Inset-shadow on HTML5 canvas image

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I\'ve seen this question before but the answers given are for canvas images that have been drawn on via path however, i\'m drawing an image.

Is it possible to creat

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伪装坚强ぢ

2021-01-03 15:37
Inspired by K3N's answer, I've created Inset.js for this exact situation!

Inset.js

Only requires setting ctx.shadowInset = true;

For example: http://codepen.io/patlillis/pen/ryoWey
```
var ctx = canvas.getContext('2d');
var img = new Image;
img.onload = function() {
  ctx.shadowInset = true;
  ctx.shadowBlur = 25;
  ctx.shadowColor = "#000";
  ctx.drawImage(this, 0, 0);
}
img.src = "http://i.imgur.com/Qrfga2b.png";
```
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后悔当初

2021-01-03 15:39
Canvas will shadow where an image changes from opaque to transparent so, as K3N shows in his correct answer, you can turn the image inside out (opaque becomes transparent & visa-versa) so the shadows are drawn inside the circle.

If you know your circle's centerpoint and radius, you can use a stroked-path to create an inset circle shadow. Here's an example:
```
var canvas=document.getElementById("canvas");
var context=canvas.getContext("2d");
var cw=canvas.width;
var ch=canvas.height;

context.beginPath();
context.arc(cw/2,ch/2,75,0,Math.PI*2);
context.fillStyle='lightcyan';
context.fill();

context.globalCompositeOperation='source-atop';

context.shadowOffsetX = 500;
context.shadowOffsetY = 0;
context.shadowBlur = 15;
context.shadowColor = 'rgba(30,30,30,1)';

context.beginPath();
context.arc(cw/2-500,ch/2,75,0,Math.PI*2);
context.stroke();
context.stroke();
context.stroke();

context.globalCompositeOperation='source-over';
```
```
<canvas id="canvas" width=300 height=300></canvas>
```
If your path is irregular or hard to define mathematically, you can also use edge-path detection algorithms. One common edge-path algorithm is Marching Squares. Stackoverflow's K3N has coded a nice Marching Squares algorithm.
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余生分开走

2021-01-03 15:40

Inspired by markE's answer , I made my own version based on a png instead of vector-graphics.

Additionnaly, I made possible to choose the true alpha of the shadow (because the default shadow strength is a way too soft in my opinion)

var img = document.getElementById("myImage");
img.onload = function(){
   createInnerShadow(this,5,1);
}

function createInnerShadow(img,distance,alpha){
  
   //the size of the shadow depends on the size of the target,
   //then I will create extra "walls" around the picture to be sure
   //tbat the shadow will be correctly filled (with the same intensity everywhere)
   //(it's not obvious with this image, but it is when there is no space at all between the image and its border)
   var offset = 50 + distance;
   var hole = document.createElement("canvas");
   var holeContext = hole.getContext("2d");
   hole.width = img.width + offset*2;
   hole.height = img.height + offset*2;
   
    //first, I draw a big black rect
   holeContext.fillStyle = "#000000";
   holeContext.fillRect(0,0,hole.width,hole.height);
   
   //then I use the image to make an hole in it
   holeContext.globalCompositeOperation = "destination-out";
   holeContext.drawImage(img,offset,offset);
   
   //I create a new canvas that will contains the shadow of the hole only
   var shadow = document.createElement("canvas");
   var shadowContext = shadow.getContext("2d");
   shadow.width = img.width;
   shadow.height = img.height;
   shadowContext.filter = "drop-shadow(0px 0px "+distance+"px #000000 ) ";
   shadowContext.drawImage(hole,-offset,-offset);
   shadowContext.globalCompositeOperation = "destination-out";
   shadowContext.drawImage(hole,-offset,-offset);
  
   //now, because the default-shadow filter is really to soft, I normalize the shadow 
   //then I will be sure that the alpha-gradient of the shadow will start at "alpha" and end at 0
   normalizeAlphaShadow(shadow,alpha);
   
   
   //Finally, I create another canvas that will contain the image and the shadow over it
   var result = document.createElement("canvas");
   result.width = img.width;
   result.height = img.height;
   var context = result.getContext("2d");
   context.drawImage(img,0,0)
   context.drawImage(shadow,0,0);
   
   //and that's it !
   document.body.appendChild(result);
   
}

function normalizeAlphaShadow(canvas,alpha){
   var imageData = canvas.getContext("2d").getImageData(0,0,canvas.width,canvas.height);
   var pixelData = imageData.data;
   var i,len = pixelData.length;
   var max = 0;
   for(i=3;i<len;i+=4) if(pixelData[i]>max) max = pixelData[i];
   
   max = (255/max) * alpha;
   for(i=3;i<len;i+=4) pixelData[i] *= max;
   
   canvas.getContext("2d").putImageData(imageData,0,0)
   
}

<html>
<body>
<img id="myImage" src="data:image/png;base64,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" />
</body>
</html>

the jsfiddle is here : https://jsfiddle.net/jrekw5og/141/

0 讨论(0)

一整个雨季

2021-01-03 15:48

const width = 100 * devicePixelRatio;
const height = 100 * devicePixelRatio;

// original canvas
const c = document.getElementById('canvas');
c.width = 300 * devicePixelRatio;
c.height = 300 * devicePixelRatio;
c.style.width = '300px';
c.style.height = '300px';
const cctx = c.getContext('2d');
cctx.fillStyle = 'rgb(20,205,75)';
cctx.arc(150 * devicePixelRatio, 150 * devicePixelRatio, 50 * devicePixelRatio, 0, Math.PI * 2);
cctx.fill();

// temporary canvas
const canvas = document.createElement('canvas');
canvas.width = width;
canvas.height = height;
canvas.style.width = `${width / devicePixelRatio}px`;
canvas.style.height = `${height / devicePixelRatio}px`;
document.body.appendChild(canvas);
var ctx = canvas.getContext('2d');

// original object on temporary canvas
ctx.arc(50 * devicePixelRatio, 50 * devicePixelRatio, 50 * devicePixelRatio, 0, Math.PI * 2);
ctx.fill();

// shadow cutting
ctx.globalCompositeOperation = 'xor';
ctx.arc(50 * devicePixelRatio, 50 * devicePixelRatio, 50 * devicePixelRatio, 0, Math.PI * 2);
ctx.fill();

// shadow props
ctx.shadowBlur = 50;
ctx.shadowOffsetX = 0;
ctx.shadowOffsetY = -25;
ctx.shadowColor = '#000';
ctx.arc(50 * devicePixelRatio, 50 * devicePixelRatio, 50 * devicePixelRatio, 0, Math.PI * 2);
ctx.fill();

// shadow color
ctx.globalCompositeOperation = 'source-in';
ctx.fillStyle = 'blue';
ctx.fillRect(0, 0, canvas.width, canvas.height);

// object cutting
ctx.globalCompositeOperation = 'destination-in';
ctx.arc(50 * devicePixelRatio, 50 * devicePixelRatio, 50 * devicePixelRatio, 0, Math.PI * 2);
ctx.fill();

// shadow opacity
cctx.globalAlpha = .4

// inserting shadow into original canvas
cctx.drawImage(canvas, 200, 200);

Colored shadow /w opacity

0 讨论(0)

陌清茗

2021-01-03 15:55

Composition chain

Use a series of composite + draw operation to obtain inset shadow.

Note: the solution require exclusive access to the canvas element when created so either do this on an off-screen canvas and draw back to main, or if possible, plan secondary graphics to be drawn after this has been generated.

The needed steps:

Draw in original image
Invert alpha channel filling the canvas with a solid using xor composition
Define shadow and draw itself back in
Deactivate shadow and draw in original image (destination-atop)

Result

var ctx = c.getContext("2d"), img = new Image;
img.onload = function() {

  // draw in image to main canvas
  ctx.drawImage(this, 0, 0);

  // invert alpha channel
  ctx.globalCompositeOperation = "xor";
  ctx.fillRect(0, 0, c.width, c.height);

  // draw itself again using drop-shadow filter
  ctx.shadowBlur = 7*2;  // use double of what is in CSS filter (Chrome x4)
  ctx.shadowOffsetX = ctx.shadowOffsetY = 5;
  ctx.shadowColor = "#000";
  ctx.drawImage(c, 0, 0);

  // draw original image with background mixed on top
  ctx.globalCompositeOperation = "destination-atop";
  ctx.shadowColor = "transparent";                  // remove shadow !
  ctx.drawImage(this, 0, 0);
}
img.src = "http://i.imgur.com/Qrfga2b.png";

<canvas id=c height=300></canvas>

0 讨论(0)

Inset-shadow on HTML5 canvas image

Inset.js

Composition chain