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tuning for real time processing(150~250% better performance) #10

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tuning for real time processing(150~250% better performance) #10

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09e771f
speed up hack. for positive number
Kanasansoft May 1, 2012
d63e286
speed up hack. for integral number
Kanasansoft May 1, 2012
f64f789
speed up hack. for reference property
Kanasansoft May 1, 2012
7abb6e6
rebuild for realtime processing.
Kanasansoft May 3, 2012
11b199b
delete duplication function and rename function
Kanasansoft May 7, 2012
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215 changes: 121 additions & 94 deletions js/ccv.js
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Original file line number Diff line number Diff line change
Expand Up @@ -97,7 +97,7 @@ var ccv = {
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;
var pix1, pix2, pix = ((canvas.width * canvas.height) << 2);
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);
Expand All @@ -106,18 +106,19 @@ var ccv = {

array_group : function (seq, gfunc) {
var i, j;
var node = new Array(seq.length);
for (i = 0; i < seq.length; i++)
var seq_length = seq.length;
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++) {
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++) {
for (j = 0; j < seq_length; j++) {
if( i != j && node[j].element && gfunc(node[i].element, node[j].element)) {
var root2 = j;

Expand Down Expand Up @@ -153,9 +154,9 @@ var ccv = {
}
}
}
var idx = new Array(seq.length);
var idx = new Array(seq_length);
var class_idx = 0;
for(i = 0; i < seq.length; i++) {
for(i = 0; i < seq_length; i++) {
j = -1;
var node1 = i;
if(node[node1].element) {
Expand All @@ -179,70 +180,75 @@ var ccv = {
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));
this.shared.scale_upto = ((Math.log(Math.min(params.canvas.width / params.cascade.width, params.canvas.height / params.cascade.height)) / Math.log(this.shared.scale)) | 0);
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;
var this_shared_cascade_stage_classifier = this.shared.cascade.stage_classifier;
var this_shared_cascade_stage_classifier_length = this_shared_cascade_stage_classifier.length;
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);
var scale_upto_next_1 = scale_upto + (next << 1);
var pyr = new Array((scale_upto + (next << 1)) << 2);
var ret = new Array((scale_upto + (next << 1)) << 2);
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 };
pyr[i << 2] = document.createElement("canvas");
pyr[i << 2].width = ((pyr[0].width / Math.pow(scale, i)) | 0);
pyr[i << 2].height = ((pyr[0].height / Math.pow(scale, i) | 0));
pyr[i << 2].getContext("2d").drawImage(pyr[0], 0, 0, pyr[0].width, pyr[0].height, 0, 0, pyr[i << 2].width, pyr[i << 2].height);
ret[i << 2] = { "width" : pyr[i << 2].width,
"height" : pyr[i << 2].height,
"data" : pyr[i << 2].getContext("2d").getImageData(0, 0, pyr[i << 2].width, pyr[i << 2].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; i < scale_upto_next_1; i++) {
pyr[i << 2] = document.createElement("canvas");
pyr[i << 2].width = ((pyr[(i << 2) - (next << 2)].width / 2) | 0);
pyr[i << 2].height = ((pyr[(i << 2) - (next << 2)].height / 2) | 0);
pyr[i << 2].getContext("2d").drawImage(pyr[(i << 2) - (next << 2)], 0, 0, pyr[(i << 2) - (next << 2)].width, pyr[(i << 2) - (next << 2)].height, 0, 0, pyr[i << 2].width, pyr[i << 2].height);
ret[i << 2] = { "width" : pyr[i << 2].width,
"height" : pyr[i << 2].height,
"data" : pyr[i << 2].getContext("2d").getImageData(0, 0, pyr[i << 2].width, pyr[i << 2].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 = (next << 1); i < scale_upto_next_1; i++) {
pyr[(i << 2) + 1] = document.createElement("canvas");
pyr[(i << 2) + 1].width = ((pyr[(i << 2) - (next << 2)].width / 2) | 0);
pyr[(i << 2) + 1].height = ((pyr[(i << 2) - (next << 2)].height / 2) | 0);
pyr[(i << 2) + 1].getContext("2d").drawImage(pyr[(i << 2) - (next << 2)], 1, 0, pyr[(i << 2) - (next << 2)].width - 1, pyr[(i << 2) - (next << 2)].height, 0, 0, pyr[(i << 2) + 1].width - 2, pyr[(i << 2) + 1].height);
ret[(i << 2) + 1] = { "width" : pyr[(i << 2) + 1].width,
"height" : pyr[(i << 2) + 1].height,
"data" : pyr[(i << 2) + 1].getContext("2d").getImageData(0, 0, pyr[(i << 2) + 1].width, pyr[(i << 2) + 1].height).data };
pyr[(i << 2) + 2] = document.createElement("canvas");
pyr[(i << 2) + 2].width = ((pyr[(i << 2) - (next << 2)].width / 2) | 0);
pyr[(i << 2) + 2].height = ((pyr[(i << 2) - (next << 2)].height / 2) | 0);
pyr[(i << 2) + 2].getContext("2d").drawImage(pyr[(i << 2) - (next << 2)], 0, 1, pyr[(i << 2) - (next << 2)].width, pyr[(i << 2) - (next << 2)].height - 1, 0, 0, pyr[(i << 2) + 2].width, pyr[(i << 2) + 2].height - 2);
ret[(i << 2) + 2] = { "width" : pyr[(i << 2) + 2].width,
"height" : pyr[(i << 2) + 2].height,
"data" : pyr[(i << 2) + 2].getContext("2d").getImageData(0, 0, pyr[(i << 2) + 2].width, pyr[(i << 2) + 2].height).data };
pyr[(i << 2) + 3] = document.createElement("canvas");
pyr[(i << 2) + 3].width = ((pyr[(i << 2) - (next << 2)].width / 2) | 0);
pyr[(i << 2) + 3].height = ((pyr[(i << 2) - (next << 2)].height / 2) | 0);
pyr[(i << 2) + 3].getContext("2d").drawImage(pyr[(i << 2) - (next << 2)], 1, 1, pyr[(i << 2) - (next << 2)].width - 1, pyr[(i << 2) - (next << 2)].height - 1, 0, 0, pyr[(i << 2) + 3].width - 2, pyr[(i << 2) + 3].height - 2);
ret[(i << 2) + 3] = { "width" : pyr[(i << 2) + 3].width,
"height" : pyr[(i << 2) + 3].height,
"data" : pyr[(i << 2) + 3].getContext("2d").getImageData(0, 0, pyr[(i << 2) + 3].width, pyr[(i << 2) + 3].height).data };
}
return [ret];
};

function core(pyr, id, worker_num) {
var cascade = this.shared.cascade;
var cascade_stage_classifier = cascade.stage_classifier;
var cascade_stage_classifier_length = cascade_stage_classifier.length;
var interval = this.shared.interval;
var scale = this.shared.scale;
var next = this.shared.next;
Expand All @@ -253,51 +259,69 @@ var ccv = {
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];
var qw = pyr[(i << 2) + (next << 3)].width - ((cascade.width / 4) | 0);
var qh = pyr[(i << 2) + (next << 3)].height - ((cascade.height / 4) | 0);
var step = [(pyr[i << 2].width << 2), (pyr[(i << 2) + (next << 2)].width << 2), (pyr[(i << 2) + (next << 3)].width << 2)];
var paddings = [(pyr[i << 2].width << 4) - (qw << 4),
(pyr[(i << 2) + (next << 2)].width << 3) - (qw << 3),
(pyr[(i << 2) + (next << 3)].width << 2) - (qw << 2)];
for (j = 0; j < cascade_stage_classifier_length; j++) {
var cascade_stage_classifier_j = cascade_stage_classifier[j];
var cascade_stage_classifier_j_count = cascade_stage_classifier_j.count;
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++) {
var orig_feature_k = orig_feature[k];
var orig_feature_k_size = orig_feature_k.size;
var orig_feature_k_px = orig_feature_k.px;
var orig_feature_k_py = orig_feature_k.py;
var orig_feature_k_pz = orig_feature_k.pz;
var orig_feature_k_nx = orig_feature_k.nx;
var orig_feature_k_ny = orig_feature_k.ny;
var orig_feature_k_nz = orig_feature_k.nz;
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)};
var feature_k = feature[k];
for (q = 0; q < orig_feature_k_size; q++) {
feature_k.px[q] = (orig_feature_k_px[q] << 2) + 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] << 2) + 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];
var u8 = [pyr[i << 2].data, pyr[(i << 2) + (next << 2)].data, pyr[(i << 2) + (next << 3) + q].data];
var u8o = [(dx[q] << 3) + dy[q] * (pyr[i << 2].width << 3), (dx[q] << 2) + dy[q] * (pyr[(i << 2) + (next << 2)].width << 2), 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++) {
for (j = 0; j < cascade_stage_classifier_length; j++) {
var cascade_stage_classifier_j = cascade_stage_classifier[j];
var cascade_stage_classifier_j_count = cascade_stage_classifier_j.count;
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 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]];
var feature_k_px = feature_k.px;
var feature_k_pz = feature_k.pz;
var feature_k_nx = feature_k.nx;
var feature_k_nz = feature_k.nz;
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];
sum += alpha[k << 1];
} 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]];
var feature_k_size = feature_k.size;
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;
Expand All @@ -306,8 +330,8 @@ var ccv = {
pmin = p;
}
}
if (feature_k.nz[f] >= 0) {
n = u8[feature_k.nz[f]][u8o[feature_k.nz[f]] + feature_k.nx[f]];
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;
Expand All @@ -317,17 +341,17 @@ var ccv = {
}
}
}
sum += (shortcut) ? alpha[k * 2 + 1] : alpha[k * 2];
sum += (shortcut) ? alpha[(k << 1) + 1] : alpha[k << 1];
}
}
if (sum < cascade.stage_classifier[j].threshold) {
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,
seq.push({"x" : ((x << 2) + (dx[q] << 1)) * scale_x,
"y" : ((y << 2) + (dy[q] << 1)) * scale_y,
"width" : cascade.width * scale_x,
"height" : cascade.height * scale_y,
"neighbor" : 1,
Expand All @@ -351,26 +375,28 @@ var ccv = {
function post(seq) {
var min_neighbors = this.shared.min_neighbors;
var cascade = this.shared.cascade;
var cascade_stage_classifier = cascade.stage_classifier;
var cascade_stage_classifier_length = cascade_stage_classifier.length;
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;
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);
var distance = ((r1.width * 0.25 + 0.5) | 0);

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;
r2.width <= ((r1.width * 1.5 + 0.5) | 0) &&
((r2.width * 1.5 + 0.5) | 0) >= r1.width;
});
var ncomp = result.cat;
var idx_seq = result.index;
Expand All @@ -384,7 +410,8 @@ var ccv = {
"confidence" : 0};

// count number of neighbors
for(i = 0; i < seq.length; i++)
var seq_length = seq.length;
for(i = 0; i < seq_length; i++)
{
var r1 = seq[i];
var idx = idx_seq[i];
Expand Down Expand Up @@ -424,7 +451,7 @@ var ccv = {
for(j = 0; j < seq2.length; j++)
{
var r2 = seq2[j];
var distance = Math.floor(r2.width * 0.25 + 0.5);
var distance = ((r2.width * 0.25 + 0.5) | 0);

if(i != j &&
r1.x >= r2.x - distance &&
Expand Down
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