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Convert JPG to TIFF

JPG to TIFF

There are many different file types available for images, each with its pros and cons. While the most common ones – JPEG and PNG, to name a few – dominate the world today, others have specific uses.

One of these file formats in particular, the Tag Image File Format (or TIFF for short), is used widely by graphic designers, photographers, and print industry professionals. It offers lossless images without any compression and can also operate as a container for multiple smaller JPEGs. And Cloudinary’s platform provides a powerful way to convert your pictures to and from any file format.

In this tutorial, we’ll create a simple script that takes an image from us and converts it to a TIFF file through the Cloudinary platform.

In this article:

Creating Our Application

We’ll be using Node for this project, so you should have some basic familiarity. The goal of this app is to be a simple process that can take a JPG image and convert it to a TIFF through Cloudinary’s Programmable Media platform. If you don’t already have a Cloudinary account, you can sign up for free.

First, we need to create a “jpg-to-tiff” folder and initialize npm to generate a package.json file.

“Image

Then, we’re going to install the required packages by running the following line of code:

npm i express cloudinary morgan dotenv express-formidable-v2

The packages installed using this line of code include:

  • ExpressJs: A minimalist NodeJS framework for building RESTful APIs.
  • Cloudinary: This allows easy integration with the Cloudinary platform.
  • Express-formidable-v2: A NodeJS middleware for handling multipart/form-data (files like images and videos).
  • Morgan: A NodeJS middleware used to log HTTP requests.
  • Dotenv: Used to load environment variables from an .env file.

We also suggest you download and use nodemon, for ease of use with Node. While it is not required, having it while still working on the backend is nice, so the server restarts automatically when changes are made.

After we have our dependencies, we’ll create an index.js file and insert the following code:

const express = require("express");
const morgan = require("morgan");
const app = express();
require("dotenv").config();
const PORT = process.env.PORT || 4000;
app.use(morgan("dev"));
app.get("/", (req, res) => {
  res.send("Cloudinary Video Overlay Tutorial ");
});
app.listen(PORT, () => {
  console.log(`Server listening on port ${PORT}`);
}); 

If you installed nodemon as a dev dependency, you’ll need to add this line of code to the “scripts” section in package.json:

"dev": "nodemon index.js"  

Now, we run the application. If you installed nodemon, use their command to start your server. Otherwise, use:

npm run dev  

Setting Up Cloudinary

After that’s all done, we’ll need to integrate Cloudinary. If you don’t have an account, you can sign up for a free one to start. Then, log in and retrieve your Cloudinary cloud name, API key, and API secret from the dashboard:

You’ll also need to create an .env file in the root folder and store the credentials as environmental variables. Then, create a “cloudinary.js” file with the following code:

const cloudinary = require(“cloudinary”).v2;

cloudinary.config({
  cloud_name: process.env.CLOUDINARY_CLOUD_NAME,
  api_key: process.env.CLOUDINARY_API_KEY,
  api_secret: process.env.CLOUDINARY_API_SECRET,
  secure: true,
}); 

After that’s set up, we’ll need to upload a picture to Cloudinary. For this tutorial, we’ll use a picture from pexels.com

In “cloudinary.js” in “config”, insert this code to upload the picture:

const cloudinaryImageUpload = (file) => {
  return new Promise((resolve, reject) => {
    cloudinary.uploader
      .upload(file)
      .then((result) => {
        resolve(result.public_id);
      })
      .catch((error) => {
        reject(error);
      });
  });
}; 

This is the code to convert jpg to tiff image format:

const pictureTransform = (img) => cloudinary.image(img, { format: "tiff" }); 

Then, create an UploadController.js file in “controllers” to retrieve the picture. This code will upload the picture to Cloudinary, and then convert it through their platform:

const pictureUpload = async (req, res) => {
  if (req.files !== undefined) {
    try {
      const pic = await cloudinaryImageUpload(req.files.picture.path);
      const transformedImage = pictureTransform(pic);
      res.status(200).json({
        sucess: true,
        picture: transformedImage,
      });
    } catch (error) {
      res.status(400).json({
        sucess: false,
        error,
      });
    }
  } else {
    res.status(400).json({
      sucess: false,
      error: "No image was uploaded",
    });
  }
}; 

Here’s what happens: we grab the path of the parsed image and upload it to Cloudinary using the “cloudinaryImageUpload” function in the “cloudinary.js” file. Then, the function returns the Public ID of the image, which is then sent to “pictureTransform” which changes the image to a .tiff.

You can use Postman to send a request to the server and make sure it’s working. A request is sent to the “upload” route with the picture attached.

Afterwhile, you should get a “200” response and the link to the .tiff image included:

The Wrap-Up

Hopefully, this little tutorial gave you a good idea of how to use the Cloudinary platform to convert your images. With a little more elbow grease, you can easily set this app up to scale with a ton of images, so you can convert to your hearts content.

See what else Cloudinary can do for you and your teams. Sign up for free and take advantage of our Media Experience Cloud to kickstart your business’s visuals. Sign up today.

QUICK TIPS
Nadin Indre
Cloudinary Logo Nadin Indre

In my experience, here are tips that can help you better handle JPG to TIFF conversions:

  1. Optimize color profiles during conversion Ensure the source JPG has the correct embedded color profile (e.g., sRGB or AdobeRGB). When converting to TIFF, preserve or convert to a high-fidelity profile like ProPhotoRGB for better color accuracy, especially for printing.
  2. Handle different compression types in TIFF TIFF files support multiple compression algorithms (e.g., LZW, ZIP). Choose the most suitable compression for your project to balance between file size and quality. LZW is lossless but compresses well, unlike uncompressed TIFF.
  3. Leverage multi-layer TIFF for complex edits Use the multi-page or multi-layer feature of TIFF files to store multiple image layers or versions in one file, especially useful in workflows where you want to retain different image states for future editing.
  4. Maintain high dynamic range (HDR) for professional edits Convert your JPG to a 16-bit TIFF file to preserve more image data. TIFF supports high-bit-depth images, essential for intricate retouching or professional color grading.
  5. Consider file size management for large TIFF images As TIFF files can be large, set up a process to batch compress or split them into smaller chunks, especially for large-scale projects. Automating this step will save significant storage space and improve transfer speeds.
  6. Ensure metadata is properly transferred Ensure that EXIF, IPTC, or XMP metadata is preserved during conversion. Some conversion processes strip metadata, which can affect subsequent editing, cataloging, or archival processes.
  7. Utilize progressive JPG for better quality retention If possible, start with progressive JPGs (instead of baseline) when converting to TIFF. Progressive JPGs store better quality data which can result in slightly improved TIFF output.
  8. Incorporate TIFF tags for better document organization Add TIFF tags (a feature within the format) to your converted files to embed descriptive information. This can be invaluable for archiving, categorization, or later retrieval of the images.
  9. Use Cloudinary transformation APIs for scaling and optimization Before converting to TIFF, use Cloudinary’s transformation options to resize or crop your images. Optimizing dimensions upfront ensures that TIFF files are not unnecessarily large due to oversized original JPGs.
  10. Integrate image quality control into automation Use automated visual quality checks post-conversion, especially when batch processing. Tools that measure sharpness, color consistency, or contrast help ensure the integrity of your TIFFs without manual review.
Last updated: Sep 8, 2024