#Gulp image resize windows not working code#

To resize the image, we first chain the resize() function to the sharp instance. toFile(_dirname + '/processed_images/resize_robo.jpg') To resize an image, first create a new file: touch _resize.jsĬonst resize = sharp('./images/robo.jpg') The rotate() method takes the rotation angle as an input and saves it as a new image: rotate_robo.jpg. We use the rotate() method within the function scope, which is chained to the sharp module. In this example, the rotateImage() function reads the image and returns it rotated by 250deg. toFile(_dirname + '/processed_images/rotate_robo.jpg')

Now, add the following code: const sharp = require('sharp') To rotate an image, start by creating a new file: touch _rotate.js Now, we run the following command: node _metadata.js We save the metadata variable and log to the terminal using console.log(). We use the metadata() function to extract the image metadata. To extract the image metadata, start by creating a new file: touch _metadata.jsĬonst metadata = sharp('./images/robo.jpg').metadata() Here’s the newly created tinted image, tint_robo.jpg: Save the file and run the following command: node _tint.js For this example, we use the 255 maximum value for the red parameter: r. The scale for this method is 0 to 255, with higher chroma values resulting in a more saturated tint. With this method, we can specify the intensity of the red, green, and blue chroma values. We use the tint() method of the sharp module to alter the color of the image. toFile(_dirname + '/processed_images/tint_robo.jpg') Now, copy the following code: const sharp = require('sharp') To tint an image, start by creating a new file: touch _tint.js The newly created grayscale image, grayscale_robo.jpg, can be found in the processed_image folder:

#Gulp image resize windows not working code#

Now, we run the file code on the terminal: node _grayscale.js We save the altered image in the processed_images folder using the toFile() method. Then, we chain the sharp module’s grayscale() method to the sharp instance to alter the image’s appearance. To carry out the processing task, we define the convertTograyscale() function. We use the sharp() instance within the require() function scope to read the path to our image. In this example, we start by creating an instance of the sharp module. toFile(_dirname + '/processed_images/grayscale_robo.jpg') Next, copy the following code: const sharp = require('sharp') To convert an image to grayscale, create a new file in the editor’s terminal: touch _grayscale.js Now, open the directory using your favorite IDE. Next, migrate to a new directory: cd sharp_project To set up a sharp image project, start by creating a new directory in the editor’s terminal: mkdir sharp_project The only prerequisite for this tutorial is a system set up with Node.js and npm. In this tutorial, we’ll analyze and modify an image using the sharp Node.js library. This module can produce images in JPEG, PNG, WebP, AVIF, and TIFF formats as well as uncompressed raw pixel data. sharp can read JPEG, PNG, WebP, AVIF, TIFF, GIF, and SVG image formats. Sharp converts large common image formats to smaller, web-friendly images. sharp compresses images faster than most other Node.js modules, like ImageMagick, Jimp, or Squoosh, and produces high-quality results. This module assists with UGC management by offering an easy solution for reading, enhancing, and saving image files. Sharp is a high-performance image processing module for Node.js. A robust image processing solution can be invaluable for UGC management. However, excessively large or unoptimized image files can negatively impact performance and user experience. Images are an important component of most applications that handle user-generated content. Pascal Akunne Follow A JavaScript developer focused on building human-centric products with HTML, CSS, React, Node.js, and MongoDB Processing images with sharp in Node.js