Konva VS fabric.js

Based on this, I found that some of the libraries are dead and no longer have any support. Only two libraries are still alive and have significant amount of stars on GitHub and downloads on NPM. They are Fabric.js and Konva.js.

I have been assigned a task to create a sort of a canva clone which will have almost same features as canva with authentication, access control and rating system(not in this phase). I need help in finding libraries similar to https://konvajs.org/ which has updated docs and great support for Nextjs.

I'm currently using konva (& react-konva) package, to utilize it in Node.js enviroment I also need canvas package installed in. However, when running the code encountering this error:

used goJS in one project and konva in another

All the UI part would make sense to do in React. The actual drawing board you likely would need to implement in canvas or SVG. It still could be a React component, but for actual drawing, you'd probably use something like Konva (https://konvajs.org/).

Konvajs - is an HTML5 Canvas JavaScript framework that enables high performance animations, transitions, node nesting, layering, filtering, caching, event handling for desktop and mobile applications, and much more.

During the development of a complex interactive UI for the configuration of a digital laboratory ecosystem, we were utilizing the Konva.js library. Konva is a wrapper around the HTML canvas that simplifies working with shapes and interacting with the canvas a lot. Everybody dealing with the plain canvas API knows how much code certain tasks require, especially when user interaction with the drawn shapes is required. The most important features Konva offers to me are

Konva.js - example

Have a go at petswitch.com if you wish... I made the original Petswitch almost ten years ago, and it's had mild success since then, including CNET writing an article about it and it receiving the prestigious honour of 'most useless website' in week 41 of 2018, as determined by theuselesswebindex.com. Aside from the obvious question of why I even made this, it was getting pretty creaky – I originally built it with PHP and ImageMagick, with the facial features being manually selected via jQuery UI. So I decided to rebuild the whole thing with a full face-to-pet ML pipeline, on static hosting. To get the human face features, the app renders the upload to a temporary img element. This is a handy way to orient the image correctly via the browser, and saves having to deal with EXIF data. It's then resized, rendered to a canvas element, converted to a base64 string, then sent via fetch to Google's Cloud Vision API, which returns landmark coordinates of the face. I use these coordinates to correct any tilt on the face, mask the eyes and mouth via a mask image, then store each masked element as an additional canvas. Detecting pet faces was trickier. Google, Amazon and Microsoft all offer object detection APIs via transfer learning, and the approach is largely the same: you supply a series of images with bounding boxes around the objects you want to detect, either added via a web interface or uploaded via their API. You train a model online from these supplied images, then the service will return the estimated coordinates of any detected objects in an uploaded image. I found a dataset of both cats and dogs that had been labelled with landmarks on their faces, then wrote a script to convert the landmarks into bounding boxes around their eyes and nose, the dimensions based on a simple formula around the distance between the eyes in each image. All in all it's been trained on about 17,000 images of cats and dogs, and the accuracy seems to be pretty good. I was pleased to discover it actually works pretty well on other pets too. I've also added some friendly pets to the Petswitch family for those that don't have a pet on hand. I decided not to use a framework for this, it's written from scratch using a series of ES6 modules – although I did use Konva to handle the manual selection of facial features if the API can't detect a face. I used ParcelJS as my task runner, and my detection APIs are hosted on Firebase Cloud Functions. Let me know if you have any questions, although I can offer no good explanation for why I created this monstrosity...

This AI-powered Story Card Maker is built as a SvelteKit application with Typescript. Using Flowbite Svelte component library, the whole application was laid out. The layout for the Story Card (emulating the size of a postcard - 4" x 3") is created as an HTML Canvas using Fabric.js.

Fabric.js is a powerful and simple Javascript HTML5 canvas library. It provides an interactive object model on top of the canvas element. Fabric also has SVG-to-canvas (and canvas-to-SVG) parser.

Based on this, I found that some of the libraries are dead and no longer have any support. Only two libraries are still alive and have significant amount of stars on GitHub and downloads on NPM. They are Fabric.js and Konva.js.

I'm actually in the process of building something similar. It's a React app and I'm using the FabricJs library

I've played with this tech in early 2010s - they are using HTML5 Canvas tech + something like Fabric.js(http://fabricjs.com/) that controls Canvas objects.

this library might help you: http://fabricjs.com/

I did some research and the most promising result was using Fabric.js (http://fabricjs.com/) to put images on products. I may not be experienced enough in JS to understand the full capabilities of this library, but it looks like most of their stuff works on flat surfaces. I am trying to replicate the properly wrapped/textured affect that is achieved in the blanket below.

set up a canvas drawing & rendering framework, for example http://fabricjs.com/

body{ display:flex; flex-direction:column; align-items:center; }

Learning Fabric

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Next, we initiate a Canvas instance in our script tag:

Syntax

new fabric.Canvas(element: HTMLElement|String, options: Object)

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This allows Fabric.js to create this class instance so that we can use the provided methods of Fabric.js:

const canvas = new fabric.Canvas("canvas", {})

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Now, we’ll go ahead and give our canvas different properties, such as width, height, and background color:

const canvas = new fabric.Canvas("canvas", {
 width:500,
 height:500,
 backgroundColor:green
})

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Output

Creating a Rectangle with Fabric.js

Now that we’ve initialized a canvas and given it various properties, we’re going to create a rectangle using the Fabric.js object fabric.Rect:

Syntax

new fabric.Rect({object})

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Here the object houses the rectangle properties:

const canvas = new fabric.Canvas("canvas", {
 width:500,
 height:500,
 backgroundColor:green
});

const rectangle = new fabric.Rect({
 width:200,
 height:200,
 /* fill is used to define the background color*/
    fill:'red'
})
/*the add method is used to add objects to the canvas element */
canvas.add(rectangle)
/*the renderAll method used to render the canvas*/
canvas.renderAll();

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The add() method is used to add objects to the Canvas element. In this case, it adds the rectangle we created to the canvas:

Output

Creating a Circle

In the same way, we’ll create a circle. This time, we’ll use fabric.Circle:

const canvas = new fabric.Canvas("canvas", {
 width:500,
 height:500,
 backgroundColor:"lightgray"
});

const circle = new fabric.Circle({
 radius:60,
 fill:"blue"
})
canvas.add(circle);
canvas.renderALl();

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Output

With the above steps, we created a rectangle and a circle using Fabric.js. Note how interactive the objects are! Next, we’ll discuss images in Fabric.js.

Images with Fabric

The Fabric.Image is a Fabric.js object used to render images on a canvas. With Fabric.js, we can interact with the image. Images can be added to our canvas in two ways:

• Fabric.Image
• Fabric.Image.fromURL

Using the Fabric.Image constructor requires us to create an image element in our HTML and then insert it into the constructor:

Syntax

fabric.Image(image_element)

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HTML

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JS

const image_element = document.querySelector('#image');
const image = new fabric.Image(image_element)
canvas.add(image);
canvas.renderAll();

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However, Fabric.Image.fromURL requires only the image URL (the URL can be retrieved from a website or your local folder), and is simpler than the former:

fabric.Image.fromURL(URL, function());

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After passing the URL, the callback function after the image is loaded. The first default parameter of the callback function is the fabric.Image object. Now, we can modify the image properties and then add it to the canvas:

const canvas = new fabric.Canvas("canvas", {
 width:500,
 height:500,
 backgroundColor:"White"
});

fabric.Image.fromURL('my_image.png',(img) => {
 // the scaleToHeight property is use to set the image height
    img.scaleToHeight(250)
 // scaleToWidth is use to set the image width
    img.scaleToWidth(250)
    canvas.add(img)  
})
canvas.renderAll()

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Output

Editing Images with Fabric.js

Now that we know how to insert an image into a canvas, we’ll look at other image objects like image filters.

Image Filters

Fabric.js provides us with built-in filters:

• BaseFilter
• Brightness
• convolute
• GradientTransparency
• Grayscale
• Invert
• Mask
• Noise
• Pixelate
• RemoveWhite
• Sepia
• Sepia2
• Tint

Every instance of fabric.Image has the "filters" property, which is a simple array of filters. We can use the array method to perform any required operation, including removing filters (pop, slice, shift), adding filters (push, unshift, slice), and even combining multiple filters. When we call applyFilters, any filter in the “filters” array will be applied one by one. Let’s use some of these filters:

Syntax

new fabric.Image.filters
// after that you can add any filter of your choice
// Example 
new fabric.Image.filters.Grayscale()

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fabric.Image.fromURL('my_image.png', (image) => {
      image.scaleToHeight(300)
       image.ScaleToWidth(300)

 // Creating filter
 const filter = new fabric.Image.filters.Grayscale()

 //push the filter instance to filters
        image.filter.push(filter)

 // apply filter
         image.applyFilters()

 //add image into canvas (it also re-render the canvas)
         canvas.add(image)
},{crossOrigin: 'anonymous'});
canvas.renderAll();

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Output

Above, we used the Grayscale filter; we can also apply other filters. All we have to do is simply change the filter, as shown in this example:

fabric.Image.fromURL('my_image.png', (image) => {
      image.scaleToHeight(300)
       image.ScaleToWidth(300)

 // creating filter
 const filter = new fabric.Image.filters.Sepia()

 //add filter
        image.filter.push(filter)

 // apply filter
         image.applyFilters()

 //add image into canvas (it also re-render the canvas)
         canvas.add(image)
},{crossOrigin: 'anonymous'});
canvas.renderAll();

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Output

Image Blending

Blending is mixing two or more images to create a new image. Fabric.js gives us this ability. Here, we’re going to use the image blending filter for our image:

Syntax

new fabric.Image.filters.BlendImage({
 // the image that we want to blend
          image:imageA,
 // blend mode (in this case we are using the 'add' mode)
          mode:'add',

 alpha:0.5
      });

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fabric.Image.fromURL('my_image.png', (imageA) => {
    imageA.scaleToWidth(350)
    imageA.scaleToHeight(350)
    canvas.add(imageA)

 // Blending filter
    filter = new fabric.Image.filters.BlendImage({
 image:imageA,
 mode:'add',
 alpha:0.5
      });

 //Add the second image  
     fabric.Image.fromURL('my_image2.png',(imageB) => {
           imageB.scaleToHeight(100),
            imageB.scaleToWidth(100),
            canvas.add(imageB)
       }, {crossOrigin:''});

     imageA.filters.push(filter);
     imageA.applyFilters(canvas.renderAll.bind(canvas));
},{crossOrigin:''})

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Output

Image Clipping

A very popular effect used today is image clipping, or rather image cropping, which is done to remove parts of an image that we don’t want. With Fabric.js, we can achieve this by using the clipPath method.

First, we have to create our own clipPath using any Fabric.js object. Then, we’ll assign it to the clipPath property of the object we want to clip. Here, we’ll use a circle object:

const clipPath = new fabric.Circle({
 radius:150,
 top:200,
 left:250,
 // The originY and originX helps to center the image and the clipPath
    originY:"center",
 originX:"center"
})

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After that, we add it to the image that we want to clip using the filter method:

new fabric.Image.fromURL('my_image.png',(img) => {
  img.scaleToHeight(300)
  img.scaleToWidth(300)
 // positioning the image
  img.scale(o.5).set({top:50,left:100})
 // Clip Path
  clipPath = new fabric.Circle({
 radius:150,
 top:200,
 left:250,
 originY:"center",
 originX:"center"
    })
  canvas.add(img)
  canvas.clipPath = clipPath;
  });
canvas.renderAll();

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Output

Image Blurring

Like other image filters, the blur filter accepts objects because they can be adjusted. A practical example is changing the brightness of an image. You can apply other image filters without any additional configurations (like grayscale, invert, or sepia). Other image filters like brightness, pixelate, tint, and noise all operate in this way, too. However, the difference is that their values are not the same. The brightness filter's actual brightness level ranges from-1 (full black) to 1 (full white). The noise filter's value is between 0 and 1000. For the blur filter, the value ranges from 0 to 10.

Syntax

new fabric.Image.filters.Blur(object)

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fabric.Image.fromURL('my_image.png', (image) => {
      image.scaleToHeight(300)
       image.ScaleToWidth(300)

 // Creating the blur filter
 const filter = new fabric.Image.filters.Blur({
 blur:0.6
       })

 //push the filter instance to filters
        image.filter.push(filter)
         image.applyFilters()
         canvas.add(image)
},{crossOrigin: 'anonymous'});
canvas.renderAll();

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Output

Conclusion

In conclusion, Fabric.js gives us an awesome experience when working with Canvas. It also provides a lot of features, some of which we covered in this article. For full details on some of the Fabric.js objects, you can review its documentation here.