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web/WebMvc/wwwroot/js/face/ccv.js 14.8 KB
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5c8a582c
 
赖素文 authored 
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var ccv = {
	pre : function (image) {
		if (image.tagName.toLowerCase() == "img") {
			var canvas = document.createElement("canvas");
			document.body.appendChild(image);
			canvas.width = image.offsetWidth;
			canvas.style.width = image.offsetWidth.toString() + "px";
			canvas.height = image.offsetHeight;
			canvas.style.height = image.offsetHeight.toString() + "px";
			document.body.removeChild(image);
			var ctx = canvas.getContext("2d");
			ctx.drawImage(image, 0, 0);
			return canvas;
		}
		return image;
	},

	grayscale : function (canvas) {
		var ctx = canvas.getContext("2d");
		var imageData = ctx.getImageData(0, 0, canvas.width, canvas.height);
		var data = imageData.data;
		var pix1, pix2, pix = canvas.width * canvas.height * 4;
		while (pix > 0)
			data[pix -= 4] = data[pix1 = pix + 1] = data[pix2 = pix + 2] = (data[pix] * 0.3 + data[pix1] * 0.59 + data[pix2] * 0.11);
		ctx.putImageData(imageData, 0, 0);
		return canvas;
	},

	__get_named_arguments : function (params, names) {
		if (params.length > 1) {
			var new_params = {};
			for (var i = 0; i < names.length; i++)
				new_params[names[i]] = params[i];
			return new_params;
		}
		return params[0];
	},

	__worker_scripts : {},

	spawn : function (pre, script, params, post, complete, worker_num) {
		var params = ccv.__get_named_arguments(arguments, ["pre", "script", "params", "post", "complete", "worker_num"]);
		var worker = new Worker("ccv.js");
		worker.onmessage = function (event) {
			params.complete(params.post((typeof event.data == "string") ? JSON.parse(event.data) : event.data));
		};
		var msg = { "data" : params.pre(),
					"script" : params.script,
					"params" : params.params,
					"id" : 0,
					"worker_num" : params.worker_num };
		try {
			worker.postMessage(msg);
		} catch (e) {
			worker.postMessage(JSON.stringify(msg));
		}
		return worker;
	},

	array_group : function (seq, gfunc) {
		var i, j;
		var node = new Array(seq.length);
		for (i = 0; i < seq.length; i++)
			node[i] = {"parent" : -1,
					   "element" : seq[i],
					   "rank" : 0};
		for (i = 0; i < seq.length; i++)
		{
			if (!node[i].element)
				continue;
			var root = i;
			while (node[root].parent != -1)
				root = node[root].parent;
			for (j = 0; j < seq.length; j++)
			{
				if( i != j && node[j].element && gfunc(node[i].element, node[j].element))
				{
					var root2 = j;

					while (node[root2].parent != -1)
						root2 = node[root2].parent;

					if(root2 != root)
					{
						if(node[root].rank > node[root2].rank)
							node[root2].parent = root;
						else
						{
							node[root].parent = root2;
							if (node[root].rank == node[root2].rank)
							node[root2].rank++;
							root = root2;
						}

						/* compress path from node2 to the root: */
						var temp, node2 = j;
						while (node[node2].parent != -1)
						{
							temp = node2;
							node2 = node[node2].parent;
							node[temp].parent = root;
						}

						/* compress path from node to the root: */
						node2 = i;
						while (node[node2].parent != -1)
						{
							temp = node2;
							node2 = node[node2].parent;
							node[temp].parent = root;
						}
					}
				}
			}
		}
		var idx = new Array(seq.length);
		var class_idx = 0;
		for(i = 0; i < seq.length; i++)
		{
			j = -1;
			var node1 = i;
			if(node[node1].element)
			{
				while (node[node1].parent != -1)
					node1 = node[node1].parent;
				if(node[node1].rank >= 0)
					node[node1].rank = ~class_idx++;
				j = ~node[node1].rank;
			}
			idx[i] = j;
		}
		return {"index" : idx, "cat" : class_idx};
	},

	detect_objects : function (canvas, cascade, interval, min_neighbors, complete, worker_num, setup) {
		var params = ccv.__get_named_arguments(arguments, ["canvas", "cascade", "interval", "min_neighbors", "complete", "worker_num", "setup"]);
		if (!params.setup) {
			var cascade = params.cascade;
			var scale = Math.pow(2, 1 / (params.interval + 1));
			var next = params.interval + 1;
			var scale_upto = Math.floor(Math.log(Math.min(params.canvas.width / cascade.width, params.canvas.height / cascade.height)) / Math.log(scale));
		}
		var pre = function () {
			var pyr = new Array((scale_upto + next * 2) * 4);
			var ret = new Array((scale_upto + next * 2) * 4);
			pyr[0] = params.canvas;
			ret[0] = { "width" : pyr[0].width,
					   "height" : pyr[0].height,
					   "data" : pyr[0].getContext("2d").getImageData(0, 0, pyr[0].width, pyr[0].height).data };
			var i;
			for (i = 1; i <= params.interval; i++) {
				pyr[i * 4] = document.createElement("canvas");
				pyr[i * 4].width = Math.floor(pyr[0].width / Math.pow(scale, i));
				pyr[i * 4].height = Math.floor(pyr[0].height / Math.pow(scale, i));
				pyr[i * 4].getContext("2d").drawImage(pyr[0], 0, 0, pyr[0].width, pyr[0].height, 0, 0, pyr[i * 4].width, pyr[i * 4].height);
				ret[i * 4] = { "width" : pyr[i * 4].width,
							   "height" : pyr[i * 4].height,
							   "data" : pyr[i * 4].getContext("2d").getImageData(0, 0, pyr[i * 4].width, pyr[i * 4].height).data };
			}
			for (i = next; i < scale_upto + next * 2; i++) {
				pyr[i * 4] = document.createElement("canvas");
				pyr[i * 4].width = Math.floor(pyr[i * 4 - next * 4].width / 2);
				pyr[i * 4].height = Math.floor(pyr[i * 4 - next * 4].height / 2);
				pyr[i * 4].getContext("2d").drawImage(pyr[i * 4 - next * 4], 0, 0, pyr[i * 4 - next * 4].width, pyr[i * 4 - next * 4].height, 0, 0, pyr[i * 4].width, pyr[i * 4].height);
				ret[i * 4] = { "width" : pyr[i * 4].width,
							   "height" : pyr[i * 4].height,
							   "data" : pyr[i * 4].getContext("2d").getImageData(0, 0, pyr[i * 4].width, pyr[i * 4].height).data };
			}
			for (i = next * 2; i < scale_upto + next * 2; i++) {
				pyr[i * 4 + 1] = document.createElement("canvas");
				pyr[i * 4 + 1].width = Math.floor(pyr[i * 4 - next * 4].width / 2);
				pyr[i * 4 + 1].height = Math.floor(pyr[i * 4 - next * 4].height / 2);
				pyr[i * 4 + 1].getContext("2d").drawImage(pyr[i * 4 - next * 4], 1, 0, pyr[i * 4 - next * 4].width - 1, pyr[i * 4 - next * 4].height, 0, 0, pyr[i * 4 + 1].width - 2, pyr[i * 4 + 1].height);
				ret[i * 4 + 1] = { "width" : pyr[i * 4 + 1].width,
								   "height" : pyr[i * 4 + 1].height,
								   "data" : pyr[i * 4 + 1].getContext("2d").getImageData(0, 0, pyr[i * 4 + 1].width, pyr[i * 4 + 1].height).data };
				pyr[i * 4 + 2] = document.createElement("canvas");
				pyr[i * 4 + 2].width = Math.floor(pyr[i * 4 - next * 4].width / 2);
				pyr[i * 4 + 2].height = Math.floor(pyr[i * 4 - next * 4].height / 2);
				pyr[i * 4 + 2].getContext("2d").drawImage(pyr[i * 4 - next * 4], 0, 1, pyr[i * 4 - next * 4].width, pyr[i * 4 - next * 4].height - 1, 0, 0, pyr[i * 4 + 2].width, pyr[i * 4 + 2].height - 2);
				ret[i * 4 + 2] = { "width" : pyr[i * 4 + 2].width,
								   "height" : pyr[i * 4 + 2].height,
								   "data" : pyr[i * 4 + 2].getContext("2d").getImageData(0, 0, pyr[i * 4 + 2].width, pyr[i * 4 + 2].height).data };
				pyr[i * 4 + 3] = document.createElement("canvas");
				pyr[i * 4 + 3].width = Math.floor(pyr[i * 4 - next * 4].width / 2);
				pyr[i * 4 + 3].height = Math.floor(pyr[i * 4 - next * 4].height / 2);
				pyr[i * 4 + 3].getContext("2d").drawImage(pyr[i * 4 - next * 4], 1, 1, pyr[i * 4 - next * 4].width - 1, pyr[i * 4 - next * 4].height - 1, 0, 0, pyr[i * 4 + 3].width - 2, pyr[i * 4 + 3].height - 2);
				ret[i * 4 + 3] = { "width" : pyr[i * 4 + 3].width,
								   "height" : pyr[i * 4 + 3].height,
								   "data" : pyr[i * 4 + 3].getContext("2d").getImageData(0, 0, pyr[i * 4 + 3].width, pyr[i * 4 + 3].height).data };
			}
			for (i = 0; i < cascade.stage_classifier.length; i++)
				cascade.stage_classifier[i].orig_feature = cascade.stage_classifier[i].feature;
			return ret;
		};

		var work = function (pyr, params, id, worker_num) {
			var cascade = params.cascade;
			var scale = Math.pow(2, 1 / (params.interval + 1));
			var next = params.interval + 1;
			var scale_upto = Math.floor(Math.log(Math.min(pyr[0].width / cascade.width, pyr[0].height / cascade.height)) / Math.log(scale));
			var i, j, k, x, y, q;
			var scale_x = 1, scale_y = 1;
			var dx = [0, 1, 0, 1];
			var dy = [0, 0, 1, 1];
			var seq = [];
			for (i = 0; i < scale_upto; i++) {
				var qw = pyr[i * 4 + next * 8].width - Math.floor(cascade.width / 4);
				var qh = pyr[i * 4 + next * 8].height - Math.floor(cascade.height / 4);
				var step = [pyr[i * 4].width * 4, pyr[i * 4 + next * 4].width * 4, pyr[i * 4 + next * 8].width * 4];
				var paddings = [pyr[i * 4].width * 16 - qw * 16,
								pyr[i * 4 + next * 4].width * 8 - qw * 8,
								pyr[i * 4 + next * 8].width * 4 - qw * 4];
				for (j = 0; j < cascade.stage_classifier.length; j++) {
					var orig_feature = cascade.stage_classifier[j].orig_feature;
					var feature = cascade.stage_classifier[j].feature = new Array(cascade.stage_classifier[j].count);
					for (k = 0; k < cascade.stage_classifier[j].count; k++) {
						feature[k] = {"size" : orig_feature[k].size,
									  "px" : new Array(orig_feature[k].size),
									  "pz" : new Array(orig_feature[k].size),
									  "nx" : new Array(orig_feature[k].size),
									  "nz" : new Array(orig_feature[k].size)};
						for (q = 0; q < orig_feature[k].size; q++) {
							feature[k].px[q] = orig_feature[k].px[q] * 4 + orig_feature[k].py[q] * step[orig_feature[k].pz[q]];
							feature[k].pz[q] = orig_feature[k].pz[q];
							feature[k].nx[q] = orig_feature[k].nx[q] * 4 + orig_feature[k].ny[q] * step[orig_feature[k].nz[q]];
							feature[k].nz[q] = orig_feature[k].nz[q];
						}
					}
				}
				for (q = 0; q < 4; q++) {
					var u8 = [pyr[i * 4].data, pyr[i * 4 + next * 4].data, pyr[i * 4 + next * 8 + q].data];
					var u8o = [dx[q] * 8 + dy[q] * pyr[i * 4].width * 8, dx[q] * 4 + dy[q] * pyr[i * 4 + next * 4].width * 4, 0];
					for (y = 0; y < qh; y++) {
						for (x = 0; x < qw; x++) {
							var sum = 0;
							var flag = true;
							for (j = 0; j < cascade.stage_classifier.length; j++) {
								sum = 0;
								var alpha = cascade.stage_classifier[j].alpha;
								var feature = cascade.stage_classifier[j].feature;
								for (k = 0; k < cascade.stage_classifier[j].count; k++) {
									var feature_k = feature[k];
									var p, pmin = u8[feature_k.pz[0]][u8o[feature_k.pz[0]] + feature_k.px[0]];
									var n, nmax = u8[feature_k.nz[0]][u8o[feature_k.nz[0]] + feature_k.nx[0]];
									if (pmin <= nmax) {
										sum += alpha[k * 2];
									} else {
										var f, shortcut = true;
										for (f = 0; f < feature_k.size; f++) {
											if (feature_k.pz[f] >= 0) {
												p = u8[feature_k.pz[f]][u8o[feature_k.pz[f]] + feature_k.px[f]];
												if (p < pmin) {
													if (p <= nmax) {
														shortcut = false;
														break;
													}
													pmin = p;
												}
											}
											if (feature_k.nz[f] >= 0) {
												n = u8[feature_k.nz[f]][u8o[feature_k.nz[f]] + feature_k.nx[f]];
												if (n > nmax) {
													if (pmin <= n) {
														shortcut = false;
														break;
													}
													nmax = n;
												}
											}
										}
										sum += (shortcut) ? alpha[k * 2 + 1] : alpha[k * 2];
									}
								}
								if (sum < cascade.stage_classifier[j].threshold) {
									flag = false;
									break;
								}
							}
							if (flag) {
								seq.push({"x" : (x * 4 + dx[q] * 2) * scale_x,
										  "y" : (y * 4 + dy[q] * 2) * scale_y,
										  "width" : cascade.width * scale_x,
										  "height" : cascade.height * scale_y,
										  "neighbor" : 1,
										  "confidence" : sum});
							}
							u8o[0] += 16;
							u8o[1] += 8;
							u8o[2] += 4;
						}
						u8o[0] += paddings[0];
						u8o[1] += paddings[1];
						u8o[2] += paddings[2];
					}
				}
				scale_x *= scale;
				scale_y *= scale;
			}
			return seq;
		};

		var post = function (seq) {
			var i, j;
			for (i = 0; i < cascade.stage_classifier.length; i++)
				cascade.stage_classifier[i].feature = cascade.stage_classifier[i].orig_feature;
			if (!(params.min_neighbors > 0))
				return seq;
			else {
				var result = ccv.array_group(seq, function (r1, r2) {
					var distance = Math.floor(r1.width * 0.25 + 0.5);

					return r2.x <= r1.x + distance &&
						   r2.x >= r1.x - distance &&
						   r2.y <= r1.y + distance &&
						   r2.y >= r1.y - distance &&
						   r2.width <= Math.floor(r1.width * 1.5 + 0.5) &&
						   Math.floor(r2.width * 1.5 + 0.5) >= r1.width;
				});
				var ncomp = result.cat;
				var idx_seq = result.index;
				var comps = new Array(ncomp + 1);
				for (i = 0; i < comps.length; i++)
					comps[i] = {"neighbors" : 0,
								"x" : 0,
								"y" : 0,
								"width" : 0,
								"height" : 0,
								"confidence" : 0};

				// count number of neighbors
				for(i = 0; i < seq.length; i++)
				{
					var r1 = seq[i];
					var idx = idx_seq[i];

					if (comps[idx].neighbors == 0)
						comps[idx].confidence = r1.confidence;

					++comps[idx].neighbors;

					comps[idx].x += r1.x;
					comps[idx].y += r1.y;
					comps[idx].width += r1.width;
					comps[idx].height += r1.height;
					comps[idx].confidence = Math.max(comps[idx].confidence, r1.confidence);
				}

				var seq2 = [];
				// calculate average bounding box
				for(i = 0; i < ncomp; i++)
				{
					var n = comps[i].neighbors;
					if (n >= params.min_neighbors)
						seq2.push({"x" : (comps[i].x * 2 + n) / (2 * n),
								   "y" : (comps[i].y * 2 + n) / (2 * n),
								   "width" : (comps[i].width * 2 + n) / (2 * n),
								   "height" : (comps[i].height * 2 + n) / (2 * n),
								   "neighbors" : comps[i].neighbors,
								   "confidence" : comps[i].confidence});
				}

				var result_seq = [];
				// filter out small face rectangles inside large face rectangles
				for(i = 0; i < seq2.length; i++)
				{
					var r1 = seq2[i];
					var flag = true;
					for(j = 0; j < seq2.length; j++)
					{
						var r2 = seq2[j];
						var distance = Math.floor(r2.width * 0.25 + 0.5);

						if(i != j &&
						   r1.x >= r2.x - distance &&
						   r1.y >= r2.y - distance &&
						   r1.x + r1.width <= r2.x + r2.width + distance &&
						   r1.y + r1.height <= r2.y + r2.height + distance &&
						   (r2.neighbors > Math.max(3, r1.neighbors) || r1.neighbors < 3))
						{
							flag = false;
							break;
						}
					}

					if(flag)
						result_seq.push(r1);
				}
				return result_seq;
			}
		};
		if (params.setup) {
			ccv.__worker_scripts.detect_objects = work;
		} else {
			if (params.complete === undefined) {
				return post(work(pre(), params, 0, 1));
			} else {
				ccv.spawn(pre, "detect_objects", { "cascade" : params.cascade,
												   "interval" : params.interval,
												   "min_neighbors" : params.min_neighbors }, post, params.complete, params.worker_num);
			}
		}
	}
}

onmessage = function (event) {
	var data = (typeof event.data == "string") ? JSON.parse(event.data) : event.data;
	ccv[data.script]({"setup" : true});
	var result = ccv.__worker_scripts[data.script](data.data, data.params, data.id, data.worker_num);
	try {
		postMessage(result);
	} catch (e) {
		postMessage(JSON.stringify(result));
	}
}