"Dynamic Avatar Blur"
Bootstrap 3.3.0 Snippet by test9999

<link href="//maxcdn.bootstrapcdn.com/bootstrap/3.3.0/css/bootstrap.min.css" rel="stylesheet" id="bootstrap-css"> <script src="//maxcdn.bootstrapcdn.com/bootstrap/3.3.0/js/bootstrap.min.js"></script> <script src="//code.jquery.com/jquery-1.11.1.min.js"></script> <!------ Include the above in your HEAD tag ----------> <div class="container"> <div class="row"> <h1> Dynamically blurring avatar images using Canvas. </h1> </div> <div class="row"> <div class="col-sm-3"> <div class="card"> <canvas class="header-bg" width="250" height="70" id="header-blur"></canvas> <div class="avatar"> <img src="" alt="" /> </div> <div class="content"> <p>Web Developer <br> More description here</p> <p><button type="button" class="btn btn-default">Contact</button></p> </div> </div> </div> <div class="col-sm-3"> <div class="card"> <canvas class="header-bg" width="250" height="70" id="header-blur"></canvas> <div class="avatar"> <img src="" alt="" /> </div> <div class="content"> <p>Web Developer <br> More description here</p> <p><button type="button" class="btn btn-default">Contact</button></p> </div> </div> </div> <div class="col-sm-3"> <div class="card"> <canvas class="header-bg" width="250" height="70" id="header-blur"></canvas> <div class="avatar"> <img src="" alt="" /> </div> <div class="content"> <p>Web Developer <br> More description here</p> <p><button type="button" class="btn btn-default">Contact</button></p> </div> </div> </div> </div> </div> <img class="src-image" src="data:image/jpeg;base64,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"/> <img class="src-image" src="data:image/jpg;base64,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"/> <img class="src-image" src="data:image/jpeg;base64,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"/>
.src-image { display: none; } .card { overflow: hidden; position: relative; border: 1px solid #CCC; border-radius: 8px; text-align: center; padding: 0; background-color: #284c79; color: rgb(136, 172, 217); } .card .header-bg { /* This stretches the canvas across the entire hero unit */ position: absolute; top: 0; left: 0; width: 100%; height: 70px; border-bottom: 1px #FFF solid; /* This positions the canvas under the text */ z-index: 1; } .card .avatar { position: relative; margin-top: 15px; z-index: 100; } .card .avatar img { width: 100px; height: 100px; -webkit-border-radius: 50%; -moz-border-radius: 50%; border-radius: 50%; border: 5px solid rgba(0,0,30,0.8); }
/* This Snippet is using a modified Stack Blur js lib for blurring the header images. I could not use hosted images because Canvas cannot work with cross domain images. If you want to use hosted images make sure they are on the same domain. Have fun! */ /* StackBlur - a fast almost Gaussian Blur For Canvas Version: 0.5 Author: Mario Klingemann Contact: mario@quasimondo.com Website: http://www.quasimondo.com/StackBlurForCanvas Twitter: @quasimondo In case you find this class useful - especially in commercial projects - I am not totally unhappy for a small donation to my PayPal account mario@quasimondo.de Or support me on flattr: https://flattr.com/thing/72791/StackBlur-a-fast-almost-Gaussian-Blur-Effect-for-CanvasJavascript Copyright (c) 2010 Mario Klingemann Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. */ var mul_table = [ 512,512,456,512,328,456,335,512,405,328,271,456,388,335,292,512, 454,405,364,328,298,271,496,456,420,388,360,335,312,292,273,512, 482,454,428,405,383,364,345,328,312,298,284,271,259,496,475,456, 437,420,404,388,374,360,347,335,323,312,302,292,282,273,265,512, 497,482,468,454,441,428,417,405,394,383,373,364,354,345,337,328, 320,312,305,298,291,284,278,271,265,259,507,496,485,475,465,456, 446,437,428,420,412,404,396,388,381,374,367,360,354,347,341,335, 329,323,318,312,307,302,297,292,287,282,278,273,269,265,261,512, 505,497,489,482,475,468,461,454,447,441,435,428,422,417,411,405, 399,394,389,383,378,373,368,364,359,354,350,345,341,337,332,328, 324,320,316,312,309,305,301,298,294,291,287,284,281,278,274,271, 268,265,262,259,257,507,501,496,491,485,480,475,470,465,460,456, 451,446,442,437,433,428,424,420,416,412,408,404,400,396,392,388, 385,381,377,374,370,367,363,360,357,354,350,347,344,341,338,335, 332,329,326,323,320,318,315,312,310,307,304,302,299,297,294,292, 289,287,285,282,280,278,275,273,271,269,267,265,263,261,259]; var shg_table = [ 9, 11, 12, 13, 13, 14, 14, 15, 15, 15, 15, 16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24, 24 ]; function stackBlurCanvasRGBA( canvas, top_x, top_y, width, height, radius ) { if ( isNaN(radius) || radius < 1 ) return; radius |= 0; var context = canvas.getContext("2d"); var imageData; try { try { imageData = context.getImageData( top_x, top_y, width, height ); } catch(e) { // NOTE: this part is supposedly only needed if you want to work with local files // so it might be okay to remove the whole try/catch block and just use // imageData = context.getImageData( top_x, top_y, width, height ); try { netscape.security.PrivilegeManager.enablePrivilege("UniversalBrowserRead"); imageData = context.getImageData( top_x, top_y, width, height ); } catch(e) { alert("Cannot access local image"); throw new Error("unable to access local image data: " + e); return; } } } catch(e) { alert("Cannot access image"); throw new Error("unable to access image data: " + e); } var pixels = imageData.data; var x, y, i, p, yp, yi, yw, r_sum, g_sum, b_sum, a_sum, r_out_sum, g_out_sum, b_out_sum, a_out_sum, r_in_sum, g_in_sum, b_in_sum, a_in_sum, pr, pg, pb, pa, rbs; var div = radius + radius + 1; var w4 = width << 2; var widthMinus1 = width - 1; var heightMinus1 = height - 1; var radiusPlus1 = radius + 1; var sumFactor = radiusPlus1 * ( radiusPlus1 + 1 ) / 2; var stackStart = new BlurStack(); var stack = stackStart; for ( i = 1; i < div; i++ ) { stack = stack.next = new BlurStack(); if ( i == radiusPlus1 ) var stackEnd = stack; } stack.next = stackStart; var stackIn = null; var stackOut = null; yw = yi = 0; var mul_sum = mul_table[radius]; var shg_sum = shg_table[radius]; for ( y = 0; y < height; y++ ) { r_in_sum = g_in_sum = b_in_sum = a_in_sum = r_sum = g_sum = b_sum = a_sum = 0; r_out_sum = radiusPlus1 * ( pr = pixels[yi] ); g_out_sum = radiusPlus1 * ( pg = pixels[yi+1] ); b_out_sum = radiusPlus1 * ( pb = pixels[yi+2] ); a_out_sum = radiusPlus1 * ( pa = pixels[yi+3] ); r_sum += sumFactor * pr; g_sum += sumFactor * pg; b_sum += sumFactor * pb; a_sum += sumFactor * pa; stack = stackStart; for( i = 0; i < radiusPlus1; i++ ) { stack.r = pr; stack.g = pg; stack.b = pb; stack.a = pa; stack = stack.next; } for( i = 1; i < radiusPlus1; i++ ) { p = yi + (( widthMinus1 < i ? widthMinus1 : i ) << 2 ); r_sum += ( stack.r = ( pr = pixels[p])) * ( rbs = radiusPlus1 - i ); g_sum += ( stack.g = ( pg = pixels[p+1])) * rbs; b_sum += ( stack.b = ( pb = pixels[p+2])) * rbs; a_sum += ( stack.a = ( pa = pixels[p+3])) * rbs; r_in_sum += pr; g_in_sum += pg; b_in_sum += pb; a_in_sum += pa; stack = stack.next; } stackIn = stackStart; stackOut = stackEnd; for ( x = 0; x < width; x++ ) { pixels[yi+3] = pa = (a_sum * mul_sum) >> shg_sum; if ( pa != 0 ) { pa = 255 / pa; pixels[yi] = ((r_sum * mul_sum) >> shg_sum) * pa; pixels[yi+1] = ((g_sum * mul_sum) >> shg_sum) * pa; pixels[yi+2] = ((b_sum * mul_sum) >> shg_sum) * pa; } else { pixels[yi] = pixels[yi+1] = pixels[yi+2] = 0; } r_sum -= r_out_sum; g_sum -= g_out_sum; b_sum -= b_out_sum; a_sum -= a_out_sum; r_out_sum -= stackIn.r; g_out_sum -= stackIn.g; b_out_sum -= stackIn.b; a_out_sum -= stackIn.a; p = ( yw + ( ( p = x + radius + 1 ) < widthMinus1 ? p : widthMinus1 ) ) << 2; r_in_sum += ( stackIn.r = pixels[p]); g_in_sum += ( stackIn.g = pixels[p+1]); b_in_sum += ( stackIn.b = pixels[p+2]); a_in_sum += ( stackIn.a = pixels[p+3]); r_sum += r_in_sum; g_sum += g_in_sum; b_sum += b_in_sum; a_sum += a_in_sum; stackIn = stackIn.next; r_out_sum += ( pr = stackOut.r ); g_out_sum += ( pg = stackOut.g ); b_out_sum += ( pb = stackOut.b ); a_out_sum += ( pa = stackOut.a ); r_in_sum -= pr; g_in_sum -= pg; b_in_sum -= pb; a_in_sum -= pa; stackOut = stackOut.next; yi += 4; } yw += width; } for ( x = 0; x < width; x++ ) { g_in_sum = b_in_sum = a_in_sum = r_in_sum = g_sum = b_sum = a_sum = r_sum = 0; yi = x << 2; r_out_sum = radiusPlus1 * ( pr = pixels[yi]); g_out_sum = radiusPlus1 * ( pg = pixels[yi+1]); b_out_sum = radiusPlus1 * ( pb = pixels[yi+2]); a_out_sum = radiusPlus1 * ( pa = pixels[yi+3]); r_sum += sumFactor * pr; g_sum += sumFactor * pg; b_sum += sumFactor * pb; a_sum += sumFactor * pa; stack = stackStart; for( i = 0; i < radiusPlus1; i++ ) { stack.r = pr; stack.g = pg; stack.b = pb; stack.a = pa; stack = stack.next; } yp = width; for( i = 1; i <= radius; i++ ) { yi = ( yp + x ) << 2; r_sum += ( stack.r = ( pr = pixels[yi])) * ( rbs = radiusPlus1 - i ); g_sum += ( stack.g = ( pg = pixels[yi+1])) * rbs; b_sum += ( stack.b = ( pb = pixels[yi+2])) * rbs; a_sum += ( stack.a = ( pa = pixels[yi+3])) * rbs; r_in_sum += pr; g_in_sum += pg; b_in_sum += pb; a_in_sum += pa; stack = stack.next; if( i < heightMinus1 ) { yp += width; } } yi = x; stackIn = stackStart; stackOut = stackEnd; for ( y = 0; y < height; y++ ) { p = yi << 2; pixels[p+3] = pa = (a_sum * mul_sum) >> shg_sum; if ( pa > 0 ) { pa = 255 / pa; pixels[p] = ((r_sum * mul_sum) >> shg_sum ) * pa; pixels[p+1] = ((g_sum * mul_sum) >> shg_sum ) * pa; pixels[p+2] = ((b_sum * mul_sum) >> shg_sum ) * pa; } else { pixels[p] = pixels[p+1] = pixels[p+2] = 0; } r_sum -= r_out_sum; g_sum -= g_out_sum; b_sum -= b_out_sum; a_sum -= a_out_sum; r_out_sum -= stackIn.r; g_out_sum -= stackIn.g; b_out_sum -= stackIn.b; a_out_sum -= stackIn.a; p = ( x + (( ( p = y + radiusPlus1) < heightMinus1 ? p : heightMinus1 ) * width )) << 2; r_sum += ( r_in_sum += ( stackIn.r = pixels[p])); g_sum += ( g_in_sum += ( stackIn.g = pixels[p+1])); b_sum += ( b_in_sum += ( stackIn.b = pixels[p+2])); a_sum += ( a_in_sum += ( stackIn.a = pixels[p+3])); stackIn = stackIn.next; r_out_sum += ( pr = stackOut.r ); g_out_sum += ( pg = stackOut.g ); b_out_sum += ( pb = stackOut.b ); a_out_sum += ( pa = stackOut.a ); r_in_sum -= pr; g_in_sum -= pg; b_in_sum -= pb; a_in_sum -= pa; stackOut = stackOut.next; yi += width; } } context.putImageData( imageData, top_x, top_y ); } function BlurStack() { this.r = 0; this.g = 0; this.b = 0; this.a = 0; this.next = null; } $( document ).ready(function() { var BLUR_RADIUS = 40; var sourceImages = []; $('.src-image').each(function(){ sourceImages.push($(this).attr('src')); }); $('.avatar img').each(function(index){ $(this).attr('src', sourceImages[index] ); }); var drawBlur = function(canvas, image) { var w = canvas.width; var h = canvas.height; var canvasContext = canvas.getContext('2d'); canvasContext.drawImage(image, 0, 0, w, h); stackBlurCanvasRGBA(canvas, 0, 0, w, h, BLUR_RADIUS); }; $('.card canvas').each(function(index){ var canvas = $(this)[0]; var image = new Image(); image.src = sourceImages[index]; image.onload = function() { drawBlur(canvas, image); } }); });

Related: See More


Questions / Comments: