multi-image-downloader

🧜‍♂️ Node Multiple Image Downloader

A fast and lightweight Node module for downloading images in bulk to local disk from an array of urls or url entries in a column of a .csv file.

🔱 Inspiration

While working on some image classification project with deep learning, we felt the lack of such a package which can download plenty of images from entries within a .csv file. 📂

📍 Hence, this downloader package was built and till date it supports two types of input ->

1. raw array of image urls 🐛
2. csv file with range of rows and column name specified. 🦋

Let's see how we can use this package to speed up our large image downloading phases.

🔱 Installation

npm install --save multi-image-downloader

🔱 Options

Parameter	Requirement	Default Value	Example
urls	Required, if csv not provided	[ ]	[ 'https://image1.jpg', 'https://image2.jpg', ... ]
targetFolder	Optional	'./downloads'	'./any/folder'
csv	Required, if urls not provided	""	'data.csv'
startRow	Optional	1	5
endRow	Optional	-1	1000
columnName	Optional	""	"image_urls"

🔱 Usage

Let's see how to build the options two use cases with examples ->

⚡ Raw url array

const urls = [
    "https://example.org/image1.jpg",
    "https://example.org/image2.jpg",
    "https://example.org/image3.jpg",
    "https://example.org/image4.jpg",
    .
    .
    .
]

const options = {
    urls,
    targetFolder: './any/folder' // optional
}

💥 With a CSV file

const csv = 'data.csv' // an available csv file address
const options = {
    csv,
    startRow: 10, 
    columnName: 1000,
    targetFolder: './any/folder', // optional
}

Now we will see how we use this option we just built in other projects.

const multiImageDownloader = require('multi-image-downloader');

// set up options as shown above

multiImageDownloader(options)

This will start downloading valid images in the targetFolder specified.

💰 After successful downloading of all the images, it will log

All images downloaded!

in the console.

Yeayy! We have successfully downloaded all our images and saved a lot of time! ⌛

Hope you enjoyed this journey. See ya in another doc of some other package! Have a nice day! 🌞