:

import ipyplot

and use any of the available plotting functions shown below (notice execution times).
images - should be a numpy array of either string (image file paths), PIL.Image objects or numpy.array objects representing images
labels - should be a numpy array of string

Display images in separate, interactive tabs for each class

Display a collection of images

Display class representations (first image for each class)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ipyplot-1.0.5.tar.gz (4.9 kB view details)

Uploaded Source

Built Distribution

ipyplot-1.0.5-py3-none-any.whl (6.3 kB view details)

Uploaded Python 3

File details

Details for the file ipyplot-1.0.5.tar.gz.

File metadata

  • Download URL: ipyplot-1.0.5.tar.gz
  • Upload date:
  • Size: 4.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for ipyplot-1.0.5.tar.gz
Algorithm Hash digest
SHA256 d5d3fa04b8d3e1960435fceb62e13b7e9e575920ce1c4ae734dfeb773b7645b1
MD5 142fc13d36ed2e3491c17a2c91f89047
BLAKE2b-256 b858c5ea9105d3ae457a54e7063fcd38900ecf88d327a79b6c8b2e70d4ff5faa

See more details on using hashes here.

File details

Details for the file ipyplot-1.0.5-py3-none-any.whl.

File metadata

  • Download URL: ipyplot-1.0.5-py3-none-any.whl
  • Upload date:
  • Size: 6.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.1.1 pkginfo/1.5.0.1 requests/2.22.0 setuptools/46.1.3 requests-toolbelt/0.9.1 tqdm/4.36.1 CPython/3.7.4

File hashes

Hashes for ipyplot-1.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 09f316f16bc77a0c9c6ae1d4b6560cd4b57cf76dd8262d9f7e67c8873a5dd6fb
MD5 569e1719e58300fa997f1f97f6cf37b8
BLAKE2b-256 c87973a14a6d2727555a14c62b9acb97c8f2624d6d878d9964054f2f039f6a7a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page