Image-CCV
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ccv-src/js/ccv.js view on Meta::CPAN
"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 : parallable("ccv.js", function (canvas, cascade, interval, min_neighbors) {
if (this.shared !== undefined) {
var params = get_named_arguments(arguments, ["canvas", "cascade", "interval", "min_neighbors"]);
this.shared.canvas = params.canvas;
this.shared.interval = params.interval;
this.shared.min_neighbors = params.min_neighbors;
this.shared.cascade = params.cascade;
this.shared.scale = Math.pow(2, 1 / (params.interval + 1));
this.shared.next = params.interval + 1;
this.shared.scale_upto = Math.floor(Math.log(Math.min(params.canvas.width / params.cascade.width, params.canvas.height / params.cascade.height)) / Math.log(this.shared.scale));
var i;
for (i = 0; i < this.shared.cascade.stage_classifier.length; i++)
this.shared.cascade.stage_classifier[i].orig_feature = this.shared.cascade.stage_classifier[i].feature;
}
function pre(worker_num) {
var canvas = this.shared.canvas;
var interval = this.shared.interval;
var scale = this.shared.scale;
var next = this.shared.next;
var scale_upto = this.shared.scale_upto;
var pyr = new Array((scale_upto + next * 2) * 4);
var ret = new Array((scale_upto + next * 2) * 4);
pyr[0] = 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 <= 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 };
}
return [ret];
};
function core(pyr, id, worker_num) {
var cascade = this.shared.cascade;
var interval = this.shared.interval;
var scale = this.shared.scale;
var next = this.shared.next;
var scale_upto = this.shared.scale_upto;
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;
};
function post(seq) {
var min_neighbors = this.shared.min_neighbors;
var cascade = this.shared.cascade;
var interval = this.shared.interval;
var scale = this.shared.scale;
var next = this.shared.next;
var scale_upto = this.shared.scale_upto;
var i, j;
for (i = 0; i < cascade.stage_classifier.length; i++)
cascade.stage_classifier[i].feature = cascade.stage_classifier[i].orig_feature;
seq = seq[0];
if (!(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 >= 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++)
( run in 0.482 second using v1.01-cache-2.11-cpan-437f7b0c052 )