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PS2 MDDN 342 2018
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license: mit
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README.md

PS2 MDDN 342 2018

hey there! I was unable to add my readmes' using git checkout (it is very late at night), so I have added them all here. sorry about this! :) they go in order from most recent - oldest and there are 6 entries for the 6 purview holder things.)

##Seccond round of testing - FINAL

this is my final: here are my official parameters:

Hair color --> opacity of the ears face width--> length of the whiskers gender--> fluffy for boys, sharp and angular for the girls eye color --> eye color skin color --> deepness of skin color

some things I had to change from the last round of training:

- reduced the number of eye colors to choose from, as the AI can barely see the difference between two.
- made the fur correspond to the skin color of the person I was testing, because hair was very iffy in terms of the AI learning how to do that to.
- opacity of the ears directly corresponds to the darkness of the hair now.

Some aestheitc changes I made:

I made added shading detail in the female cats, making them look a little 3D and angular. I could not find a way to do this super nicely for the men.

Choice in images:

All three have a different narrative, and are not related in any way

Crazy cat people --> this one is relativly self explanatory, crazy cat people wearing crazy cat mask faces! Kardashians --> pussy power, powerfull women, enough said. Past US presidents --> it'd be nice to view the past presidents as nice fluffy aproachable people rather than big scary men in suits. It represents that everyone has a soft side.

My overall thoughts on the final product:

I do like it, I just wish I had allowed myself more time to work out the kinks in the design and the testing. As I am a perfectionist this is not enough for me, but I think it is adequate/pretty good for the time contraints I have had thoughout project 2 (from other subject, asignments, and work). I like my ps1 better, and I think the two link together well.

##First Round of Training:

Things I have trained:

hair color --> changes the color of the cats fur (i.e. people with dark hair will have black or brown - people with red hair have pink)

Face width --> the length of the cats whiskers (i.e. much like in nature the wider the cat the wider the whiskers).

Gender --> People who present as mascualine become cute and fluffy cats

Facial Hair --> men with facial hair have darker ear inners/eat opacity

Eye color --> I am training at the moment to blue, green, brown, and dark eye colors. This is in a very 'beta' stage. i.e is not working so well. In my next iteration I will definitly be changing the colors to more like: 'light, medium, and dark' to try and confuse the AI a little bit less

The other thing which is currently in beta is the hair color. As kim kardashian certainly isnt ginger - but the Ai believes she is. I will likely be changing and training further.

If I have time/ mad passion I will defintily add some more sliders which can be further customisable to the Individual which is mapped.

Choice in images:

All three have a different narrative, and are not related in any way

Crazy cat people --> this one is relativly self explanatory, crazy cat people wearing crazy cat mask faces! Kardashians --> pussy power, powerfull women, enough said. Past US presidents --> it'd be nice to view the past presidents as nice fluffy aproachable people rather than big scary men in suits. It represents that everyone has a soft side.

##fourth entry:

I am experiementing with testing today, I was having some issues with getting the testing to work on the images I had selected. They would train fine, and the quiz would be fine, but they would reset to the default face and be all the same in the faces section. It turns out there was an issue with merging part three. Tom fixed it for me.

The mappings I have now are: tilt, character type (the men are fluffy), whisker length, color, ear opacity, eye color. I have changed the color from black and white to natural hair colors, in order to have some diversity when mapping hair color. I am not sure how I feel about it though.

##Third Entry:

In order to make my mak more mask like, I deleted every second vertice from the chin mapping. This created a more structured look which I feel made it look more mask like. This also got rid of the annoying chin point. In addition to this, I added names to my sliders. I have tilt, whiskers and mouth, gender, and glasses. I ended up getting rid of the mouth, and replacing it with a for loop of just the top lip. This makes them look a little creepy cat/human like, which I am pleased with. I have not yet linked the sliders but I will asap.

The other thing I did was experiment with pictures, I added the kardashians in which I like, but I will probably revert back to the origional image for tersting purposes. Soley becaue the kardashian picture is far away, and harder for me to see.

##Second Entry:

I decided to go with a a geometric theme, as I felt this would be easier to implement using the points given from the mapping. The only thing I do not like about this is that the chin is super long for a cat. I would prefer for it to look more like a mask rather than a weird cat face imposed on a human. I can also not nolonger like the mouth - as thr line does not line up with the nose (which I made using a for loop).

I also re made the eyes. I did this by using a for loop to circle around the points, and then I adjusted scale to make them big and exadgerated like cats eyes. The ears are based on the eyebrows. I like having almost everything mapped to the verticies as it looks more dynamic in relation to the face.

At this point, I only one slider, which is tilt at this point. And also whisker length/mouth length.

##First Entry:

Importing my values from ps1 into code for ps2. Have added in some aspects of my previous design, have not implemented the changes yet. I did have to hard code as the scale was different from ps1. I redid all my code.

Raw
face.js
/*
* FaceMap class - holds all informaiton about one mapped
* face and is able to draw itself.
*/
// other variables can be in here too
// these control the colors used
const bg_color = [225, 206, 187];
const fg_color = [151, 102, 52];
const stroke_color = [95, 52, 8];
function Face() {
// these are state variables for a face
// (your variables may be different)
this.tilt_value = 0;
this.eye_value = 2;
this.whisker_value = 1;
this.hue = 0;
this.face_opacity = 255;
this.fur_color = 2;
strokeJoin(ROUND);
colorMode(RGB);
/*
* Draw a face with position lists that include:
* chin, right_eye, left_eye, right_eyebrow, left_eyebrow
* bottom_lip, top_lip, nose_tip, nose_bridge,
*/
this.draw = function(positions) {
rotate(this.tilt_value);
// scale(0.8);
var r = random(240);
//rgb controling color of base face
var r = random(240);
//var g = random(100);
//var b = random(100);
let rb = 0;
let g = focusedRandom(200,255);
let b = focusedRandom(200,255);
if (this.fur_color <= 0){ //white
fill(255);
}
if (this.fur_color == 1){
fill(225);
let rb = 10;
}
if (this.fur_color == 2){
fill(150);
}
if (this.fur_color == 3){
fill(75);
}
if (this.fur_color == 4){ //black
fill(25);
}
var eye1_pos = average_point(positions.left_eye);
var eye2_pos = average_point(positions.right_eye);
let face0 = positions.chin[0];
let face1 = positions.chin[1];
let face2 = positions.chin[2];
let face3 = positions.chin[3];
let face4 = positions.chin[4];
let face5 = positions.chin[5];
let face6 = positions.chin[6];
let face7 = positions.chin[7];
let face8 = positions.chin[8];
let face9 = positions.chin[9];
let face10 = positions.chin[10];
let face11 = positions.chin[11];
let face12 = positions.chin[12];
let face13 = positions.chin[13];
let face14 = positions.chin[14];
let face15 = positions.chin[15];
let face16 = positions.chin[16];
//left eyebrow
let eyebrow1 = positions.left_eyebrow[0];
let eyebrow2 = positions.left_eyebrow[1];
let eyebrow3 = positions.left_eyebrow[2];
let eyebrow4 = positions.left_eyebrow[3];
let eyebrow5 = positions.left_eyebrow[4];
//right eyebrow
let eyebrow6 = positions.right_eyebrow[0];
let eyebrow7 = positions.right_eyebrow[1];
let eyebrow8 = positions.right_eyebrow[2];
let eyebrow9 = positions.right_eyebrow[3];
let eyebrow10 = positions.right_eyebrow[4];
//eyes
let eye1 = positions.left_eye[0];
let eye2 = positions.left_eye[1];
let eye3 = positions.left_eye[2];
let eye4 = positions.left_eye[3];
let eye5 = positions.left_eye[4];
let eye6 = positions.left_eye[5];
let eye7 = positions.right_eye[0];
let eye8 = positions.right_eye[1];
let eye9 = positions.right_eye[2];
let eye10 = positions.right_eye[3];
let eye11 = positions.right_eye[4];
let eye12 = positions.right_eye[5];
let lip = positions.bottom_lip[1];
strokeWeight(0);
if (this.gender_value!= 2){
beginShape();
vertex(face0[0], face0[1]);
// vertex(face1[0], face1[1]);
vertex(face2[0], face2[1]);
// vertex(face3[0], face3[1]);
vertex(face4[0], face4[1]);
// vertex(face5[0], face5[1]);
vertex(face6[0], face6[1]);
//vertex(face7[0], face7[1]);
// vertex(face8[0], face8[1]);
// vertex(face9[0], face9[1]);
vertex(face10[0], face10[1]);
// vertex(face11[0], face11[1]);
vertex(face12[0], face12[1]);
//vertex(face13[0], face13[1]);
vertex(face14[0], face14[1]);
// vertex(face15[0], face15[1]);
vertex(face16[0], face16[1]);
vertex(eyebrow7[0],eyebrow7[1]);
vertex(eyebrow4[0],eyebrow4[1]);
endShape();
if (this.fur_color <= 0){ //white
fill(245);
}
if (this.fur_color == 1){
fill(215);
}
if (this.fur_color == 2){
fill(140);
}
if (this.fur_color == 3){
fill(65);
}
if (this.fur_color == 4){ //black
fill(15);
}
beginShape();
vertex(face6[0], face6[1]);
vertex(face10[0], face10[1]);
vertex(face12[0], face12[1]);
vertex(face14[0], face14[1]);
vertex(face16[0], face16[1]);
vertex(lip[0], lip[1]);
endShape();
}
if (this.gender_value == 2){
var fluffsize = 1.2;
scale(0.8);
ellipse(face0[0], face0[1],fluffsize,fluffsize);
ellipse(face2[0], face2[1],fluffsize,fluffsize);
ellipse(face4[0], face4[1],fluffsize,fluffsize);
ellipse(face6[0], face6[1] -0.2,fluffsize,fluffsize);
ellipse(face8[0], face8[1] -0.5,fluffsize,fluffsize);
ellipse(face10[0], face10[1] -0.2,fluffsize,fluffsize);
ellipse(face12[0], face12[1],fluffsize,fluffsize);
ellipse(face14[0], face14[1],fluffsize,fluffsize);
ellipse(face16[0], face16[1],fluffsize,fluffsize);
ellipse(eyebrow7[0],eyebrow7[1],fluffsize,fluffsize);
ellipse(eyebrow4[0],eyebrow4[1],fluffsize,fluffsize);
ellipse(eyebrow2[0],eyebrow2[1],fluffsize,fluffsize);
ellipse(eyebrow1[0],eyebrow1[1],fluffsize,fluffsize);
ellipse(eyebrow6[0],eyebrow6[1],fluffsize,fluffsize);
ellipse(eyebrow9[0],eyebrow9[1],fluffsize,fluffsize);
strokeWeight(0);
beginShape();
vertex(face0[0], face0[1]);
// vertex(face1[0], face1[1]);
vertex(face2[0], face2[1]);
// vertex(face3[0], face3[1]);
vertex(face4[0], face4[1]);
// vertex(face5[0], face5[1]);
vertex(face6[0], face6[1]);
//vertex(face7[0], face7[1]);
// vertex(face8[0], face8[1]);
// vertex(face9[0], face9[1]);
vertex(face10[0], face10[1]);
// vertex(face11[0], face11[1]);
vertex(face12[0], face12[1]);
//vertex(face13[0], face13[1]);
vertex(face14[0], face14[1]);
// vertex(face15[0], face15[1]);
vertex(face16[0], face16[1]);
vertex(eyebrow7[0],eyebrow7[1]);
vertex(eyebrow4[0],eyebrow4[1]);
endShape();
scale(1.3);
}
colorMode(RGB);
//ears
if (this.fur_color <= 0){ //white
stroke(255);
}
if (this.fur_color == 1){
stroke(225);
let rb = 10;
}
if (this.fur_color == 2){
stroke(150);
}
if (this.fur_color == 3){
stroke(75);
}
if (this.fur_color == 4){ //black
stroke(25);
}
//stroke(rb);
strokeWeight(0.03);
triangle(face0[0], face0[1], face0[0], -2, eyebrow4[0], eyebrow4[1]); //left, top, right
triangle(eyebrow7[0], eyebrow7[1], face16[0], -2,face16[0], face16[1]); //left, top, right
//inner ear
scale(0.9);
fill(rb, this.face_opacity);
triangle(face0[0], face0[1], face0[0], -1.9, eyebrow4[0], eyebrow4[1]); //left, top, right
triangle(eyebrow7[0], eyebrow7[1], face16[0], -1.9,face16[0], face16[1]); //left, top, right
scale(1.1);
strokeWeight(0);
//eye
var eyeshifty = 0.7;
var eyeshiftx = 0.4;
fill(0);
scale(1.7);
scale(1.1);
rotate(15);
//strokeWeight(0.1);
//BLACK
if (this.gender_value == 1){
beginShape();
vertex(eye1[0]+eyeshiftx, eye1[1]+eyeshifty);
vertex(eye2[0]+eyeshiftx, eye2[1]+eyeshifty);
vertex(eye3[0]+eyeshiftx, eye3[1]+eyeshifty);
vertex(eye4[0]+eyeshiftx,eye4[1]+eyeshifty);
vertex(eye5[0]+eyeshiftx,eye5[1]+0.1+eyeshifty);
vertex(eye6[0]+eyeshiftx,eye6[1]+0.1+eyeshifty);
endShape();
}
scale(0.9);
fill(255);
//LEFT EYE
beginShape();
vertex(eye1[0]+eyeshiftx, eye1[1]+eyeshifty);
vertex(eye2[0]+eyeshiftx, eye2[1]+eyeshifty);
vertex(eye3[0]+eyeshiftx, eye3[1]+eyeshifty);
vertex(eye4[0]+eyeshiftx,eye4[1]+eyeshifty);
vertex(eye5[0]+eyeshiftx,eye5[1]+0.1+eyeshifty);
vertex(eye6[0]+eyeshiftx,eye6[1]+0.1+eyeshifty);
endShape();
//BLACK BEHIND RIGHT EYE
if (this.eye_color <= 0){ //green
fill(65,178,231);
}
if (this.eye_color == 1 ){ //blue
fill(40, 9, 9);
}
if (this.eye_color ==2){ //brown
fill(90, 212,18);
}
ellipse(eye1_pos[0]+eyeshiftx +mouseX/15000, eye1_pos[1]+eyeshifty+0.04,0.1,0.22);
fill(0);
//ellipse(eye1_pos[0]+eyeshiftx +mouseX/15000, eye1_pos[1]+eyeshifty+0.04,0.05,0.2);
rotate(-15);
fill(255);
rotate(-15);
scale(1.1);
fill(0);
if (this.gender_value == 1){
beginShape();
vertex(eye7[0]-eyeshiftx/2, eye7[1]+eyeshifty);
vertex(eye8[0]-eyeshiftx/2, eye8[1]+eyeshifty);
vertex(eye9[0]-eyeshiftx/2, eye9[1]+eyeshifty);
vertex(eye10[0]-eyeshiftx/2,eye10[1]+eyeshifty);
vertex(eye11[0]-eyeshiftx/2,eye11[1]+0.1+eyeshifty);
vertex(eye12[0]-eyeshiftx/2,eye12[1]+0.1+eyeshifty);
endShape();
}
//WHITE PART OF RIGHT EYE
scale(0.9);
fill(255);
beginShape();
vertex(eye7[0]-eyeshiftx/2, eye7[1]+eyeshifty);
vertex(eye8[0]-eyeshiftx/2, eye8[1]+eyeshifty);
vertex(eye9[0]-eyeshiftx/2, eye9[1]+eyeshifty);
vertex(eye10[0]-eyeshiftx/2,eye10[1]+eyeshifty);
vertex(eye11[0]-eyeshiftx/2,eye11[1]+0.1+eyeshifty);
vertex(eye12[0]-eyeshiftx/2,eye12[1]+0.1+eyeshifty);
endShape();
if (this.eye_color <= 0){ //green
fill(65,178,231);
}
if (this.eye_color == 1 ){ //blue
fill(40, 9, 9);
}
if (this.eye_color ==2){ //brown
fill(90, 212,18);
}
ellipse(eye2_pos[0]-eyeshiftx/2 +mouseX/15000, eye2_pos[1]+eyeshifty+0.04,0.1,0.22);
fill(0);
//ellipse(eye2_pos[0]-eyeshiftx/2 +mouseX/15000, eye2_pos[1]+eyeshifty+0.04,0.05,0.2);
rotate(15);
scale(0.6);
if (this.fur_color <= 0){ //white
fill(255);
let rb = 255;
}
if (this.fur_color == 1){
fill(225);
let rb = 225;
}
if (this.fur_color == 2){
fill(150);let rb = 150;
}
if (this.fur_color == 3){
fill(75);let rb = 75;
}
if (this.fur_color == 4){ //black
fill(25);let rb = 25;
}
// head
strokeWeight(0);
//ellipse(0, 0, 3, 3); //cat base face
//noStroke();
//changes the color of the face attributes different to the face color
var noseCol;
if (rb > 150){
noseCol = rb - 55; //variation of the nose color, so that the color of the nose will never be the same as the fur
}
if (rb<150){
noseCol = rb +55;
}
fill(noseCol);
fill(r);
//ellipse(0, -0.7, 3, 2); //cat base face //second cat face
fill(noseCol);
stroke(noseCol);
let pos_nose2 = positions.nose_tip[2];
strokeWeight(0.03);
scale(0.7)
beginShape();
for(var i=0; i<positions.top_lip.length;i++) {
vertex(positions.top_lip[i][0], positions.top_lip[i][1]+0.4);
}
endShape(CLOSE);
beginShape();
endShape(CLOSE);
scale(1.3);
// mouth
strokeWeight(0.02);
fill(bg_color);
beginShape();
endShape();
fill(noseCol);
//whiskers
strokeWeight(0.03);
//right whiskers
line(1, 0.4, 0.5 + this.whisker_value/3, 0.4 ); //middle
line(1, 0.45, 0.5 + this.whisker_value/3, 0.55 ); //bottom
line(1, 0.35, 0.5 +this.whisker_value/3, 0.25 ); //top
//left
line(-1, 0.4, -0.5 - this.whisker_value/3, 0.4 ); //middle
line(-1, 0.45, -0.5 - this.whisker_value/3, 0.55 ); //bottom
line(-1, 0.35, -0.5 -this.whisker_value/3, 0.25 ); //top
strokeWeight(0.0);
fill(0);
//scaled down nose
scale(0.03);
fill(noseCol);
//triangle(-7.5,0,7.5,0,0,7.5);
scale(20);
//nose using for loop
scale(1.5);
beginShape();
//vertex(positions.nose_bridge[0][0], positions.nose_bridge[0][1]);
for(var i=0; i<positions.nose_tip.length;i++) {
vertex(positions.nose_tip[i][0], positions.nose_tip[i][1]);
//3
}
endShape(CLOSE);
// mouth
fill(bg_color);
//ellipse(0, 0.64, 1.36, 1.36 * 0.25 * this.whisker_value);
}
/* set internal properties based on list numbers 0-100 */
this.setProperties = function(settings) {
// print(settings);
this.tilt_value = map(settings[0], 0, 100, -30, 30);
this.gender_value = int(map(settings[1], 0, 100, 1, 2));
this.whisker_value = map(settings[2], 0, 100, 4, 8);
this.fur_color = int(map(settings[3], 0, 100, 0, 4));
this.face_opacity = map(settings[4], 0, 100, 10, 255);
this.eye_color = int(map(settings[5], 0, 100, 0, 2));
}
/* get internal properties as list of numbers 0-100 */
this.getProperties = function() {
properties = new Array(6);
properties[0] = map(this.tilt_value,-30,30,0,100);
properties[1] = map(this.gender_value, 1,2,0,100);
properties[2] = map(this.whisker_value,4,8,0,100);
properties[3] = map(this.fur_color,0,4,0,100);
properties[4] = map(this.face_opacity,10,255,0,100);
properties[5] = map(this.eye_color,0,2,0,100);
return properties;
}
}
// given an array of [x,y] points, return the average
function average_point(list) {
var sum_x = 0;
var sum_y = 0;
var num_points = 0;
for(var i=0; i<list.length; i++) {
sum_x += list[i][0];
sum_y += list[i][1];
num_points += 1;
}
return [sum_x / num_points, sum_y / num_points];
}
Raw
index.html
<head>
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.6.1/p5.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/0.6.1/addons/p5.dom.js"></script>
<script src="https://cdnjs.cloudflare.com/ajax/libs/seedrandom/2.4.3/seedrandom.min.js"></script>
<script src="https://d3js.org/d3-random.v1.min.js"></script>
<script src="z_clmtrackr.js"></script>
<script src="z_model_pca_20_svm.js"></script>
<script language="javascript" type="text/javascript" src="z_purview_helper.js"></script>
<script language="javascript" type="text/javascript" src="z_focused_random.js"></script>
<script language="javascript" type="text/javascript" src="kdTree.js"></script>
<script language="javascript" type="text/javascript" src="face.js"></script>
<script language="javascript" type="text/javascript" src="sketch.js"></script>
<style>
body { padding: 0; margin: 0; }
.inner { position: absolute; }
#controls {
font: 300 12px "Helvetica Neue";
padding: 5;
margin: 5;
background: #f0f0f0;
opacity: 0.0;
-webkit-transition: opacity 0.2s ease;
-moz-transition: opacity 0.2s ease;
-o-transition: opacity 0.2s ease;
-ms-transition: opacity 0.2s ease;
}
#controls:hover { opacity: 0.9; }
</style>
</head>
<body style="background-color:white">
<div class="outer">
<div class="inner" id="controls" height="500">
<table>
<tr>
<td>Tilt</td>
<td id="slider1Container"></td>
</tr>
<tr>
<td>Character Type/Gender</td>
<td id="slider2Container"></td>
</tr>
<tr>
<td>Whisker Length/ Face Wideness</td>
<td id="slider3Container"></td>
</tr>
<tr>
<td>Fur Color (Skin Color)</td>
<td id="slider4Container"></td>
</tr>
<tr>
<td>Ear Opacity (Hair Color) </td>
<td id="slider5Container"></td>
</tr>
<tr>
<td>Eye Color</td>
<td id="slider6Container"></td>
</tr>
<tr>
<td>setting 7</td>
<td id="slider7Container"></td>
</tr>
<tr>
<td>setting 8</td>
<td id="slider8Container"></td>
</tr>
<tr>
<td>setting 9</td>
<td id="slider9Container"></td>
</tr>
<tr>
<td>setting 10</td>
<td id="slider10Container"></td>
</tr>
<tr>
<td>setting 11</td>
<td id="slider11Container"></td>
</tr>
<tr>
<td>setting 12</td>
<td id="slider12Container"></td>
</tr>
<tr>
</tr>
<tr>
<td>show target</td>
<td id="sliderTintContainer"></td>
</tr>
<tr>
<td>Draw function</td>
<td id="selector1Container"></td>
</tr>
<tr>
<td>Face Draw</td>
<td id="checkbox1Container"></td>
</tr>
<tr>
<td>Face Targets</td>
<td id="checkbox2Container"></td>
</tr>
<tr>
<td>Face Points</td>
<td id="checkbox3Container"></td>
</tr>
<tr>
<td></td>
<td id="button1Container"></td>
</tr>
<tr>
<td></td>
<td id="button2Container"></td>
</tr>
<tr>
<td></td>
<td id="button3Container"></td>
</tr>
<tr>
<td></td>
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Raw
kdTree.js
/**
* k-d Tree JavaScript - V 1.01
*
* https://github.com/ubilabs/kd-tree-javascript
*
* @author Mircea Pricop <pricop@ubilabs.net>, 2012
* @author Martin Kleppe <kleppe@ubilabs.net>, 2012
* @author Ubilabs http://ubilabs.net, 2012
* @license MIT License <http://www.opensource.org/licenses/mit-license.php>
*/
(function (root, factory) {
if (typeof define === 'function' && define.amd) {
define(['exports'], factory);
} else if (typeof exports === 'object') {
factory(exports);
} else {
factory((root.commonJsStrict = {}));
}
}(this, function (exports) {
function Node(obj, dimension, parent) {
this.obj = obj;
this.left = null;
this.right = null;
this.parent = parent;
this.dimension = dimension;
}
function kdTree(points, metric, dimensions) {
var self = this;
function buildTree(points, depth, parent) {
var dim = depth % dimensions.length,
median,
node;
if (points.length === 0) {
return null;
}
if (points.length === 1) {
return new Node(points[0], dim, parent);
}
points.sort(function (a, b) {
return a[dimensions[dim]] - b[dimensions[dim]];
});
median = Math.floor(points.length / 2);
node = new Node(points[median], dim, parent);
node.left = buildTree(points.slice(0, median), depth + 1, node);
node.right = buildTree(points.slice(median + 1), depth + 1, node);
return node;
}
// Reloads a serialied tree
function loadTree (data) {
// Just need to restore the `parent` parameter
self.root = data;
function restoreParent (root) {
if (root.left) {
root.left.parent = root;
restoreParent(root.left);
}
if (root.right) {
root.right.parent = root;
restoreParent(root.right);
}
}
restoreParent(self.root);
}
// If points is not an array, assume we're loading a pre-built tree
if (!Array.isArray(points)) loadTree(points, metric, dimensions);
else this.root = buildTree(points, 0, null);
// Convert to a JSON serializable structure; this just requires removing
// the `parent` property
this.toJSON = function (src) {
if (!src) src = this.root;
var dest = new Node(src.obj, src.dimension, null);
if (src.left) dest.left = self.toJSON(src.left);
if (src.right) dest.right = self.toJSON(src.right);
return dest;
};
this.insert = function (point) {
function innerSearch(node, parent) {
if (node === null) {
return parent;
}
var dimension = dimensions[node.dimension];
if (point[dimension] < node.obj[dimension]) {
return innerSearch(node.left, node);
} else {
return innerSearch(node.right, node);
}
}
var insertPosition = innerSearch(this.root, null),
newNode,
dimension;
if (insertPosition === null) {
this.root = new Node(point, 0, null);
return;
}
newNode = new Node(point, (insertPosition.dimension + 1) % dimensions.length, insertPosition);
dimension = dimensions[insertPosition.dimension];
if (point[dimension] < insertPosition.obj[dimension]) {
insertPosition.left = newNode;
} else {
insertPosition.right = newNode;
}
};
this.remove = function (point) {
var node;
function nodeSearch(node) {
if (node === null) {
return null;
}
if (node.obj === point) {
return node;
}
var dimension = dimensions[node.dimension];
if (point[dimension] < node.obj[dimension]) {
return nodeSearch(node.left, node);
} else {
return nodeSearch(node.right, node);
}
}
function removeNode(node) {
var nextNode,
nextObj,
pDimension;
function findMin(node, dim) {
var dimension,
own,
left,
right,
min;
if (node === null) {
return null;
}
dimension = dimensions[dim];
if (node.dimension === dim) {
if (node.left !== null) {
return findMin(node.left, dim);
}
return node;
}
own = node.obj[dimension];
left = findMin(node.left, dim);
right = findMin(node.right, dim);
min = node;
if (left !== null && left.obj[dimension] < own) {
min = left;
}
if (right !== null && right.obj[dimension] < min.obj[dimension]) {
min = right;
}
return min;
}
if (node.left === null && node.right === null) {
if (node.parent === null) {
self.root = null;
return;
}
pDimension = dimensions[node.parent.dimension];
if (node.obj[pDimension] < node.parent.obj[pDimension]) {
node.parent.left = null;
} else {
node.parent.right = null;
}
return;
}
// If the right subtree is not empty, swap with the minimum element on the
// node's dimension. If it is empty, we swap the left and right subtrees and
// do the same.
if (node.right !== null) {
nextNode = findMin(node.right, node.dimension);
nextObj = nextNode.obj;
removeNode(nextNode);
node.obj = nextObj;
} else {
nextNode = findMin(node.left, node.dimension);
nextObj = nextNode.obj;
removeNode(nextNode);
node.right = node.left;
node.left = null;
node.obj = nextObj;
}
}
node = nodeSearch(self.root);
if (node === null) { return; }
removeNode(node);
};
this.nearest = function (point, maxNodes, maxDistance) {
var i,
result,
bestNodes;
bestNodes = new BinaryHeap(
function (e) { return -e[1]; }
);
function nearestSearch(node) {
var bestChild,
dimension = dimensions[node.dimension],
ownDistance = metric(point, node.obj),
linearPoint = {},
linearDistance,
otherChild,
i;
function saveNode(node, distance) {
bestNodes.push([node, distance]);
if (bestNodes.size() > maxNodes) {
bestNodes.pop();
}
}
for (i = 0; i < dimensions.length; i += 1) {
if (i === node.dimension) {
linearPoint[dimensions[i]] = point[dimensions[i]];
} else {
linearPoint[dimensions[i]] = node.obj[dimensions[i]];
}
}
linearDistance = metric(linearPoint, node.obj);
if (node.right === null && node.left === null) {
if (bestNodes.size() < maxNodes || ownDistance < bestNodes.peek()[1]) {
saveNode(node, ownDistance);
}
return;
}
if (node.right === null) {
bestChild = node.left;
} else if (node.left === null) {
bestChild = node.right;
} else {
if (point[dimension] < node.obj[dimension]) {
bestChild = node.left;
} else {
bestChild = node.right;
}
}
nearestSearch(bestChild);
if (bestNodes.size() < maxNodes || ownDistance < bestNodes.peek()[1]) {
saveNode(node, ownDistance);
}
if (bestNodes.size() < maxNodes || Math.abs(linearDistance) < bestNodes.peek()[1]) {
if (bestChild === node.left) {
otherChild = node.right;
} else {
otherChild = node.left;
}
if (otherChild !== null) {
nearestSearch(otherChild);
}
}
}
if (maxDistance) {
for (i = 0; i < maxNodes; i += 1) {
bestNodes.push([null, maxDistance]);
}
}
if(self.root)
nearestSearch(self.root);
result = [];
for (i = 0; i < Math.min(maxNodes, bestNodes.content.length); i += 1) {
if (bestNodes.content[i][0]) {
result.push([bestNodes.content[i][0].obj, bestNodes.content[i][1]]);
}
}
return result;
};
this.balanceFactor = function () {
function height(node) {
if (node === null) {
return 0;
}
return Math.max(height(node.left), height(node.right)) + 1;
}
function count(node) {
if (node === null) {
return 0;
}
return count(node.left) + count(node.right) + 1;
}
return height(self.root) / (Math.log(count(self.root)) / Math.log(2));
};
}
// Binary heap implementation from:
// http://eloquentjavascript.net/appendix2.html
function BinaryHeap(scoreFunction){
this.content = [];
this.scoreFunction = scoreFunction;
}
BinaryHeap.prototype = {
push: function(element) {
// Add the new element to the end of the array.
this.content.push(element);
// Allow it to bubble up.
this.bubbleUp(this.content.length - 1);
},
pop: function() {
// Store the first element so we can return it later.
var result = this.content[0];
// Get the element at the end of the array.
var end = this.content.pop();
// If there are any elements left, put the end element at the
// start, and let it sink down.
if (this.content.length > 0) {
this.content[0] = end;
this.sinkDown(0);
}
return result;
},
peek: function() {
return this.content[0];
},
remove: function(node) {
var len = this.content.length;
// To remove a value, we must search through the array to find
// it.
for (var i = 0; i < len; i++) {
if (this.content[i] == node) {
// When it is found, the process seen in 'pop' is repeated
// to fill up the hole.
var end = this.content.pop();
if (i != len - 1) {
this.content[i] = end;
if (this.scoreFunction(end) < this.scoreFunction(node))
this.bubbleUp(i);
else
this.sinkDown(i);
}
return;
}
}
throw new Error("Node not found.");
},
size: function() {
return this.content.length;
},
bubbleUp: function(n) {
// Fetch the element that has to be moved.
var element = this.content[n];
// When at 0, an element can not go up any further.
while (n > 0) {
// Compute the parent element's index, and fetch it.
var parentN = Math.floor((n + 1) / 2) - 1,
parent = this.content[parentN];
// Swap the elements if the parent is greater.
if (this.scoreFunction(element) < this.scoreFunction(parent)) {
this.content[parentN] = element;
this.content[n] = parent;
// Update 'n' to continue at the new position.
n = parentN;
}
// Found a parent that is less, no need to move it further.
else {
break;
}
}
},
sinkDown: function(n) {
// Look up the target element and its score.
var length = this.content.length,
element = this.content[n],
elemScore = this.scoreFunction(element);
while(true) {
// Compute the indices of the child elements.
var child2N = (n + 1) * 2, child1N = child2N - 1;
// This is used to store the new position of the element,
// if any.
var swap = null;
// If the first child exists (is inside the array)...
if (child1N < length) {
// Look it up and compute its score.
var child1 = this.content[child1N],
child1Score = this.scoreFunction(child1);
// If the score is less than our element's, we need to swap.
if (child1Score < elemScore)
swap = child1N;
}
// Do the same checks for the other child.
if (child2N < length) {
var child2 = this.content[child2N],
child2Score = this.scoreFunction(child2);
if (child2Score < (swap == null ? elemScore : child1Score)){
swap = child2N;
}
}
// If the element needs to be moved, swap it, and continue.
if (swap != null) {
this.content[n] = this.content[swap];
this.content[swap] = element;
n = swap;
}
// Otherwise, we are done.
else {
break;
}
}
}
};
this.kdTree = kdTree;
exports.kdTree = kdTree;
exports.BinaryHeap = BinaryHeap;
}));
Raw
purview.json
{
"commits": [
{
"sha": "e928842427adf3a91ea2c4f3a7cc13b19d093196",
"name": "final version"
},
{
"sha": "13a81dd0035c3cda3c76166e881f8c7d00e1531d",
"name": "extra_experiment"
},
{
"sha": "b8bdf6815874d5d14129b2f8b8d3bf0bdcaba568",
"name": "Iteration4"
},
{
"sha": "0c21b83bbb978e88ef6af94757fd52f5296c7d25",
"name": "Iteration3"
},
{
"sha": "d132abb4b6339012ec531f80451a2402365a9b98",
"name": "Iteration2"
},
{
"sha": "618b3b1db823dfdc53af05acfb597dd5bab203b8",
"name": "Iteration1"
}
]
}
Raw
sample_images.json
[
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{"right_eye": [[0.5669913111895505, -0.8175985529301849], [0.8042524498506649, -0.9297693884966264], [1.0501467785627774, -0.9008754876192222], [1.2347879024803765, -0.7559349109169072], [1.0350538547476638, -0.7485936676187326], [0.8003766095921957, -0.7537614546300253]], "left_eyebrow": [[-1.6309647234043476, -1.2299254808273112], [-1.3074323193297848, -1.5280293870641748], [-0.9403235277814689, -1.6725595265477258], [-0.5520725158726878, -1.7109681270101866], [-0.17891442777902022, -1.5970949074721579]], "chin": [[-2.560159004441164, -0.6164512882515883], [-2.4419388723293705, -0.12078679056889419], [-2.3237187402175774, 0.3748777071138002], [-2.170555410683029, 0.8830512351059617], [-1.8862524815084556, 1.300196147892147], [-1.4820270362505021, 1.6025863316062445], [-1.0165483861980351, 1.788929839495431], [-0.5273436222794566, 1.964056263827973], [-0.035554964855231685, 2.021844065582781], [0.41265730509523957, 1.9260581005842765], [0.7474067927264463, 1.6516803082135243], [1.0485050296877203, 1.3061241742444376], [1.2797168718034835, 0.9355499796564165], [1.429825235517091, 0.5162316105833493], [1.5087552576323644, 0.1305644921802145], [1.5639591658815262, -0.24388554266627616], [1.5492766792851769, -0.6433536381317015]], "right_eyebrow": [[0.5350424444912053, -1.4991961212833014], [0.7947377502656083, -1.56391472911752], [1.110518473823232, -1.5100027676211814], [1.353828909029698, -1.363770244166043], [1.4897258584622508, -1.1377261890615726]], "left_eye": [[-1.191796080723638, -0.9150262668037465], [-0.9420259117530563, -1.0621402997929439], [-0.6724054691748325, -1.044463482472184], [-0.4528211478344778, -0.8870138754604014], [-0.7000074232994133, -0.8572384650489384], [-0.9696278658776372, -0.8749152823696983]], "nose_bridge": [[0.2326522607771081, -1.0949706760253477], [0.25121058763192694, -0.8715105144265235], [0.2934950283528572, -0.6592674363843436], [0.34699655263043166, -0.42329824447605224]], "bottom_lip": [[0.8556411529378879, 0.4683689456323621], [0.6705895918015246, 0.8751782843959621], [0.4083103925214754, 1.0572355148079147], [0.1723412006131841, 1.1107370390854892], [-0.07355312809892828, 1.081843138208085], [-0.5165976110381071, 0.9429518580511216], [-1.0006345879453928, 0.5331481885631111], [-0.8608617982543706, 0.5831843098009803], [-0.011007976551591858, 0.9071271510943072], [0.21245218504723226, 0.8885688242394882], [0.4596384605121678, 0.8587934138280252], [0.7495196139167979, 0.4895111659928272]], "nose_tip": [[-0.25866532433182204, -0.10792795813719287], [-0.03649710948582112, -0.06781697370314466], [0.2081052724734681, 0.019746238463126495], [0.38540515309289247, -0.03504723256727112], [0.5627050337123167, -0.08984070359766869]], "top_lip": [[-1.0006345879453928, 0.5331481885631111], [-0.5498384244892753, 0.3200236009868722], [-0.07660809391986935, 0.15435124114285628], [0.14556012092613158, 0.1944622255769045], [0.36902028252495567, 0.17590389872208567], [0.6610748922164679, 0.2410329437750685], [0.8556411529378879, 0.4683689456323621], [0.7495196139167979, 0.4895111659928272], [0.3427102751531979, 0.30445960485646395], [0.09552399968826236, 0.3342350152679269], [-0.11542713160109441, 0.3178501446999902], [-0.8608617982543706, 0.5831843098009803]], "transform": {"center": [166.15277777777777, 177.93055555555554], "scale": 38.103839503080835, "angle": 0.44163034041047217}},
{"right_eye": [[0.4151434248116892, -0.9747116017375426], [0.6164530502082548, -1.1177643511780764], [0.840374908534021, -1.115304567222966], [1.0812559415566874, -1.0037103832211225], [0.8629871414632213, -0.9697920338273219], [0.6083402080208444, -0.9302206262012211]], "left_eyebrow": [[-1.3575459734645086, -1.5933991816579023], [-1.228992614765765, -1.7251458146338354], [-1.04710194802121, -1.753411105795336], [-0.8118739732308435, -1.6781950551424039], [-0.6437492069059991, -1.5552947546759603]], "chin": [[-1.2808629421674176, -0.8601834564473818], [-1.3278137016588496, -0.44306481491246047], [-1.3020081944524593, -0.037252289842139324], [-1.1977933623159471, 0.3936322521124927], [-1.0208222634816126, 0.8132106776025245], [-0.8438511646472786, 1.2327891030925562], [-0.6361549906963333, 1.6103363370013768], [-0.39208068339647717, 1.9822305126778974], [0.0056189994864335735, 2.1439687304483623], [0.47853473302227667, 2.070478973428461], [0.9595633087455303, 1.8094454914317046], [1.3565295013063619, 1.4869618592017262], [1.7001583858213816, 1.0609968851573148], [1.8926216787084575, 0.6212660106931931], [2.001022588433111, 0.1200849859958496], [2.109423498157765, -0.381096038701494], [2.139415082952296, -0.9073490802831485]], "right_eyebrow": [[0.17918195969924341, -1.5341495023909184], [0.5316571767237532, -1.6634363514117416], [0.8954385102128634, -1.7199669337347425], [1.2511070015145629, -1.5889537910808884], [1.5146002674664296, -1.331847073683401]], "left_eye": [[-1.127237566584363, -1.0703394143534375], [-0.9986842078856193, -1.2020860473293709], [-0.7691092913275532, -1.1632481300253494], [-0.5589533334214976, -1.009622754442295], [-0.7828751917472637, -1.0120825383974055], [-1.0067970500730299, -1.0145423223525156]], "nose_bridge": [[-0.23720319151359864, -1.096878411881907], [-0.28980700923733055, -0.7161379036958966], [-0.3424108269610625, -0.3353973955098862], [-0.3642895695681836, 0.0033119210949131075]], "bottom_lip": [[1.0220062622897037, 0.5330175499426296], [0.6702645355872733, 1.1465262489638959], [0.21996103498063055, 1.3655285393794412], [-0.07106403181065749, 1.410753005237842], [-0.3426701399499349, 1.3411900128172096], [-0.6481945974830128, 1.0533582203031115], [-0.8898091208277586, 0.4575421863008249], [-0.7693686043164254, 0.5133392783017465], [-0.34586341422712463, 1.0808900211425327], [-0.07991036432014736, 1.1140748802142542], [0.18038962735452982, 1.1108816059370643], [0.9492499955918816, 0.5443236664072298]], "nose_tip": [[-0.6189365030105607, 0.042883328721013844], [-0.4815368118023271, 0.20781482076866853], [-0.24630883701196074, 0.283030871421601], [-0.0029680200341839318, 0.1707031970976782], [0.209647721826982, 0.10040671435496656]], "top_lip": [[-0.8898091208277586, 0.4575421863008249], [-0.6771933789665927, 0.38724570355811316], [-0.4112403290596155, 0.42043056262983447], [-0.14528727915263823, 0.4536154217015558], [0.1457377876386498, 0.40839095584315493], [0.5935815042901821, 0.4133105237533757], [1.0220062622897037, 0.5330175499426296], [0.9492499955918816, 0.5443236664072298], [0.12631882898663913, 0.5231784141221881], [-0.17035929603694905, 0.5320247466316779], [-0.39993421259501527, 0.49318682932765656], [-0.7693686043164254, 0.5133392783017465]], "transform": {"center": [388.7916666666667, 118.43055555555556], "scale": 27.163027335191224, "angle": 0.15416410878170614}}
],
"url": "z_selfie.jpg"}
]
Raw
sketch.js
// recent work from my @VicUniWgtn 3rd year media design students that combines @nulhom's dlib face library with @p5xjs
var canvasWidth = 960;
var canvasHeight = 500;
var button;
var curRandomSeed;
var mainFace;
var faceImages = [];
var curFaceIndex = 0;
var curTrainIndex = 0;
var curValidIndex = 0;
var main_canvas;
var faceSelector;
var drawFaceCheckbox;
var faceGuideCheckbox;
var facePointsCheckbox;
var sliders = [];
var NUM_SLIDERS = 12;
var sliderTint;
var selfieData = []
var trainData = {}
var trainDataKeys = []
var trainValues = {}
var validData = {}
var validDataKeys = []
var faceMapping = null;
var loadedSelfieData = [];
function preload () {
loadedSelfieData = loadJSON('sample_images.json');
trainData = loadJSON('training_images.json');
trainValues = loadJSON('training_values.json');
validData = loadJSON('testing_images.json');
}
var allEmbeddingsTree;
var allEmbeddings = [];
var embeddingDimensions;
var curNeighbors = [];
function squaredDistance(a, b) {
var sum = 0;
var length = 128;
for(var i=0; i<128; i++) {
var diff = a[i] - b[i];
sum += diff * diff;
}
// print(a.length,diff);
// print(sum, a==b);
return sum;
}
var haveStarted = false;
function setup () {
var loadedSelfieDataArray = Object.values(loadedSelfieData);
Array.prototype.unshift.apply(selfieData, loadedSelfieDataArray);
// create the drawing canvas, save the canvas element
main_canvas = createCanvas(canvasWidth, canvasHeight);
main_canvas.parent('canvasContainer');
curRandomSeed = int(focusedRandom(0, 100));
mainFace = new Face();
littleFace = new Face();
for(var i=0; i<selfieData.length; i++) {
var data = selfieData[i];
data.image = loadImage(data.url);
}
trainDataKeys = Object.keys(trainData);
for(var i=0; i<trainDataKeys.length; i++) {
var curKey = trainDataKeys[i];
var data = trainData[curKey];
var curEmbedding = data.embedding[0];
if(curEmbedding.length == 128) {
curEmbedding.push(curKey);
allEmbeddings.push(curEmbedding);
}
else {
print("rejected embedding ", curEmbedding);
}
data.image = loadImage(data.url);
}
validDataKeys = Object.keys(validData);
for(var i=0; i<validDataKeys.length; i++) {
var curKey = validDataKeys[i];
var data = validData[curKey];
data.image = loadImage(data.url);
}
// print("Length: ", allEmbeddings.length);
// setup k-d tree
var N = allEmbeddings[0].length - 1;
embeddingDimensions = Array.apply(null, {length: N}).map(Number.call, Number);
// print(embeddingDimensions)
allEmbeddingsTree = new kdTree(allEmbeddings, squaredDistance, embeddingDimensions);
// print(allEmbeddingsTree)
faceSelector = createSelect();
faceSelector.option('Faces');
faceSelector.option('Train');
faceSelector.option('NearestNeighbors');
faceSelector.option('TrainingQuiz');
faceSelector.option('InterpolationQuiz');
faceSelector.value('Faces');
faceSelector.parent('selector1Container');
/* create the sliders */
for(i=1; i<=NUM_SLIDERS; i++) {
var slider = createSlider(0, 100, 50);
var parentStr = 'slider' + i + 'Container';
slider.parent(parentStr);
sliders.push(slider);
}
drawFaceCheckbox = createCheckbox('', true);
drawFaceCheckbox.parent('checkbox1Container');
faceGuideCheckbox = createCheckbox('', false);
faceGuideCheckbox.parent('checkbox2Container');
facePointsCheckbox = createCheckbox('', false);
facePointsCheckbox.parent('checkbox3Container');
sliderTint = createSlider(0, 100, 10);
sliderTint.parent("sliderTintContainer");
/* and the buttons */
var loadButton = createButton('load');
loadButton.mousePressed(loadCurrentSettings);
loadButton.parent('button1Container');
var interpButton = createButton('interpolate');
interpButton.mousePressed(interpolateCurrent);
interpButton.parent('button1Container');
var saveButton = createButton('save');
saveButton.mousePressed(saveCurrentSettings);
saveButton.parent('button2Container');
var getValuesButton = createButton('get values');
getValuesButton.mousePressed(getSingleJson);
getValuesButton.parent('button3Container');
var randButton = createButton('get all values');
randButton.mousePressed(getAllJson);
randButton.parent('button4Container');
updateSlidersForTraining();
// rotation in degrees
angleMode(DEGREES);
haveStarted = true;
}
function saveCurrentSettings() {
var curKey = trainDataKeys[curTrainIndex];
obj = mainFace.getProperties();
trainValues[curKey] = obj;
// for(var i=0; i<obj.length; i++) {
// trainData[curKey][i] = obj[i];
// }
var text = select('#output');
text.html("Storing values for " + curKey);
// getAllJson();
}
function getSingleJson() {
obj = mainFace.getProperties();
var text = select('#output');
var json = JSON.stringify(obj, null, 2);
text.html(json)
}
function getAllJson() {
obj = trainValues;
var text = select('#output');
var json = JSON.stringify(obj, null, 2);
// alert(json);
text.html(json)
}
// global variables for colors
var bg_color1 = [50, 50, 50];
var lastSwapTime = 0;
var millisPerSwap = 5000;
function changeRandomSeed() {
curRandomSeed = curRandomSeed + 1;
lastSwapTime = millis();
}
function mouseClicked() {
// changeRandomSeed();
}
var quiz_done = false;
var guessed_answer = 0;
function draw () {
var mode = faceSelector.value();
if(millis() > lastSwapTime + millisPerSwap) {
lastSwapTime = millis();
// changeRandomSeed();
}
resetFocusedRandom(curRandomSeed);
noStroke();
background(bg_color1);
var textDisplay = "unknown";
var params = [];
for(var i=0; i<NUM_SLIDERS; i++) {
params.push(sliders[i].value());
}
if (mode == 'Faces' || mode == 'FacePair' || mode == 'Train') {
var do_train = (mode == 'Train');
var is_face = (mode == 'Faces');
var show_face_guide = faceGuideCheckbox.checked();
var show_face_points = facePointsCheckbox.checked();
var do_draw_face = drawFaceCheckbox.checked();
if(do_train) {
// var keys = Object.keys(trainData);
var curKey = trainDataKeys[curTrainIndex];
var data = trainData[curKey];
}
else {
var data = selfieData[curFaceIndex];
}
// Displays the image at its actual size at point (0,0)
var img = data.image
if (is_face) {
x2 = 0;
y1 = 0;
x1 = 0;
var im_w = 960;
var im_h = 500;
var rect_w = 960;
var rect_h = 540;
image(img, x2, y1, im_w, im_h);
var is_face = true;
}
else {
var x1 = (width/4-400/2);
var x2 = (3*width/4-400/2);
var y1 = (height/2-400/2);
var rect_w = 400;
var rect_h = 400;
var im_w = 400;
var im_h = 400;
image(img, x1, y1, 400, 400);
var is_face = false;
}
if(do_train) {
if (curKey in trainValues) {
fill(0, 200, 0);
}
else {
fill(200, 0, 0);
}
ellipse(x1+400/2, y1+400+15, 10, 10);
}
noStroke();
var curSliderTintValue = sliderTint.value();
var overlayAlpha = map(curSliderTintValue, 0, 100, 255, 0);
fill(bg_color1[0], bg_color1[1], bg_color1[2], overlayAlpha);
rect(x2, y1, rect_w, rect_h);
stroke(0);
fill(255);
for(var i=0; i<data.landmarks.length; i++) {
// get array of face marker positions [x, y] format
var positions = data.landmarks[i];
var shifted_positions = JSON.parse(JSON.stringify(positions))
var data_mean = [0.0, 0.0];
var data_scale = 1.0;
var data_angle = 0.0;
if ('transform' in positions) {
data_mean = positions.transform.center;
data_scale = positions.transform.scale;
data_angle = positions.transform.angle;
delete shifted_positions.transform
}
var scale_x = im_w / img.width;
var scale_y = im_h / img.height;
push();
translate(x1, y1)
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
stroke(0);
fill(255);
strokeWeight(1/data_scale);
Object.keys(positions).forEach(function(key) {
if (key=='transform') {
return;
}
var curSection = positions[key];
var shiftedSection = shifted_positions[key];
for (var i=0; i<curSection.length; i++) {
var cur_x = curSection[i][0];
var cur_y = curSection[i][1];
if (show_face_points) {
ellipse(cur_x, cur_y, 5/data_scale, 5/data_scale);
}
// get ready for drawing the face
shiftedSection[i][0] = cur_x;
shiftedSection[i][1] = cur_y;
}
});
noFill();
if(show_face_guide) {
stroke(0, 0, 255);
ellipse(0, 0, 4, 4);
line(0, -2, 0, 2);
line(-2, 0, 2, 0);
}
// ellipse(x1+data_mean[0], y1+data_mean[1], 4*data_scale, 4*data_scale);
// line(x1+data_mean[0], y1+data_mean[1]-2*data_scale, x1+data_mean[0], y1+data_mean[1]+2*data_scale);
pop();
var settings = params;
// interpolation
if ((typeof data.embedding !== 'undefined') &&
(data.embedding != null) &&
(data.embedding.length > i) &&
(data.embedding[i] != null) &&
(typeof data.embedding[i].length !== 'undefined') &&
(data.embedding[i].length == 128)) {
var curEmbedding = data.embedding[i];
results = getAverageSettingsFrom(curEmbedding);
trySettings = results[0];
if (typeof trySettings !== 'undefined') {
settings = trySettings;
// print("Using embedding ", i, results)
}
}
push();
translate(x2, y1)
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
strokeWeight(1/data_scale);
mainFace.setProperties(settings);
if (do_draw_face) {
mainFace.draw(shifted_positions);
}
pop();
}
if(do_train) {
textDisplay = "Train: " + curKey;
}
else {
textDisplay = "";
}
}
else if (mode == 'NearestNeighbors') {
// var keys = Object.keys(trainData);
var curKey = trainDataKeys[curTrainIndex];
var data = trainData[curKey];
// Displays the image at its actual size at point (0,0)
var img = data.image
var x1 = (width/4-250/2);
var y1 = (height/3-250/2);
image(img, x1, y1, 250, 250);
if (curKey in trainValues) {
fill(0, 200, 0);
}
else {
fill(200, 0, 0);
}
ellipse(x1+250/2, y1+250+15, 10, 10);
var y2 = (3*height/4-80/2);
for(var i=0; i<4; i++) {
// var keys = Object.keys(trainData);
var curKey = curNeighbors[i];
var nearData = trainData[curKey];
// Displays the image at its actual size at point (0,0)
var img = nearData.image
var x2 = (width/4 - 200 + i*100);
image(img, x2, y2, 80, 80);
}
for(var i=0; i<1; i++) {
// get array of face marker positions [x, y] format
var positions = data.landmarks[i];
var shifted_positions = JSON.parse(JSON.stringify(positions))
var data_mean = [0.0, 0.0];
var data_scale = 1.0;
var data_angle = 0.0;
if ('transform' in positions) {
data_mean = positions.transform.center;
data_scale = positions.transform.scale;
data_angle = positions.transform.angle;
delete shifted_positions.transform
}
var scale_x = 400.0 / img.width;
var scale_y = 400.0 / img.height;
Object.keys(positions).forEach(function(key) {
if (key=='transform') {
return;
}
var curSection = positions[key];
var shiftedSection = shifted_positions[key];
for (var i=0; i<curSection.length; i++) {
var cur_x = curSection[i][0];
var cur_y = curSection[i][1];
// get ready for drawing the face
shiftedSection[i][0] = cur_x;
shiftedSection[i][1] = cur_y;
}
});
var scale_x = 250.0 / img.width;
var scale_y = 250.0 / img.height;
var x2 = (3*width/4-250/2);
push();
translate(x2, y1);
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
strokeWeight(1/data_scale);
mainFace.setProperties(params);
mainFace.draw(shifted_positions);
pop();
var scale_x = 80.0 / img.width;
var scale_y = 80.0 / img.height;
for(var j=0; j<4; j++) {
// var keys = Object.keys(trainData);
var curKey = curNeighbors[j];
var x2 = (3*width/4 - 200 + j*100);
push();
translate(x2, y2);
if (curKey in trainValues) {
var settings = trainValues[curKey]
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
strokeWeight(1/data_scale);
littleFace.setProperties(settings);
littleFace.draw(shifted_positions);
}
else {
noFill();
stroke(100);
rect(10, 10, 70, 70);
}
pop();
}
}
textDisplay = "Neighbors: " + trainDataKeys[curTrainIndex];
}
else if (mode == 'TrainingQuiz' || mode == 'InterpolationQuiz') {
var curKey = trainDataKeys[curTrainIndex];
var data = trainData[curKey];
var valid_mode = false;
if (mode == 'InterpolationQuiz') {
valid_mode = true;
curKey = validDataKeys[curValidIndex];
data = validData[curKey];
}
// Displays the image at its actual size at point (0,0)
var img = data.image
var x1 = (width/2-200/2);
var y1 = (height/3-300/2);
image(img, x1, y1, 200, 200);
if(valid_mode) {
fill(0, 0, 200);
}
else if (curKey in trainValues) {
fill(0, 200, 0);
}
else {
fill(200, 0, 0);
}
ellipse(x1+200/2, y1+200+15, 10, 10);
var y2 = (3*height/5-80/2);
var y3 = (4*height/5-80/2);
/*
for(var i=0; i<4; i++) {
// var keys = Object.keys(trainData);
var curKey = curNeighbors[i];
var nearData = trainData[curKey];
// Displays the image at its actual size at point (0,0)
var img = nearData.image
var x2 = (width/4 - 200 + i*100);
image(img, x2, y2, 80, 80);
}
*/
for(var i=0; i<1; i++) {
// get array of face marker positions [x, y] format
var positions = data.landmarks[i];
var shifted_positions = JSON.parse(JSON.stringify(positions))
var data_mean = [0.0, 0.0];
var data_scale = 1.0;
var data_angle = 0.0;
if ('transform' in positions) {
data_mean = positions.transform.center;
data_scale = positions.transform.scale;
data_angle = positions.transform.angle;
delete shifted_positions.transform
}
var scale_x = 400.0 / img.width;
var scale_y = 400.0 / img.height;
Object.keys(positions).forEach(function(key) {
if (key=='transform') {
return;
}
var curSection = positions[key];
var shiftedSection = shifted_positions[key];
for (var i=0; i<curSection.length; i++) {
var cur_x = curSection[i][0];
var cur_y = curSection[i][1];
// get ready for drawing the face
shiftedSection[i][0] = cur_x;
shiftedSection[i][1] = cur_y;
}
});
/*
var scale_x = 250.0 / img.width;
var scale_y = 250.0 / img.height;
var x2 = (3*width/4-250/2);
push();
translate(x2, y1);
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
strokeWeight(1/data_scale);
mainFace.setProperties(params);
mainFace.draw(shifted_positions);
pop();
*/
var scale_x = 80.0 / img.width;
var scale_y = 80.0 / img.height;
var otherKeys = Object.keys(trainValues);
var index = otherKeys.indexOf(trainDataKeys[curTrainIndex]);
if(index >= 0) {
otherKeys.splice(index, 1);
}
var answerSlot = int(focusedRandom(0, 4));
var answerKeys = Array(4);
for(var j=0; j<4; j++) {
if(j == answerSlot) {
curKey = trainDataKeys[curTrainIndex];
}
else {
var guess = int(focusedRandom(0, otherKeys.length));
// if(otherKeys.length > j+2) {
// while(answerKeys.indexOf(guess) == -1) {
// guess = int(focusedRandom(0, otherKeys.length));
// }
// }
curKey = otherKeys[guess];
}
answerKeys[j] = curKey;
// print("Answer", j, " is ", curKey);
var x2 = (width/2 - 200 + j*100);
var settings = params;
if (valid_mode && j == answerSlot) {
var curEmbedding = data.embedding[0];
results = getAverageSettingsFrom(curEmbedding);
settings = results[0];
var validTrainKeys = results[1];
}
else if (curKey in trainValues) {
settings = trainValues[curKey];
}
push();
translate(x2, y2);
translate(scale_x*data_mean[0], scale_y*data_mean[1]);
scale(scale_x*data_scale, scale_y*data_scale);
rotate(degrees(data_angle));
strokeWeight(1/data_scale);
if (typeof settings !== 'undefined') {
littleFace.setProperties(settings);
}
littleFace.draw(shifted_positions);
pop();
if(quiz_done && guessed_answer == (j+1)) {
push();
translate(x2, y2);
noFill();
strokeWeight(4);
if(guessed_answer == (answerSlot+1)) {
stroke(0, 100, 0);
}
else {
stroke(100, 0, 0);
}
rect(-10, -10, 100, 100);
pop();
}
}
if(quiz_done) {
for(var j=0; j<4; j++) {
if (valid_mode && (answerSlot+1) == (j+1)) {
for(var k=0; k<4; k++) {
var curKey = validTrainKeys[k];
var nearData = trainData[curKey];
// Displays the image at its actual size at point (0,0)
var img = nearData.image
var x2 = (width/2 - 200 + j*100 + (k%2)*40);
var y4 = y3 + (int(k/2))*40;
image(img, x2, y4, 40, 40);
}
}
else {
var curKey = answerKeys[j];
var nearData = trainData[curKey];
// Displays the image at its actual size at point (0,0)
if (typeof nearData !== 'undefined') {
var img = nearData.image
var x2 = (width/2 - 200 + j*100);
image(img, x2, y3, 80, 80);
}
}
}
}
}
if(valid_mode) {
if(quiz_done) {
textDisplay = "InterpolationQuiz: hit spacebar to continue";
}
else {
textDisplay = "InterpolationQuiz: hit 1, 2, 3, or 4 to guess";
}
}
else {
if(quiz_done) {
textDisplay = "TrainingQuiz: hit spacebar to continue";
}
else {
textDisplay = "TrainingQuiz: hit 1, 2, 3, or 4 to guess";
}
}
}
fill(255);
textSize(32);
textAlign(CENTER);
text(textDisplay, width/2, height-12);
}
function keyTyped() {
if(!haveStarted) {
return;
}
var mode = faceSelector.value();
if (key == 'q' && mode != 'Faces') {
faceSelector.value('Faces');
}
else if (key == 'w' && mode != 'Train') {
faceSelector.value('Train');
}
else if (key == 'e' && mode != 'NearestNeighbors') {
faceSelector.value('NearestNeighbors');
}
else if (key == 'r' && mode != 'TrainingQuiz') {
faceSelector.value('TrainingQuiz');
}
else if (key == 't' && mode != 'InterpolationQuiz') {
faceSelector.value('InterpolationQuiz');
}
if (key == ' ' &&
(mode == 'TrainingQuiz' || mode == 'InterpolationQuiz') && quiz_done) {
quiz_done = false;
if(mode == 'TrainingQuiz') {
curTrainIndex = (curTrainIndex + 1) % trainDataKeys.length;
}
else {
curValidIndex = (curValidIndex + 1) % validDataKeys.length;
}
changeRandomSeed();
}
else if ((mode == 'TrainingQuiz' || mode == 'InterpolationQuiz') && quiz_done == false) {
if(key >= '1' && key <= '4') {
guessed_answer = key - '0';
quiz_done = true;
}
}
if (key == 's') {
saveCurrentSettings();
}
else if (key == 'i') {
interpolateCurrent();
}
else if (key == 'l') {
loadCurrentSettings();
}
if (key == '!') {
saveBlocksImages();
}
else if (key == '@') {
saveBlocksImages(true);
}
}
function interpolateCurrent() {
var curNeighborSettings = [];
for(var i=0; i<4; i++) {
neighborKey = curNeighbors[i]
if(neighborKey in trainValues) {
curNeighborSettings.push(trainValues[neighborKey]);
}
}
for(var i=0; i<NUM_SLIDERS; i++) {
sliders[i].value(50);
}
if(curNeighborSettings.length > 0) {
settings = curNeighborSettings[0];
for(var i=0; i<settings.length; i++) {
var sum = 0;
for(j=0; j<curNeighborSettings.length; j++) {
sum += curNeighborSettings[j][i];
}
var avg = int(sum / curNeighborSettings.length)
sliders[i].value(avg);
}
}
}
function loadCurrentSettings() {
var curKey = trainDataKeys[curTrainIndex];
for(var i=0; i<NUM_SLIDERS; i++) {
sliders[i].value(50);
}
if (curKey in trainValues) {
var settings = trainValues[curKey]
for(var i=0; i<settings.length; i++) {
sliders[i].value(settings[i]);
}
}
}
function updateSlidersForTraining() {
var mode = faceSelector.value();
var curKey = trainDataKeys[curTrainIndex];
// first find the closest neighbors
var nearest = allEmbeddingsTree.nearest(trainData[curKey].embedding[0], 5);
curNeighbors = [];
curNeighborSettings = [];
for(var i=0; i<5; i++) {
if(nearest[i][0][128] != curKey) {
var neighborKey = nearest[i][0][128];
curNeighbors.push(neighborKey);
if(neighborKey in trainValues) {
curNeighborSettings.push(trainValues[neighborKey]);
}
}
}
loadCurrentSettings();
// if(mode == 'NearestNeighbors') {
// interpolateCurrent();
// }
// else {
// loadCurrentSettings();
// }
}
function getAverageSettingsFrom(e) {
// first find the closest neighbors
var nearest = allEmbeddingsTree.nearest(e, 4);
curNeighbors = [];
curNeighborSettings = [];
for(var i=0; i<4; i++) {
var neighborKey = nearest[i][0][128];
curNeighbors.push(neighborKey);
if(neighborKey in trainValues) {
curNeighborSettings.push(trainValues[neighborKey]);
}
}
for(var i=0; i<4; i++) {
neighborKey = curNeighbors[i]
if(neighborKey in trainValues) {
curNeighborSettings.push(trainValues[neighborKey]);
}
}
var trainValueKeys = Object.keys(trainValues);
var props = trainValues[trainValueKeys[0]];
if(curNeighborSettings.length > 0) {
settings = curNeighborSettings[0];
for(var i=0; i<settings.length; i++) {
var sum = 0;
for(j=0; j<curNeighborSettings.length; j++) {
sum += curNeighborSettings[j][i];
}
var avg = int(sum / curNeighborSettings.length)
props[i] = avg;
}
}
return [props, curNeighbors];
}
function keyPressed() {
if(!haveStarted) {
return;
}
var mode = faceSelector.value();
if (mode == 'Faces') {
if (keyCode == LEFT_ARROW || keyCode == UP_ARROW) {
curFaceIndex = (curFaceIndex + selfieData.length - 1) % selfieData.length;
} else if (keyCode === RIGHT_ARROW || keyCode == DOWN_ARROW) {
curFaceIndex = (curFaceIndex + 1) % selfieData.length;
}
}
else if (mode == 'Train' || mode == 'NearestNeighbors') {
if (keyCode == LEFT_ARROW || keyCode == UP_ARROW) {
curTrainIndex = (curTrainIndex + trainDataKeys.length - 1) % trainDataKeys.length;
updateSlidersForTraining();
} else if (keyCode == RIGHT_ARROW || keyCode == DOWN_ARROW) {
curTrainIndex = (curTrainIndex + 1) % trainDataKeys.length;
updateSlidersForTraining();
}
}
}
Raw
testing_images.json
{
"162771": {"landmarks": [{"chin": [[-1.607575262062853, -1.0016724859194308], [-1.6351091555381696, -0.5396664325705911], [-1.5394992491248505, -0.07852759428757607], [-1.4131033927393726, 0.38239444022898283], [-1.2869243401203507, 0.8125305247733828], [-1.0378182913791492, 1.2110134442797993], [-0.7583599001987015, 1.5477076600754416], [-0.4175464128403919, 1.8531823183660128], [0.04467644427490394, 1.9115021618134882], [0.5370348400629903, 1.8772473515780308], [1.0280924132523397, 1.6582768415096198], [1.457361282730915, 1.4089539890019627], [1.7938386947601013, 1.0987096478493557], [2.006305091834827, 0.6661887218739381], [2.094977277721549, 0.14217716104786826], [2.1528635136361123, -0.3816175960117454], [2.180180603344973, -0.874409599332744]], "left_eye": [[-1.2385774699298584, -1.0658460310612226], [-1.0549457889291858, -1.2210766035207539], [-0.7776554354132997, -1.1922418874467005], [-0.5606361592429941, -0.9782578640067813], [-0.8067069552538093, -0.9457374839029732], 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Raw
training_images.json
This file has been truncated, but you can view the full file.
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