https://github.com/i008/easyimages

Thin wrapper ontop of PIL to explore,visualize and share images
https://github.com/i008/easyimages

image-dataset image-processing image-viewer imread pil pillow visualization

Last synced: about 2 months ago
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Thin wrapper ontop of PIL to explore,visualize and share images

• Host: GitHub
• URL: https://github.com/i008/easyimages
• Owner: i008
• License: mit
• Created: 2018-08-24T21:19:23.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2020-10-15T19:49:28.000Z (about 4 years ago)
• Last Synced: 2024-09-19T14:19:11.383Z (4 months ago)
• Topics: image-dataset, image-processing, image-viewer, imread, pil, pillow, visualization
• Language: Jupyter Notebook
• Homepage:
• Size: 6.85 MB
• Stars: 15
• Watchers: 2
• Forks: 2
• Open Issues: 0
• Metadata Files:
  • Readme: README.MD
  • Changelog: HISTORY.rst
  • Contributing: CONTRIBUTING.rst
  • License: LICENSE

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README

        

# easyimages

![Build Test Release](https://github.com/i008/easyimages/workflows/Build%20Test%20Release/badge.svg)

# Info

This small but handy package solves several issues i had while working with images and image datasets - especially in the context

of exploring datsets, inspecting and shareing the results.

Keep in mind that his package is not directly related to the training process and loading

image data, for that i found pytorch dataloading patterns to work very well.

# Installation

```bash

pip install easyimages

```

Features

--------

- Simple API

- Easy image exploration

- Inteligent behaviour based on execution context (terminal, jupyter etc)

- Lazy evaluation

- Loading images from many different sources (filesystem, pytorch, numpy, web-urls, etc)

- Storing annotations (tags, bounding boxes) allong the image in the same object

- Visualizing labels (drawing boxes and drawing the label onto the image)

- Visualizing images as Grids (ImagesLists)

- Visualizing huge amounts of images at once (by leveraging fast html rendering)

- Displaying images while working in jupyter notebook

- Displaying images inline in console mode (iterm)

Credits

-------

MAP calculation code comes from: 

https://github.com/MathGaron/mean_average_precision