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chocolate-bars

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Readme

🍫 chocolate-bars readme

Present histograms (bars!) of images in a directory, including extras such as exif data from the camera.

Electron based app which runs on node.js.

status - !in development!

chocolate-bars is in ongoing development (Linux, Mac, Windows) following semantic versioning.

why?

Histograms are useful for finding image defects such as:

over-exposure
under-exposure
low contrast

Also was curious how to implement this in node.js.

dependencies

Node 8.11.3 or higher

features (in development!)

scan a folder of images and present a browsable summary
show image thumbnail and histogram
show additional image properties such as file size, image size
show exif tags where available (JPEG files)

usage - as cli (command line tool)

1 Install dependencies

Install:

Yarn
Node 8.3.11 (or higher)

2 get chocolate bars of images

Screenshot

ways to run

You can run chocolate-bars in one of two ways:

a) from the source code
OR b) as a globally installed command line tool

a) from the source code

yarn

On Windows: use a bash shell like git bash.

To test your installation:

./test.sh

To check your images:

./go.sh <path to image direcory>

example:

./go.sh ../myPhotos

To see more detailed usage info:

./go.sh

b) install globally as a command line tool

npm i -g electron@4

npm i -g chocolate-bars@latest --production

To use:

chocolate-bars <path to image direcory>

references

electron starter

https://github.com/electron/electron-quick-start

electron and react boilerplate

https://github.com/iRath96/electron-react-typescript-boilerplate

https://github.com/electron-react-boilerplate/electron-react-boilerplate

sites

site	URL
source code (github)	https://github.com/mrseanryan/chocolate-bars
github page	https://mrseanryan.github.io/chocolate-bars/
npm	https://www.npmjs.com/package/chocolate-bars

developing code in this repository

see the contributing readme.

origin

This project is based on the excellent seeder project typescript-library-starter.

ORIGINAL readme (from the seeder project)

see here

authors

Original work by Sean Ryan - mr.sean.ryan(at gmail.com)

licence = MIT

This project is licensed under the MIT License - see the LICENSE file for details