Correction [SobelFilter] + [CannyFilter] inspired by examples on `jsfeat` demo website

public_html/js/action-script.js

@@ -40,8 +40,7 @@
 
 	var Controller,
 		init,
-		featureZones,
+		zones = {feature: [], face: []},
-		faceZones,
 		track,
 		featureTracker,
 		faceTracker,
@@ -75,18 +74,18 @@ ControllerRememberer.fetch(function(loaded_data){
 		};
 
 		/* (2) Gestion de tracking.js */
-		featureZones = [];
+		zones.feature = [];
-		faceZones = [];
+		zones.face = [];
 
 		/* (3) Gestion du track de l'image */
 		track = {
 			trackFeatures: function(){
-				featureZones = [];
+				zones.feature = [];
 				featureTrackerTask = tracking.track(_CAN, featureTracker);
 			},
 
 			trackFace: function(){
-				faceZones = [];
+				zones.face = [];
 				faceTrackerTask = tracking.track(_CAN, faceTracker);
 			}
 		};
@@ -95,15 +94,19 @@ ControllerRememberer.fetch(function(loaded_data){
 		faceTracker    = new tracking.ObjectTracker(['face']);
 		featureTracker = new tracking.ObjectTracker(['eye', 'mouth']);
 
-		faceTracker.setStepSize(1.5);
+		faceTracker.setInitialScale(1.0);
-		featureTracker.setStepSize(1.5);
+		featureTracker.setInitialScale(1.0);
+		faceTracker.setStepSize(1.2);
+		featureTracker.setStepSize(1.2);
+		faceTracker.setEdgesDensity(0.1);
+		featureTracker.setEdgesDensity(0.1);
 
-		trackerCallback = function(zones, e){
+		trackerCallback = function(z, e){
 
-			zones.length = 0;
+			zones[z].length = 0;
 
 			e.data.forEach(function(rect){
-				zones.push({
+				zones[z].push({
 					x: rect.x / _CAN.width,
 					y: rect.y / _CAN.height,
 					w: rect.width / _CAN.width,
@@ -111,15 +114,18 @@ ControllerRememberer.fetch(function(loaded_data){
 				});
 			});
 
-			// On enregistre dans `featureZones` les featureZones trackées
+			// On enregistre dans `zones.feature` les zones.feature trackées
-			log('Recognition done', '[Tracking.js]');
+			if( zones[z].length > 0 )
+				log(z+' recognition done', '[Tracking.js]');
+			else
+				log(z+' recognition failed', '[Tracking.js]');
 
-			// On met à jour le rendu (affichage des featureZones)
+			// On met à jour le rendu (affichage des zones.feature)
 			process.apply(DOM.imageLoader);
 		}
 
-		faceTracker.on('track', function(e){    return trackerCallback.apply(this, [faceZones,    e]); });
+		faceTracker.on('track', function(e){    return trackerCallback.apply(this, ['face',    e]); });
-		featureTracker.on('track', function(e){ return trackerCallback.apply(this, [featureZones, e]); });
+		featureTracker.on('track', function(e){ return trackerCallback.apply(this, ['feature', e]); });
 
 	}
 
@@ -136,8 +142,8 @@ ControllerRememberer.fetch(function(loaded_data){
 		/* [0.0] Gestion du changement d'image
 		=========================================================*/
 		if( this.src != last ){
-			faceZones    = [];
+			zones.face    = [];
-			featureZones = [];
+			zones.feature = [];
 			exec         = false;
 			last         = this.src;
 		}
@@ -176,13 +182,16 @@ ControllerRememberer.fetch(function(loaded_data){
 			/* (1) Contraste */
 			filterManager.get('contrast').apply();
 
-			/* (2) Sobel */
+			/* (2) Contraste */
+			filterManager.get('grayscale').apply();
+
+			/* (3) Sobel */
 			filterManager.get('sobel').apply();
 
-			/* (3) Gaussian Filter */
+			/* (4) Gaussian Filter */
 			filterManager.get('gaussian').apply();
 
-			/* (4) Canny Filter */
+			/* (5) Canny Filter */
 			filterManager.get('canny').apply();
 		}
 
@@ -192,36 +201,28 @@ ControllerRememberer.fetch(function(loaded_data){
 
 			/* (1) On reporte chaque zone trackée sur le `<canvas>` */
 			var i, x, y, w, h;
-			for( i in featureZones ){
+			for( i in zones.feature ){
-				x = featureZones[i].x * _CAN.width;
+				x = zones.feature[i].x * _CAN.width;
-				y = featureZones[i].y * _CAN.height;
+				y = zones.feature[i].y * _CAN.height;
-				w = featureZones[i].w * _CAN.width;
+				w = zones.feature[i].w * _CAN.width;
-				h = featureZones[i].h * _CAN.height;
+				h = zones.feature[i].h * _CAN.height;
-				_CON.beginPath();
+
-					_CON.moveTo( x,   y   );
-					_CON.lineTo( x,   y+h );
-					_CON.lineTo( x+w, y+h );
-					_CON.lineTo( x+w, y   );
-					_CON.lineTo( x,   y   );
 				_CON.lineWidth = 5;
 				_CON.strokeStyle = '#f00';
-				_CON.stroke();
+
+				_CON.strokeRect(x, y, w, h);
 			}
 
-			for( i in faceZones ){
+			for( i in zones.face ){
-				x = faceZones[i].x * _CAN.width;
+				x = zones.face[i].x * _CAN.width;
-				y = faceZones[i].y * _CAN.height;
+				y = zones.face[i].y * _CAN.height;
-				w = faceZones[i].w * _CAN.width;
+				w = zones.face[i].w * _CAN.width;
-				h = faceZones[i].h * _CAN.height;
+				h = zones.face[i].h * _CAN.height;
-				_CON.beginPath();
+
-					_CON.moveTo( x,   y   );
-					_CON.lineTo( x,   y+h );
-					_CON.lineTo( x+w, y+h );
-					_CON.lineTo( x+w, y   );
-					_CON.lineTo( x,   y   );
 				_CON.lineWidth = 5;
 				_CON.strokeStyle = '#ff0';
-				_CON.stroke();
+
+				_CON.strokeRect(x, y, w, h);
 			}
 		}
 
@@ -245,6 +246,7 @@ ControllerRememberer.fetch(function(loaded_data){
 		/* (2) Ajout des filtres */
 		filterManager.add('resolution', reactiveResolution);
 		filterManager.add('contrast',   reactiveContrast);
+		filterManager.add('grayscale',  reactiveGrayscale);
 		filterManager.add('sobel',      reactiveSobel);
 		filterManager.add('gaussian',   reactiveGaussianBlur);
 		filterManager.add('canny',      reactiveCanny);
@@ -252,6 +254,7 @@ ControllerRememberer.fetch(function(loaded_data){
 		/* (3) Gestion des backups */
 		Controller.remember(filterManager.get('resolution'));
 		Controller.remember(filterManager.get('contrast'));
+		Controller.remember(filterManager.get('grayscale'));
 		Controller.remember(filterManager.get('sobel'));
 		Controller.remember(filterManager.get('canny'));
 		Controller.remember(filterManager.get('gaussian'));
@@ -261,16 +264,23 @@ ControllerRememberer.fetch(function(loaded_data){
 			Controller.add(track, 'trackFace');
 			Controller.add(track, 'trackFeatures');
 		Controller.addFolder('Image Resolution');
-			Controller.add(filterManager.get('resolution'), 'width', 0, 2).step(0.1);//listen();
+			Controller.add(filterManager.get('resolution'), 'width', 0, 2).step(0.1);
-			Controller.add(filterManager.get('resolution'), 'height', 0, 2).step(0.1);//listen();
+			Controller.add(filterManager.get('resolution'), 'height', 0, 2).step(0.1);
 		Controller.addFolder('Basic Image Processing');
-			Controller.add(filterManager.get('contrast'), 'contrast', 0, 100);//listen();
+			Controller.add(filterManager.get('contrast'), 'contrast', 0, 100);
+			Controller.add(filterManager.get('grayscale'), 'grayscale');
 		Controller.addFolder('Gaussian Blur');
-			Controller.add(filterManager.get('gaussian'), 'sigma', 0, 10).step(0.5);//listen();
+			Controller.add(filterManager.get('gaussian'), 'sigma', 0, 10).step(0.5);
-			Controller.add(filterManager.get('gaussian'), 'radius', 1, 11).step(1);//listen();
+			Controller.add(filterManager.get('gaussian'), 'radius', 1, 11).step(1);
-		Controller.addFolder('Convolution Filters');
+		Controller.addFolder('Sobel Filter');
-			Controller.add(filterManager.get('sobel'), 'sobelActive');//listen();
+			Controller.add(filterManager.get('sobel'), 'sobelActive');
-			Controller.add(filterManager.get('canny'), 'canny_radius');//listen();
+		Controller.addFolder('Canny Filter');
+			Controller.add(filterManager.get('canny'), 'active');
+			Controller.add(filterManager.get('canny'), 'radius', 0, 4).step(1);
+			Controller.add(filterManager.get('canny'), 'low_threshold', 1, 127).step(1);
+			Controller.add(filterManager.get('canny'), 'high_threshold', 1, 127).step(1);
+		Controller.addFolder('Process');
+			Controller.add({render: process}, 'render');
 
 
 		/* (5) Gestion du @PermanentStorage */

public_html/js/lib/min/reactive-filter.js

@@ -1,13 +1,16 @@
-var ReactiveFilter=function(a){this._manager={_process:function(){}};this._attr=a instanceof Object?a:{};for(var b in this._attr)this.__defineGetter__(b,function(a){return this._attr[a]}.bind(this,b)),this.__defineSetter__(b,function(a,b){return function(c){a._attr[b]=c;a._manager.process()}}(this,b));this.apply=function(){}},ReactiveFilterManager=function(a,b,d){this._target=a instanceof HTMLImageElement?a:null;if(!this._target)throw Error("Param 1 expected to be an HTMLImageElement (<img>), but "+
+var ReactiveFilter=function(a){this._manager={_process:function(){}};this._attr=a instanceof Object?a:{};for(var c in this._attr)this.__defineGetter__(c,function(a){return this._attr[a]}.bind(this,c)),this.__defineSetter__(c,function(a,b){return function(c){a._attr[b]=c;a._manager.process()}}(this,c));this.apply=function(){}},ReactiveFilterManager=function(a,c,d){this._target=a instanceof HTMLImageElement?a:null;if(!this._target)throw Error("Param 1 expected to be an HTMLImageElement (<img>), but "+
-a.constructor.name+" received");this._canvas=b instanceof HTMLCanvasElement?b:null;if(!this._canvas)throw Error("Param 2 expected to be an HTMLCanvasElement (<canvas>), but "+b.constructor.name+" received");this._context=this._canvas.getContext("2d");this._process=d instanceof Function?d:null;if(!this._process)throw Error("Param 3 expected to be a Function, but "+d.constructor.name+" received");this._filter={}};
+a.constructor.name+" received");this._canvas=c instanceof HTMLCanvasElement?c:null;if(!this._canvas)throw Error("Param 2 expected to be an HTMLCanvasElement (<canvas>), but "+c.constructor.name+" received");this._context=this._canvas.getContext("2d");this._process=d instanceof Function?d:null;if(!this._process)throw Error("Param 3 expected to be a Function, but "+d.constructor.name+" received");this._filter={}};
-ReactiveFilterManager.prototype.add=function(a,b){a="string"===typeof a?a:null;if(!a)throw Error("Param 1 expected to be a `string`, but "+a.constructor.name+" received");b=b instanceof ReactiveFilter?b:null;if(!b)throw Error("Param 2 expected to be a `ReactiveFilter`, but "+b.constructor.name+" received");if(null!=this._filter[a])return!0;this._filter[a]=b;b._manager=this};
+ReactiveFilterManager.prototype.add=function(a,c){a="string"===typeof a?a:null;if(!a)throw Error("Param 1 expected to be a `string`, but "+a.constructor.name+" received");c=c instanceof ReactiveFilter?c:null;if(!c)throw Error("Param 2 expected to be a `ReactiveFilter`, but "+c.constructor.name+" received");if(null!=this._filter[a])return!0;this._filter[a]=c;c._manager=this};
 ReactiveFilterManager.prototype.get=function(a){a="string"===typeof a?a:null;if(!a)throw Error("Param 1 expected to be a `string`, but "+a.constructor.name+" received");return null!=this._filter[a]?this._filter[a]:!1};ReactiveFilterManager.prototype.process=function(){this._process.bind(this._target)()};
-ConvolutionFilter=function(a,b,d,e){var c,f,h,g,p=parseInt(e.length/2),q=parseInt(e[0].length/2),l=d.slice(0),n,k,m,r,t,u;for(k=p;k<b;k++)for(n=q;n<a;n++){g=h=f=c=0;for(r=-p;r<=p;r++)for(m=-q;m<=q;m++)t=e[p+r][q+m],u=4*((k+r)*a+(n+m)),c+=l[u+0]*t,f+=l[u+1]*t,h+=l[u+2]*t,g+=l[u+3]*t;m=4*(k*a+n);d[m+0]=c;d[m+1]=f;d[m+2]=h;d[m+3]=g}};
+ConvolutionFilter=function(a,c,d,b){var e,g,f,h,q=parseInt(b.length/2),p=parseInt(b[0].length/2),l=d.slice(0),k,n,m,r,t,u;for(n=q;n<c;n++)for(k=p;k<a;k++){h=f=g=e=0;for(r=-q;r<=q;r++)for(m=-p;m<=p;m++)t=b[q+r][p+m],u=4*((n+r)*a+(k+m)),e+=l[u+0]*t,g+=l[u+1]*t,f+=l[u+2]*t,h+=l[u+3]*t;m=4*(n*a+k);d[m+0]=e;d[m+1]=g;d[m+2]=f;d[m+3]=h}};
-SobelFilter=function(a,b,d){var e=[[-1,0,1],[-2,0,2],[-1,0,1]],c=[[1,2,1],[0,0,0],[-1,-2,-1]],f=parseInt(e.length/2),h=parseInt(e[0].length/2),g=d.slice(0),p,q,l,n,k,m;for(q=f;q<b;q++)for(p=h;p<a;p++){k=0;for(n=-f;n<=f;n++)for(l=-h;l<=h;l++)m=4*((q+n)*a+(p+l)),k+=g[m+0]*(e[f+n][h+l]+c[f+n][h+l])/2;l=q*a+p;k=Math.abs(k);d[l]=k<<32|k<<16|k<<8|255}};var reactiveResolution=new ReactiveFilter({width:1,height:1});
+SobelFilter=function(a,c,d){var b=[[-1,0,1],[-2,0,2],[-1,0,1]],e=[[1,2,1],[0,0,0],[-1,-2,-1]],g=parseInt(b.length/2),f=parseInt(b[0].length/2),h=d.slice(0),q,p,l,k,n,m;for(p=g;p<c;p++)for(q=f;q<a;q++){n=0;for(k=-g;k<=g;k++)for(l=-f;l<=f;l++)m=4*((p+k)*a+(q+l)),n+=h[m+0]*(b[g+k][f+l]+e[g+k][f+l])/2;l=p*a+q;n=Math.abs(n);d[l]=(n<<32)+(n<<16)+(n<<8)|4278190080}};var reactiveResolution=new ReactiveFilter({width:1,height:1});
-reactiveResolution.apply=function(){if(this._manager instanceof ReactiveFilterManager){var a=this._manager._target,b=this._manager._canvas,d=this._manager._context;b.width=a.width*this.width;b.height=a.height*this.height;d.drawImage(a,0,0,b.width,b.height)}};var reactiveContrast=new ReactiveFilter({contrast:0});
+reactiveResolution.apply=function(){if(this._manager instanceof ReactiveFilterManager){var a=this._manager._target,c=this._manager._canvas,d=this._manager._context;c.width=a.width*this.width;c.height=a.height*this.height;d.drawImage(a,0,0,c.width,c.height)}};var reactiveContrast=new ReactiveFilter({contrast:0});
-reactiveContrast.apply=function(){if(this._manager instanceof ReactiveFilterManager){for(var a=this._manager._canvas,b=this._manager._context,a=b.getImageData(0,0,a.width,a.height),d=a.data,e=this.contrast;1<e;)e/=100;for(var e=127*(1-e),c=0,f=d.length;c<f;c++)0!=c%3&&(d[c]>=127+e&&(d[c]=255),d[c]<=127-e&&(d[c]=0));b.putImageData(a,0,0)}};var reactiveSobel=new ReactiveFilter({sobelActive:!1});
+reactiveContrast.apply=function(){if(this._manager instanceof ReactiveFilterManager){for(var a=this._manager._canvas,c=this._manager._context,a=c.getImageData(0,0,a.width,a.height),d=a.data,b=this.contrast;1<b;)b/=100;for(var b=127*(1-b),e=0,g=d.length;e<g;e++)0!=e%3&&(d[e]>=127+b&&(d[e]=255),d[e]<=127-b&&(d[e]=0));c.putImageData(a,0,0)}};var reactiveGrayscale=new ReactiveFilter({grayscale:!1});
-reactiveSobel.apply=function(){if(this._manager instanceof ReactiveFilterManager&&this.sobelActive){var a=this._manager._canvas,b=this._manager._context,d=b.getImageData(0,0,a.width,a.height),e=new Uint32Array(d.buffer);SobelFilter(a.width,a.height,e);b.putImageData(d,0,0)}};var reactiveGaussianBlur=new ReactiveFilter({sigma:0,radius:3});
+reactiveGrayscale.apply=function(){if(this._manager instanceof ReactiveFilterManager&&this.grayscale){for(var a=this._manager._canvas,c=this._manager._context,a=c.getImageData(0,0,a.width,a.height),d=a.data,b=this.contrast;1<b;)b/=100;for(var e=0,g=d.length;e<g;e++)0<e%4||(b=Math.round(.298*d[e]+.586*d[e+1]+.114*d[e+2]),d[e]=d[e+1]=d[e+2]=b);c.putImageData(a,0,0)}};var reactiveSobel=new ReactiveFilter({sobelActive:!1});
-reactiveGaussianBlur.apply=function(){if(this._manager instanceof ReactiveFilterManager){var a=this._manager._target,b=this._manager._canvas,d=this._manager._context,e=d.getImageData(0,0,b.width,b.height),c=new Uint32Array(e.buffer),b=document.createElement("canvas").getContext("2d").createImageData(b.width,b.height);b.data.set(e.data.slice(0));tBuf=new Uint32Array(b.buffer);for(var f=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),h=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),a=a.width*
+reactiveSobel.apply=function(){if(this._manager instanceof ReactiveFilterManager&&this.sobelActive){var a=this._manager._canvas,c=this._manager._context,d=c.getImageData(0,0,a.width,a.height);new Uint32Array(d.buffer);var b=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),e=new jsfeat.matrix_t(a.width,a.height,jsfeat.S32C2_t),g=new jsfeat.matrix_t(a.width,a.height,jsfeat.S32C1_t),f,h,q,p,l,k,n,m,r;jsfeat.imgproc.grayscale(d.data,a.width,a.height,b);jsfeat.imgproc.gaussian_blur(b,b,3);jsfeat.imgproc.sobel_derivatives(b,
-a.height,g;0<=--a;)g=c[a],f.data[a]=g<<24|g<<16|g<<8|g;jsfeat.imgproc.gaussian_blur(f,h,this.radius+1<<1,this.sigma);for(a=h.cols*h.rows;0<=--a;)g=h.data[a],tBuf[a]=g<<24|g<<16|g<<8|g;e.data.set(b.data);d.putImageData(b,0,0)}};var reactiveCanny=new ReactiveFilter({canny_radius:3});
+e);a=b.cols*b.rows;p=l=agx=agy=0;e=e.data;k=g.data;for(n=b.data;0<=--a;)f=e[a<<1],h=e[(a<<1)+1],k[a]=f*f+h*h;for(q=1;q<b.rows-1;++q)for(a=q*b.cols+1|0,g=1;g<b.cols-1;++g,++a)f=e[a<<1],h=e[(a<<1)+1],agx=(f^f>>31)-(f>>31)|0,agy=(h^h>>31)-(h>>31)|0,0<f&&(p=1)||(p=-1),0<h&&(l=b.cols)||(l=-b.cols),agx>agy?(m=k[a+p],r=k[a+p+-l],f=k[a-p],h=k[a-p+l],m=(agx-agy)*m+agy*r,f=(agx-agy)*f+agy*h,h=k[a]*agx,n[a]=h>=m&&h>f?agx&255:0):(m=k[a+-l],r=k[a+p+-l],f=k[a+l],h=k[a-p+l],m=(agy-agx)*m+agx*r,f=(agy-agx)*f+agx*
-reactiveCanny.apply=function(){if(this._manager instanceof ReactiveFilterManager){var a=this._manager._target,b=this._manager._canvas,d=this._manager._context,b=d.getImageData(0,0,b.width,b.height),e=new Uint32Array(b.buffer),a=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),c,f=e.length;c={};jsfeat.imgproc.canny(a,a,40,40);for(i=0;i<f;i++)c=a.data[i],c|=c<<16|c<<8,c={a:-16777216,b:(c&16711680)>>16,g:(c&65280)>>8,r:c&255},255===c.r&&255===c.g&&255===c.b?c={r:c.r,g:0,b:0,a:-16777216}:c.a=0,e[i]=
+h,h=k[a]*agy,n[a]=h>=m&&h>f?agy&255:0);data_u32=new Uint32Array(d.data.buffer);for(a=b.cols*b.rows;0<=--a;)data_u32[a]=-16777216|n[a]<<16|n[a]<<8|n[a];c.putImageData(d,0,0)}};var reactiveGaussianBlur=new ReactiveFilter({sigma:0,radius:3});
-c.a|c.b<<16|c.g<<8|c.r;d.putImageData(b,0,0)}};
+reactiveGaussianBlur.apply=function(){if(this._manager instanceof ReactiveFilterManager){for(var a=this._manager._target,c=this._manager._canvas,d=this._manager._context,c=d.getImageData(0,0,c.width,c.height),b=new Uint32Array(c.buffer),e=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),g=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),a=a.width*a.height,f;0<=--a;)f=b[a],e.data[a]=f<<24|f<<16|f<<8|f;jsfeat.imgproc.gaussian_blur(e,g,this.radius+1<<1,this.sigma);for(a=g.cols*g.rows;0<=--a;)f=
+g.data[a],b[a]=f<<24|f<<16|f<<8|f;d.putImageData(c,0,0)}};var reactiveCanny=new ReactiveFilter({active:!1,low_threshold:1,high_threshold:1,radius:3});
+reactiveCanny.apply=function(){if(this._manager instanceof ReactiveFilterManager&&this.active){var a=this._manager._canvas,c=this._manager._context,d=c.getImageData(0,0,a.width,a.height),b=new jsfeat.matrix_t(a.width,a.height,jsfeat.U8C1_t),e,g;jsfeat.imgproc.grayscale(d.data,a.width,a.height,b);jsfeat.imgproc.gaussian_blur(b,b,(this.radius|0)+1<<1,0);jsfeat.imgproc.canny(b,b,this.low_threshold|0,this.high_threshold|0);a=new Uint32Array(d.data.buffer);e=b.cols*b.rows;for(pix=0;0<=--e;)g=b.data[e],
+a[e]=-16777216|g<<16|g<<8|g;c.putImageData(d,0,0)}};

public_html/js/lib/reactive-filter.js

@@ -256,7 +256,7 @@ SobelFilter = function(width, height, buff32){
 			dIndex = (y*width + x); // indice destination
 			convolved = Math.abs(convolved);
 
-			buff32[dIndex] = convolved << 32 | convolved << 16 | convolved << 8 | 0xff;
+			buff32[dIndex] = (convolved << 32) + (convolved << 16) + (convolved << 8) | 0xff000000;
 			// buff32[dIndex+1] = Math.abs(convolved);
 			// buff32[dIndex+2] = Math.abs(convolved);
 			// buff32[dIndex+3] = 0xff;
@@ -344,6 +344,56 @@ reactiveContrast.apply = function(){
 };
 
 
+/************************************************
+****          Gestion du grayscale           ****
+************************************************/
+var reactiveGrayscale = new ReactiveFilter({ grayscale: false });
+reactiveGrayscale.apply = function(){
+	/* [1] Si pas de manager, on exit
+	=========================================================*/
+	if( !(this._manager instanceof ReactiveFilterManager) )
+		return;
+
+	if( !this.grayscale )
+		return;
+
+	/* [2] On recupère notre back-buffer (8Uint)
+	=========================================================*/
+	var o = {
+		image:   this._manager._target,
+		canvas:  this._manager._canvas,
+		context: this._manager._context
+	};
+
+	var imageData = o.context.getImageData(0, 0, o.canvas.width, o.canvas.height);
+	var buffer    = imageData.data;
+	// var buffer32 = new Uint32Array( imageData.imageData );
+
+
+	/* [3] On effectue notre modification
+	=========================================================*/
+	/* (1) On récupère la valeur du contraste */
+	var thresold = this.contrast;
+
+	while( thresold > 1 ) thresold /= 100;
+
+	thresold = (1-thresold) * 127;
+
+	/* (1) Gestion du contraste */
+	var g;
+	for( var i = 0, len = buffer.length ; i < len ; i++ ){
+		// si pas pixel rouge, on ne fait rien
+		if( i%4 > 0 ) continue;
+
+		// Grayscale
+		g = Math.round(0.298 * buffer[i] + 0.586 * buffer[i+1] + 0.114 * buffer[i+2]);
+		buffer[i] = buffer[i+1] = buffer[i+2] = g;
+	}
+
+	/* (2) Copie le résultat sur le `<canvas>` */
+	o.context.putImageData(imageData, 0, 0);
+};
+
 
 /************************************************
 ****            Gestion du Sobel             ****
@@ -368,41 +418,78 @@ reactiveSobel.apply = function(){
 	};
 
 	var imageData = o.context.getImageData(0, 0, o.canvas.width, o.canvas.height);
-	// var buffer    = imageData.data;
 	var buffer32  = new Uint32Array( imageData.buffer );
+	var img_u8    = new jsfeat.matrix_t(o.canvas.width, o.canvas.height, jsfeat.U8C1_t),
+		img_gxgy  = new jsfeat.matrix_t(o.canvas.width, o.canvas.height, jsfeat.S32C2_t),
+		img_mag   = new jsfeat.matrix_t(o.canvas.width, o.canvas.height, jsfeat.S32C1_t);
 
+	var i, gx, gy, x, y, dx, dy, gd, mag, id, a1, a2, b1, b2, A, B, point, data_32, a, p;
 
 	/* [3] On effectue notre modification
 	=========================================================*/
-	SobelFilter(o.canvas.width, o.canvas.height, buffer32);
+	jsfeat.imgproc.grayscale(imageData.data, o.canvas.width, o.canvas.height, img_u8);
-	/* (1) On calcule la convolution horizontale */
+	jsfeat.imgproc.gaussian_blur(img_u8, img_u8, 3);
-	// var Gx = buffer.slice(0);
+	jsfeat.imgproc.sobel_derivatives(img_u8, img_gxgy);
-	// ConvolutionFilter(o.canvas.width, o.canvas.height, Gx, [
+
-	// 	[-1, 0, 1],
+	i   = img_u8.cols*img_u8.rows;
-	// 	[-2, 0, 2],
+	gx  = gy = x = y = dx = dy = agx = agy = 0;
-	// 	[-1, 0, 1]
+	gd  = img_gxgy.data;
-	// ]);
+	mag = img_mag.data;
-	//
+	id  = img_u8.data;
-	// /* (2) On calcule la convolution verticale */
+
-	// var Gy = buffer.slice(0);
+	while( --i >= 0 ){
-	// ConvolutionFilter(o.canvas.width, o.canvas.height, Gy, [
+		gx     = gd[ i<<1 ];
-	// 	[1,   2,  1],
+		gy     = gd[ (i<<1) + 1 ];
-	// 	[0,   0,  0],
+		mag[i] = gx*gx + gy*gy;
-	// 	[-1, -2, -1]
+	}
-	// ]);
+
-	//
+	for( y = 1 ; y < img_u8.rows - 1 ; ++y ){
-	// /* (3) On mixe les 2 */
+		i = (y * img_u8.cols + 1) | 0;
-	// for( var i = 0, len = buffer.length ; i < len ; i += 4 ){
+
-	//
+		for( x = 1 ; x < img_u8.cols - 1 ; ++x, ++i){
-	// 	/* (4.1) On ajoute la convolution horizontale en rouge */
+
-	// 	buffer[i] = Math.abs(Gy[i]);
+			gx  = gd[ i<<1 ];
-	//
+			gy  = gd[ (i<<1) + 1 ];
-	// 	/* (4.2) On ajoute la convolution verticale en vert */
+			agx = ((gx ^ (gx >> 31)) - (gx >> 31))|0;
-	// 	buffer[i+1] = Math.abs(Gx[i+1]);
+			agy = ((gy ^ (gy >> 31)) - (gy >> 31))|0;
-	//
+
-	// 	buffer[i+2] = 0x00;
+			(gx > 0) && (dx = 1) || (dx = -1);
-	// 	buffer[i+3] = 0xff;
+
-	// }
+			(gy > 0) && (dy = img_u8.cols) || (dy = -img_u8.cols);
+
+			if( agx > agy ){
+
+				a1 = mag[i+dx];
+				a2 = mag[i+dx+(-dy)];
+				b1 = mag[i-dx];
+				b2 = mag[i-dx+dy];
+				A = (agx - agy)*a1 + agy*a2;
+				B = (agx - agy)*b1 + agy*b2;
+				point = mag[i] * agx;
+				id[i] = (point >= A && point > B) ? agx&0xff : 0x0;
+
+			} else  {
+				a1 = mag[i+(-dy)];
+				a2 = mag[i+dx+(-dy)];
+				b1 = mag[i+dy];
+				b2 = mag[i-dx+dy];
+				A = (agy - agx)*a1 + agx*a2;
+				B = (agy - agx)*b1 + agx*b2;
+				point = mag[i] * agy;
+
+				id[i] = (point >= A && point > B) ? agy&0xff : 0x0;
+
+			}
+		}
+	}
+
+	// render result back to canvas
+	data_u32 = new Uint32Array(imageData.data.buffer);
+	a = (0xff << 24);
+	p = 0;
+	i = img_u8.cols*img_u8.rows;
+	while( --i >= 0 )
+		data_u32[i] = a | (id[i] << 16) | (id[i] << 8) | id[i];
 
 
 	/* (2) Copie le résultat sur le `<canvas>` */
@@ -434,12 +521,6 @@ reactiveGaussianBlur.apply = function(){
 	// var buffer    = imageData.data;
 	var buffer32  = new Uint32Array( imageData.buffer );
 
-	/* (2) Create target */
-	var tCan = document.createElement('canvas');
-	var tmp  = tCan.getContext('2d').createImageData(o.canvas.width, o.canvas.height);
-	tmp.data.set( imageData.data.slice(0) );
-	tBuf = new Uint32Array( tmp.buffer );
-
 
 	/* [3] On effectue notre modification
 	=========================================================*/
@@ -460,25 +541,26 @@ reactiveGaussianBlur.apply = function(){
 	p_num = target.cols * target.rows;
 	while( --p_num >= 0 ){
 		pixel = target.data[p_num];
-		tBuf[p_num] = (pixel << 24) | (pixel << 16) | (pixel << 8) | pixel;
+		buffer32[p_num] = (pixel << 24) | (pixel << 16) | (pixel << 8) | pixel;
 	}
 
 	/* (2) Copie le résultat sur le `<canvas>` */
-	imageData.data.set( tmp.data );
+	o.context.putImageData(imageData, 0, 0);
-	o.context.putImageData(tmp, 0, 0);
 };
 
 
 /************************************************
 ****         Gestion du Canny Filter         ****
 ************************************************/
-var reactiveCanny = new ReactiveFilter({ canny_radius: 3 });
+var reactiveCanny = new ReactiveFilter({ active: false, low_threshold: 1, high_threshold: 1, radius: 3 });
 reactiveCanny.apply = function(){
 	/* [1] Si pas de manager, on exit
 	=========================================================*/
 	if( !(this._manager instanceof ReactiveFilterManager) )
 		return;
 
+	if( !this.active )
+		return;
 
 	/* [2] On recupère notre back-buffer (8Uint)
 	=========================================================*/
@@ -490,43 +572,28 @@ reactiveCanny.apply = function(){
 
 	/* (1) Get source */
 	var imageData = o.context.getImageData(0, 0, o.canvas.width, o.canvas.height);
-	// var buffer    = imageData.data;
+	var img_u8 = new jsfeat.matrix_t(o.canvas.width, o.canvas.height, jsfeat.U8C1_t);
-	var buffer32  = new Uint32Array( imageData.buffer );
-
 
+	var r, kernel_size, buffer32, a, i, p;
 	/* [3] On effectue notre modification
 	=========================================================*/
-	var matrix = new jsfeat.matrix_t(o.image.width, o.image.height, jsfeat.U8C1_t);
+	jsfeat.imgproc.grayscale(imageData.data, o.canvas.width, o.canvas.height, img_u8);
-	var pixel,
-		kernel_size    = (this.canny_radius + 1) << 1,
-		alpha          = (0x000000FF << 24),
-		p_num          = buffer32.length,
-		low_threshold  = 40,
-		high_threshold = 40,
-		x              = {},
-		cur;
 
-	// jsfeat.imgproc.gaussian_blur(matrix, matrix, kernel_size, 0);
+	r = this.radius|0;
+	kernel_size = (r+1) << 1;
+	jsfeat.imgproc.gaussian_blur(img_u8, img_u8, kernel_size, 0);
+	jsfeat.imgproc.canny(img_u8, img_u8, this.low_threshold|0, this.high_threshold|0);
 
-	jsfeat.imgproc.canny(matrix, matrix, low_threshold | 0, high_threshold | 0);
+	// render result back to canvas
-
+	buffer32 = new Uint32Array( imageData.data.buffer );
-	for( i = 0 ; i < p_num ; i++  ){
+	a = (0xff << 24);
-		pixel = matrix.data[i];
+	i = img_u8.cols*img_u8.rows, pix = 0;
-		cur = (pixel << 16) | (pixel << 8) | pixel;
+	while( --i >= 0 ){
-		x = {
+		p = img_u8.data[i];
-			a: alpha,
+		buffer32[i] = a | (p << 16) | (p << 8) | p;
-			b: (cur & 0x00FF0000) >> 16,
-			g: (cur & 0x0000FF00) >> 8,
-			r: cur & 0x000000FF
-		};
-		if( x.r === 255 && x.g === 255 && x.b === 255 ) // white
-			x = { r: x.r, g: 0, b: 0, a: (0x000000FF << 24) };
-		else
-			x.a = (0x00000000 << 24); // 'alpha' is set to min., i.e., '0'
-
-		buffer32[i] = x.a | (x.b << 16) | (x.g << 8) | x.r;
 	}
 
+
 	/* (2) Copie le résultat sur le `<canvas>` */
 	o.context.putImageData(imageData, 0, 0);
 

public_html/js/min/action-script.js

@@ -1,9 +1,10 @@
-var DOM={body:$("body"),canvas:$("canvas"),imageLoader:$("#image-loader")},_CAN=DOM.canvas;_CAN.width=_CAN.height=1E3;var _CON=_CAN.getContext("2d"),iL,filterManager,process=function(){},exec=!1,last,featureTrackerTask,faceTrackerTask,trackerCallback,Controller,init,featureZones,faceZones,track,featureTracker,faceTracker,initialized=!1,ControllerRememberer=new PermanentStorage;
+var DOM={body:$("body"),canvas:$("canvas"),imageLoader:$("#image-loader")},_CAN=DOM.canvas;_CAN.width=_CAN.height=1E3;var _CON=_CAN.getContext("2d"),iL,filterManager,process=function(){},exec=!1,last,featureTrackerTask,faceTrackerTask,trackerCallback,Controller,init,zones={feature:[],face:[]},track,featureTracker,faceTracker,initialized=!1,ControllerRememberer=new PermanentStorage;
-ControllerRememberer.fetch(function(f){log("Preset loaded.","[PermanentStorage]");Controller=new dat.GUI({load:JSON.parse(f),preset:"default"});init=function(){last=this.src="front/male/1.jpg";initialized=!0;Controller.addFolder("Source Picture");Controller.remember(this);Controller.add(this,"src",this._images).listen()};featureZones=[];faceZones=[];track={trackFeatures:function(){featureZones=[];featureTrackerTask=tracking.track(_CAN,featureTracker)},trackFace:function(){faceZones=[];faceTrackerTask=
+ControllerRememberer.fetch(function(f){log("Preset loaded.","[PermanentStorage]");Controller=new dat.GUI({load:JSON.parse(f),preset:"default"});init=function(){last=this.src="front/male/1.jpg";initialized=!0;Controller.addFolder("Source Picture");Controller.remember(this);Controller.add(this,"src",this._images).listen()};zones.feature=[];zones.face=[];track={trackFeatures:function(){zones.feature=[];featureTrackerTask=tracking.track(_CAN,featureTracker)},trackFace:function(){zones.face=[];faceTrackerTask=
-tracking.track(_CAN,faceTracker)}};faceTracker=new tracking.ObjectTracker(["face"]);featureTracker=new tracking.ObjectTracker(["eye","mouth"]);faceTracker.setStepSize(1.5);featureTracker.setStepSize(1.5);trackerCallback=function(a,c){a.length=0;c.data.forEach(function(b){a.push({x:b.x/_CAN.width,y:b.y/_CAN.height,w:b.width/_CAN.width,h:b.height/_CAN.height})});log("Recognition done","[Tracking.js]");process.apply(DOM.imageLoader)};faceTracker.on("track",function(a){return trackerCallback.apply(this,
+tracking.track(_CAN,faceTracker)}};faceTracker=new tracking.ObjectTracker(["face"]);featureTracker=new tracking.ObjectTracker(["eye","mouth"]);faceTracker.setInitialScale(1);featureTracker.setInitialScale(1);faceTracker.setStepSize(1.2);featureTracker.setStepSize(1.2);faceTracker.setEdgesDensity(.1);featureTracker.setEdgesDensity(.1);trackerCallback=function(a,c){zones[a].length=0;c.data.forEach(function(b){zones[a].push({x:b.x/_CAN.width,y:b.y/_CAN.height,w:b.width/_CAN.width,h:b.height/_CAN.height})});
-[faceZones,a])});featureTracker.on("track",function(a){return trackerCallback.apply(this,[featureZones,a])});process=function(){if(initialized&&this instanceof HTMLImageElement){console.time("PROCESS");this.src!=last&&(faceZones=[],featureZones=[],exec=!1,last=this.src);exec||(this.defaultWidth=this.width,this.defaultHeight=this.height,log("Image copied","[Canvas]"),exec=!0);_CON.clearRect(0,0,_CAN.width,_CAN.height);filterManager.get("resolution").apply();filterManager.get("contrast").apply();filterManager.get("sobel").apply();
+0<zones[a].length?log(a+" recognition done","[Tracking.js]"):log(a+" recognition failed","[Tracking.js]");process.apply(DOM.imageLoader)};faceTracker.on("track",function(a){return trackerCallback.apply(this,["face",a])});featureTracker.on("track",function(a){return trackerCallback.apply(this,["feature",a])});process=function(){if(initialized&&this instanceof HTMLImageElement){console.time("PROCESS");this.src!=last&&(zones.face=[],zones.feature=[],exec=!1,last=this.src);exec||(this.defaultWidth=this.width,
-filterManager.get("gaussian").apply();filterManager.get("canny").apply();var a,c,b,d,e;for(a in featureZones)c=featureZones[a].x*_CAN.width,b=featureZones[a].y*_CAN.height,d=featureZones[a].w*_CAN.width,e=featureZones[a].h*_CAN.height,_CON.beginPath(),_CON.moveTo(c,b),_CON.lineTo(c,b+e),_CON.lineTo(c+d,b+e),_CON.lineTo(c+d,b),_CON.lineTo(c,b),_CON.lineWidth=5,_CON.strokeStyle="#f00",_CON.stroke();for(a in faceZones)c=faceZones[a].x*_CAN.width,b=faceZones[a].y*_CAN.height,d=faceZones[a].w*_CAN.width,
+this.defaultHeight=this.height,log("Image copied","[Canvas]"),exec=!0);_CON.clearRect(0,0,_CAN.width,_CAN.height);filterManager.get("resolution").apply();filterManager.get("contrast").apply();filterManager.get("grayscale").apply();filterManager.get("sobel").apply();filterManager.get("gaussian").apply();filterManager.get("canny").apply();var a,c,b,d,e;for(a in zones.feature)c=zones.feature[a].x*_CAN.width,b=zones.feature[a].y*_CAN.height,d=zones.feature[a].w*_CAN.width,e=zones.feature[a].h*_CAN.height,
-e=faceZones[a].h*_CAN.height,_CON.beginPath(),_CON.moveTo(c,b),_CON.lineTo(c,b+e),_CON.lineTo(c+d,b+e),_CON.lineTo(c+d,b),_CON.lineTo(c,b),_CON.lineWidth=5,_CON.strokeStyle="#ff0",_CON.stroke();console.timeEnd("PROCESS")}};filterManager=new ReactiveFilterManager(DOM.imageLoader,_CAN,process);filterManager.add("resolution",reactiveResolution);filterManager.add("contrast",reactiveContrast);filterManager.add("sobel",reactiveSobel);filterManager.add("gaussian",reactiveGaussianBlur);filterManager.add("canny",
+_CON.lineWidth=5,_CON.strokeStyle="#f00",_CON.strokeRect(c,b,d,e);for(a in zones.face)c=zones.face[a].x*_CAN.width,b=zones.face[a].y*_CAN.height,d=zones.face[a].w*_CAN.width,e=zones.face[a].h*_CAN.height,_CON.lineWidth=5,_CON.strokeStyle="#ff0",_CON.strokeRect(c,b,d,e);console.timeEnd("PROCESS")}};filterManager=new ReactiveFilterManager(DOM.imageLoader,_CAN,process);filterManager.add("resolution",reactiveResolution);filterManager.add("contrast",reactiveContrast);filterManager.add("grayscale",reactiveGrayscale);
-reactiveCanny);Controller.remember(filterManager.get("resolution"));Controller.remember(filterManager.get("contrast"));Controller.remember(filterManager.get("sobel"));Controller.remember(filterManager.get("canny"));Controller.remember(filterManager.get("gaussian"));Controller.addFolder("Tracking.js");Controller.add(track,"trackFace");Controller.add(track,"trackFeatures");Controller.addFolder("Image Resolution");Controller.add(filterManager.get("resolution"),"width",0,2).step(.1);Controller.add(filterManager.get("resolution"),
+filterManager.add("sobel",reactiveSobel);filterManager.add("gaussian",reactiveGaussianBlur);filterManager.add("canny",reactiveCanny);Controller.remember(filterManager.get("resolution"));Controller.remember(filterManager.get("contrast"));Controller.remember(filterManager.get("grayscale"));Controller.remember(filterManager.get("sobel"));Controller.remember(filterManager.get("canny"));Controller.remember(filterManager.get("gaussian"));Controller.addFolder("Tracking.js");Controller.add(track,"trackFace");
-"height",0,2).step(.1);Controller.addFolder("Basic Image Processing");Controller.add(filterManager.get("contrast"),"contrast",0,100);Controller.addFolder("Gaussian Blur");Controller.add(filterManager.get("gaussian"),"sigma",0,10).step(.5);Controller.add(filterManager.get("gaussian"),"radius",1,11).step(1);Controller.addFolder("Convolution Filters");Controller.add(filterManager.get("sobel"),"sobelActive");Controller.add(filterManager.get("canny"),"canny_radius");Controller.__save_row.children[2].addEventListener("click",
+Controller.add(track,"trackFeatures");Controller.addFolder("Image Resolution");Controller.add(filterManager.get("resolution"),"width",0,2).step(.1);Controller.add(filterManager.get("resolution"),"height",0,2).step(.1);Controller.addFolder("Basic Image Processing");Controller.add(filterManager.get("contrast"),"contrast",0,100);Controller.add(filterManager.get("grayscale"),"grayscale");Controller.addFolder("Gaussian Blur");Controller.add(filterManager.get("gaussian"),"sigma",0,10).step(.5);Controller.add(filterManager.get("gaussian"),
+"radius",1,11).step(1);Controller.addFolder("Sobel Filter");Controller.add(filterManager.get("sobel"),"sobelActive");Controller.addFolder("Canny Filter");Controller.add(filterManager.get("canny"),"active");Controller.add(filterManager.get("canny"),"radius",0,4).step(1);Controller.add(filterManager.get("canny"),"low_threshold",1,127).step(1);Controller.add(filterManager.get("canny"),"high_threshold",1,127).step(1);Controller.addFolder("Process");Controller.add({render:process},"render");Controller.__save_row.children[2].addEventListener("click",
 function(){Controller.save();try{var a=JSON.stringify(Controller.getSaveObject());ControllerRememberer.store(a,function(){log("dat.GUI preset stored.","[PermanentStorage]");return!0})}catch(c){log("Corrupted data.","[PermanentStorage]")}},!1);iL=new ImageLoader(DOM.imageLoader,init,process);return!0});

public_html/permanent-storage/storage.json

@@ -1 +1 @@
-{"preset":"default","remembered":{"default":{"0":{"width":1,"height":1},"1":{"contrast":0},"2":{"sobelActive":false},"3":{"canny_radius":3},"4":{"sigma":6,"radius":3},"5":{"src":"front/male/1.jpg"}},"test1":{"0":{"width":1.8,"height":0.5},"1":{"contrast":55.27520549370516},"2":{"sobelActive":false},"3":{"canny_radius":3},"4":{"sigma":0,"radius":3},"5":{"src":"front/male/1.jpg"}}},"closed":false,"folders":{"Tracking.js":{"preset":"Default","closed":true,"folders":{}},"Image Resolution":{"preset":"Default","closed":true,"folders":{}},"Basic Image Processing":{"preset":"Default","closed":true,"folders":{}},"Gaussian Blur":{"preset":"Default","closed":true,"folders":{}},"Convolution Filters":{"preset":"Default","closed":true,"folders":{}},"Source Picture":{"preset":"Default","closed":true,"folders":{}}}}
+{"preset":"default","remembered":{"default":{"0":{"width":0.7000000000000001,"height":0.7000000000000001},"1":{"contrast":0},"2":{"grayscale":false},"3":{"sobelActive":false},"4":{"canny_radius":3},"5":{"sigma":9,"radius":3},"6":{"src":"front/male/1.jpg"}},"test1":{"0":{"width":1.8,"height":0.5},"1":{"contrast":55.27520549370516},"2":{"sobelActive":false},"3":{"canny_radius":3},"4":{"sigma":0,"radius":3},"5":{"src":"front/male/1.jpg"}}},"closed":false,"folders":{"Tracking.js":{"preset":"Default","closed":true,"folders":{}},"Image Resolution":{"preset":"Default","closed":true,"folders":{}},"Basic Image Processing":{"preset":"Default","closed":true,"folders":{}},"Gaussian Blur":{"preset":"Default","closed":true,"folders":{}},"Convolution Filters":{"preset":"Default","closed":true,"folders":{}},"Process":{"preset":"Default","closed":true,"folders":{}},"Source Picture":{"preset":"Default","closed":true,"folders":{}}}}