Fabric.js is a JavaScript library that is used to work with canvas. The canvas image is one of the class of fabric.js that is used to create image instances. The canvas image means the Image is movable and can be stretched according to requirement. The strokeDashOffset property is used to set the stroke offset of a canvas image
Approach: First import the fabric.js library. After importing the library, create a canvas block in the body tag which will contain the image. After this, initialize an instance of Canvas and image class provided by Fabric.JS and use the strokeDashOffset property to set stroke offset of a canvas image. After this render the image on the canvas.
Syntax:
fabric.Image(image, {
strokeDashOffset : number
});
Parameters: This function takes a single parameter as mentioned above and described below:
- strokeDashOffset : This parameter takes a number value to set stroke offset of the canvas image.
Example: This example uses FabricJS to set the strokeDashOffset  property of the canvas image as shown in the below example:
HTML
<!DOCTYPE html> <html>   <head>     <!-- Adding the FabricJS library -->    <script src=     </script>   </head>     <body>     <h1 style="color: green;">       neveropen     </h1>       <b>       Fabric.js Image strokeDashOffset Property     </b>       <canvas id="canvas" width="400" height="300"            style="border:2px solid #000000">     </canvas>       <img src=       width="100" height="100" id="my-image"      style="display: none;">     <br>       <script>         // Creating the instance of canvas object       var canvas = new fabric.Canvas("canvas");         // Getting the image       var img = document.getElementById('my-image');         // Creating the image instance       var neveropen = new fabric.Image(img, {         stroke:"green",         strokeMiterLimit : 100,         strokeDashOffset :10,         strokeDashArray: [10],         strokeWidth:3       });         canvas.add(neveropen);       canvas.centerObject(neveropen);     </script>   </body>   </html> |
Output:
