您需要先安装一个扩展,例如 篡改猴、Greasemonkey 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 暴力猴,之后才能安装此脚本。
您需要先安装一个扩展,例如 篡改猴 或 Userscripts ,之后才能安装此脚本。
您需要先安装一款用户脚本管理器扩展,例如 Tampermonkey,才能安装此脚本。
您需要先安装用户脚本管理器扩展后才能安装此脚本。
Apply SmartCrop (https://github.com/jwagner/smartcrop.js) to images on TweetDeck
// ==UserScript== // @name SmartCrop for TweetDeck // @namespace https://tweetdeck.twitter.com/ // @version 0.1 // @description Apply SmartCrop (https://github.com/jwagner/smartcrop.js) to images on TweetDeck // @author Flat // @match https://tweetdeck.twitter.com/ // @grant GM_xmlhttpRequest // @run-at document-end // ==/UserScript== /* jshint -W097 */ /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// /* Because there are no CDNs hosting smartcrop.js, I included library in the script. The original library is available here https://github.com/jwagner/smartcrop.js . */ /** smart-crop.js * A javascript library implementing content aware image cropping * * Copyright (C) 2014 Jonas Wagner * * 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. */ (function(){ "use strict"; function SmartCrop(options){ this.options = extend({}, SmartCrop.DEFAULTS, options); } SmartCrop.DEFAULTS = { width: 0, height: 0, aspect: 0, cropWidth: 0, cropHeight: 0, detailWeight: 0.2, skinColor: [0.78, 0.57, 0.44], skinBias: 0.01, skinBrightnessMin: 0.2, skinBrightnessMax: 1.0, skinThreshold: 0.8, skinWeight: 1.8, saturationBrightnessMin: 0.05, saturationBrightnessMax: 0.9, saturationThreshold: 0.4, saturationBias: 0.2, saturationWeight: 0.3, // step * minscale rounded down to the next power of two should be good scoreDownSample: 8, step: 8, scaleStep: 0.1, minScale: 0.9, maxScale: 1.0, edgeRadius: 0.4, edgeWeight: -20.0, outsideImportance: -0.5, ruleOfThirds: true, prescale: true, canvasFactory: null, debug: false }; SmartCrop.crop = function(image, options, callback){ if(options.aspect){ options.width = options.aspect; options.height = 1; } // work around images scaled in css by drawing them onto a canvas if(image.naturalWidth && (image.naturalWidth != image.width || image.naturalHeight != image.height)){ var c = new SmartCrop(options).canvas(image.naturalWidth, image.naturalHeight), cctx = c.getContext('2d'); c.width = image.naturalWidth; c.height = image.naturalHeight; cctx.drawImage(image, 0, 0); image = c; } var scale = 1, prescale = 1; if(options.width && options.height) { scale = min(image.width/options.width, image.height/options.height); options.cropWidth = ~~(options.width * scale); options.cropHeight = ~~(options.height * scale); // img = 100x100, width = 95x95, scale = 100/95, 1/scale > min // don't set minscale smaller than 1/scale // -> don't pick crops that need upscaling options.minScale = min(options.maxScale || SmartCrop.DEFAULTS.maxScale, max(1/scale, (options.minScale||SmartCrop.DEFAULTS.minScale))); } var smartCrop = new SmartCrop(options); if(options.width && options.height) { if(options.prescale !== false){ prescale = 1/scale/options.minScale; if(prescale < 1) { var prescaledCanvas = smartCrop.canvas(image.width*prescale, image.height*prescale), ctx = prescaledCanvas.getContext('2d'); ctx.drawImage(image, 0, 0, image.width, image.height, 0, 0, prescaledCanvas.width, prescaledCanvas.height); image = prescaledCanvas; smartCrop.options.cropWidth = ~~(options.cropWidth*prescale); smartCrop.options.cropHeight = ~~(options.cropHeight*prescale); } else { prescale = 1; } } } var result = smartCrop.analyse(image); for(var i = 0, i_len = result.crops.length; i < i_len; i++) { var crop = result.crops[i]; crop.x = ~~(crop.x/prescale); crop.y = ~~(crop.y/prescale); crop.width = ~~(crop.width/prescale); crop.height = ~~(crop.height/prescale); } callback(result); return result; }; // check if all the dependencies are there SmartCrop.isAvailable = function(options){ try { var s = new this(options), c = s.canvas(16, 16); return typeof c.getContext === 'function'; } catch(e){ return false; } }; SmartCrop.prototype = { canvas: function(w, h){ if(this.options.canvasFactory !== null){ return this.options.canvasFactory(w, h); } var c = document.createElement('canvas'); c.width = w; c.height = h; return c; }, edgeDetect: function(i, o){ var id = i.data, od = o.data, w = i.width, h = i.height; for(var y = 0; y < h; y++) { for(var x = 0; x < w; x++) { var p = (y*w+x)*4, lightness; if(x === 0 || x >= w-1 || y === 0 || y >= h-1){ lightness = sample(id, p); } else { lightness = sample(id, p)*4 - sample(id, p-w*4) - sample(id, p-4) - sample(id, p+4) - sample(id, p+w*4); } od[p+1] = lightness; } } }, skinDetect: function(i, o){ var id = i.data, od = o.data, w = i.width, h = i.height, options = this.options; for(var y = 0; y < h; y++) { for(var x = 0; x < w; x++) { var p = (y*w+x)*4, lightness = cie(id[p], id[p+1], id[p+2])/255, skin = this.skinColor(id[p], id[p+1], id[p+2]); if(skin > options.skinThreshold && lightness >= options.skinBrightnessMin && lightness <= options.skinBrightnessMax){ od[p] = (skin-options.skinThreshold)*(255/(1-options.skinThreshold)); } else { od[p] = 0; } } } }, saturationDetect: function(i, o){ var id = i.data, od = o.data, w = i.width, h = i.height, options = this.options; for(var y = 0; y < h; y++) { for(var x = 0; x < w; x++) { var p = (y*w+x)*4, lightness = cie(id[p], id[p+1], id[p+2])/255, sat = saturation(id[p], id[p+1], id[p+2]); if(sat > options.saturationThreshold && lightness >= options.saturationBrightnessMin && lightness <= options.saturationBrightnessMax){ od[p+2] = (sat-options.saturationThreshold)*(255/(1-options.saturationThreshold)); } else { od[p+2] = 0; } } } }, crops: function(image){ var crops = [], width = image.width, height = image.height, options = this.options, minDimension = min(width, height), cropWidth = options.cropWidth || minDimension, cropHeight = options.cropHeight || minDimension; for(var scale = options.maxScale; scale >= options.minScale; scale -= options.scaleStep){ for(var y = 0; y+cropHeight*scale <= height; y+=options.step) { for(var x = 0; x+cropWidth*scale <= width; x+=options.step) { crops.push({ x: x, y: y, width: cropWidth*scale, height: cropHeight*scale }); } } } return crops; }, score: function(output, crop){ var score = { detail: 0, saturation: 0, skin: 0, total: 0 }, options = this.options, od = output.data, downSample = options.scoreDownSample, invDownSample = 1/downSample, outputHeightDownSample = output.height*downSample, outputWidthDownSample = output.width*downSample, outputWidth = output.width; for(var y = 0; y < outputHeightDownSample; y+=downSample) { for(var x = 0; x < outputWidthDownSample; x+=downSample) { var p = (~~(y*invDownSample)*outputWidth+~~(x*invDownSample))*4, importance = this.importance(crop, x, y), detail = od[p+1]/255; score.skin += od[p]/255*(detail+options.skinBias)*importance; score.detail += detail*importance; score.saturation += od[p+2]/255*(detail+options.saturationBias)*importance; } } score.total = (score.detail*options.detailWeight + score.skin*options.skinWeight + score.saturation*options.saturationWeight)/crop.width/crop.height; return score; }, importance: function(crop, x, y){ var options = this.options; if (crop.x > x || x >= crop.x+crop.width || crop.y > y || y >= crop.y+crop.height) return options.outsideImportance; x = (x-crop.x)/crop.width; y = (y-crop.y)/crop.height; var px = abs(0.5-x)*2, py = abs(0.5-y)*2, // distance from edge dx = Math.max(px-1.0+options.edgeRadius, 0), dy = Math.max(py-1.0+options.edgeRadius, 0), d = (dx*dx+dy*dy)*options.edgeWeight; var s = 1.41-sqrt(px*px+py*py); if(options.ruleOfThirds){ s += (Math.max(0, s+d+0.5)*1.2)*(thirds(px)+thirds(py)); } return s+d; }, skinColor: function(r, g, b){ var mag = sqrt(r*r+g*g+b*b), options = this.options, rd = (r/mag-options.skinColor[0]), gd = (g/mag-options.skinColor[1]), bd = (b/mag-options.skinColor[2]), d = sqrt(rd*rd+gd*gd+bd*bd); return 1-d; }, analyse: function(image){ var result = {}, options = this.options, canvas = this.canvas(image.width, image.height), ctx = canvas.getContext('2d'); ctx.drawImage(image, 0, 0); var input = ctx.getImageData(0, 0, canvas.width, canvas.height), output = ctx.getImageData(0, 0, canvas.width, canvas.height); this.edgeDetect(input, output); this.skinDetect(input, output); this.saturationDetect(input, output); var scoreCanvas = this.canvas(ceil(image.width/options.scoreDownSample), ceil(image.height/options.scoreDownSample)), scoreCtx = scoreCanvas.getContext('2d'); ctx.putImageData(output, 0, 0); scoreCtx.drawImage(canvas, 0, 0, canvas.width, canvas.height, 0, 0, scoreCanvas.width, scoreCanvas.height); var scoreOutput = scoreCtx.getImageData(0, 0, scoreCanvas.width, scoreCanvas.height); var topScore = -Infinity, topCrop = null, crops = this.crops(image); for(var i = 0, i_len = crops.length; i < i_len; i++) { var crop = crops[i]; crop.score = this.score(scoreOutput, crop); if(crop.score.total > topScore){ topCrop = crop; topScore = crop.score.total; } } result.crops = crops; result.topCrop = topCrop; if(options.debug && topCrop){ ctx.fillStyle = 'rgba(255, 0, 0, 0.1)'; ctx.fillRect(topCrop.x, topCrop.y, topCrop.width, topCrop.height); for (var y = 0; y < output.height; y++) { for (var x = 0; x < output.width; x++) { var p = (y * output.width + x) * 4; var importance = this.importance(topCrop, x, y); if (importance > 0) { output.data[p + 1] += importance * 32; } if (importance < 0) { output.data[p] += importance * -64; } output.data[p + 3] = 255; } } ctx.putImageData(output, 0, 0); ctx.strokeStyle = 'rgba(255, 0, 0, 0.8)'; ctx.strokeRect(topCrop.x, topCrop.y, topCrop.width, topCrop.height); result.debugCanvas = canvas; } return result; } }; // aliases and helpers var min = Math.min, max = Math.max, abs = Math.abs, ceil = Math.ceil, sqrt = Math.sqrt; function extend(o){ for(var i = 1, i_len = arguments.length; i < i_len; i++) { var arg = arguments[i]; if(arg){ for(var name in arg){ o[name] = arg[name]; } } } return o; } // gets value in the range of [0, 1] where 0 is the center of the pictures // returns weight of rule of thirds [0, 1] function thirds(x){ x = ((x-(1/3)+1.0)%2.0*0.5-0.5)*16; return Math.max(1.0-x*x, 0.0); } function cie(r, g, b){ return 0.5126*b + 0.7152*g + 0.0722*r; } function sample(id, p) { return cie(id[p], id[p+1], id[p+2]); } function saturation(r, g, b){ var maximum = max(r/255, g/255, b/255), minumum = min(r/255, g/255, b/255); if(maximum === minumum){ return 0; } var l = (maximum + minumum) / 2, d = maximum-minumum; return l > 0.5 ? d/(2-maximum-minumum) : d/(maximum+minumum); } // amd if (typeof define !== 'undefined' && define.amd) define(function(){return SmartCrop;}); //common js if (typeof exports !== 'undefined') exports.SmartCrop = SmartCrop; // browser else if (typeof navigator !== 'undefined') window.SmartCrop = SmartCrop; // nodejs if (typeof module !== 'undefined') { module.exports = SmartCrop; } })(); /////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////// (function($, SmartCrop) { // 設定 var debug = false; // 適用 (function applyCrop() { var $elements = $('.js-media-image-link:not([data-smartcrop])'); $elements.each(function() { var $e = $(this); // 多重処理防止 $e.attr('data-smartcrop', 'pending'); // 画像のURL取得 var imgUrl = $e.css('background-image').slice(5, -2); // 画像を取得 // twimgがCORSに対応していればGreaseMonkeyの機能を使わずに済んだんだけどなー GM_xmlhttpRequest({ method: 'GET', url: imgUrl, responseType: 'blob', onload: function(data) { // 画像読み込み // CSPの関係でBlobURIスキームは使えない var reader = new FileReader(); reader.onloadend = function() { var img = new Image(); img.onload = function() { // クロップ SmartCrop.crop(img, { width: $e.width(), height: $e.height(), debug: debug, }, function(result) { var crop = result.topCrop; /* // background-position、background-sizeを使用する方法 // なんかうまくいかないのでやめた // 本当はこっちの方法のほうが読み込み早いと思う $e.css({ 'background-position': 'left ' + -crop.x + 'px top ' + -crop.y + 'px', 'background-size': (img.width / crop.width * 100) + '% ' + (img.height / crop.height * 100) + '%', }); /*/ // 自力で切り出してbackground-imageに指定する方法 // 多分遅いし非効率的 var canvas = document.createElement('canvas'); canvas.width = crop.width; canvas.height = crop.height; canvas.getContext('2d').drawImage(img, -crop.x, -crop.y); $e.css('background-image', 'url("' + canvas.toDataURL('image/png') + '")'); //*/ // 一応処理が終了したことを示しておく、使わないけど $e.attr('data-smartcrop', 'completed'); if (debug) { // ちなみに並び順は逆になる $e.parents('.js-media').after($(result.debugCanvas).css('width', $e.width())); } }); }; img.src = reader.result; }; reader.readAsDataURL(data.response); } }); }); // もっと良い方法でループを回すべきかもしれない setTimeout(applyCrop, 1000); })(); })(unsafeWindow.jQuery, window.SmartCrop || this.window.SmartCrop);