Merge branch 'iris-clasification' of s434734/AiForklift into master
This commit is contained in:
commit
7b02c4f746
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iris_model.h5
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BIN
iris_model.h5
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@ -1,68 +1,66 @@
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class Forklift {
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constructor(x, y) {
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this.positoin = createVector(x, y);
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this.speed = 5;
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this.path = [];
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this.currentTarget = '';
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this.targetId = 0;
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this.velocity = createVector(0, 0);
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this.direction = createVector(0, 0);
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this.end = false;
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this.currentSection = 0;
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}
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constructor(x, y) {
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this.positoin = createVector(x, y);
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this.speed = 5;
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this.path = [];
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this.currentTarget = '';
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this.targetId = 0;
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this.velocity = createVector(0, 0);
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this.direction = createVector(0, 0);
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this.end = false;
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this.currentSection = 0;
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}
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draw() {
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fill(225, 255, 0);
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ellipse(this.positoin.x, this.positoin.y, 20);
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}
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draw() {
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fill(225, 255, 0);
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ellipse(this.positoin.x, this.positoin.y, 20);
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}
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setPath(path) {
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this.end = false;
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this.path = path;
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this.currentTarget = this.path[this.targetId];
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this.setVelocity();
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}
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setPath(path) {
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this.end = false;
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this.path = path;
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this.currentTarget = this.path[this.targetId];
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this.setVelocity();
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}
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nextTarget() {
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this.targetId += 1;
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if (this.targetId < this.path.length) {
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this.currentTarget = this.path[this.targetId];
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} else {
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this.end = true;
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this.targetId = 0;
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}
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nextTarget() {
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this.targetId += 1;
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if (this.targetId < this.path.length) {
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this.currentTarget = this.path[this.targetId];
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} else {
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this.end = true;
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this.targetId = 0;
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}
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}
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targetReached() {
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this.currentSection = this.currentTarget;
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return this.end;
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}
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targetReached() {
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this.currentSection = this.currentTarget;
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return this.end;
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}
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setVelocity() {
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debugger;
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this.direction = this.sub(sections[this.currentTarget], this.positoin);
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this.velocity = this.direction.setMag(this.speed);
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}
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setVelocity() {
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this.direction = this.sub(sections[this.currentTarget], this.positoin);
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this.velocity = this.direction.setMag(this.speed);
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}
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move() {
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this.positoin = this.add(this.positoin, this.velocity);
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if (
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Math.abs(this.positoin.x - sections[this.currentTarget].x) <=
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this.speed &&
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Math.abs(this.positoin.y - sections[this.currentTarget].y) <=
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this.speed
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) {
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this.positoin = sections[this.currentTarget];
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this.nextTarget();
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this.setVelocity();
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}
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move() {
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this.positoin = this.add(this.positoin, this.velocity);
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if (
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Math.abs(this.positoin.x - sections[this.currentTarget].x) <=
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this.speed &&
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Math.abs(this.positoin.y - sections[this.currentTarget].y) <= this.speed
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) {
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this.positoin = sections[this.currentTarget];
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this.nextTarget();
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this.setVelocity();
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}
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}
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sub(target, pos) {
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return createVector(target.x - pos.x, target.y - pos.y);
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}
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sub(target, pos) {
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return createVector(target.x - pos.x, target.y - pos.y);
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}
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add(target, pos) {
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return createVector(target.x + pos.x, target.y + pos.y);
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}
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add(target, pos) {
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return createVector(target.x + pos.x, target.y + pos.y);
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}
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}
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@ -1,130 +1,149 @@
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const serverUrl = 'http://localhost:8000';
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let sections;
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let roads;
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let packageClaim;
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let going = false;
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let forklift;
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let target;
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// This runs once at start
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function setup() {
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createCanvas(600, 600).parent('canvas');
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createCanvas(600, 600).parent('canvas');
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frameRate(30);
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frameRate(30);
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createMagazineLayout();
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createMagazineLayout();
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select('#button').mousePressed(deliver);
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target = select('#target');
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// Create a forklift instance
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forklift = new Forklift(sections[0].x, sections[0].y);
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select('#button').mousePressed(getIrisType);
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sepalWidth = select('#sepalWidth');
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sepalLength = select('#sepalLength');
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petalWidth = select('#petalWidth');
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petalLength = select('#petalLength');
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// Create a forklift instance
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forklift = new Forklift(sections[0].x, sections[0].y);
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}
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// This runs every frame
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function draw() {
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background(64);
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drawMagazine();
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forklift.draw();
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if (going) {
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if (forklift.targetReached()) {
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going = false;
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} else {
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forklift.move();
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}
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background(64);
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drawMagazine();
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forklift.draw();
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if (going) {
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if (forklift.targetReached()) {
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going = false;
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} else {
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forklift.move();
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}
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}
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}
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function drawMagazine() {
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noFill();
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stroke(220);
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strokeWeight(10);
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// Draw all the roads in the magazine
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for (let road of roads) {
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line(
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sections[road[0]].x,
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sections[road[0]].y,
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sections[road[1]].x,
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sections[road[1]].y,
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);
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}
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noStroke();
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textAlign(CENTER, CENTER);
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// Draw all sections in the magazine
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for (let section of Object.keys(sections)) {
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if (section === 0) {
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fill(80);
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rect(sections[section].x - 15, sections[section].y, 30, 30);
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} else {
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fill(30);
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ellipse(sections[section].x, sections[section].y, 30);
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fill(255);
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text(section, sections[section].x, sections[section].y);
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}
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noFill();
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stroke(220);
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strokeWeight(10);
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// Draw all the roads in the magazine
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for (let road of roads) {
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line(
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sections[road[0]].x,
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sections[road[0]].y,
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sections[road[1]].x,
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sections[road[1]].y,
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);
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}
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noStroke();
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textAlign(CENTER, CENTER);
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// Draw all sections in the magazine
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for (let section of Object.keys(sections)) {
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if (section === 0) {
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fill(80);
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rect(sections[section].x - 15, sections[section].y, 30, 30);
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} else {
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fill(30);
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ellipse(sections[section].x, sections[section].y, 30);
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fill(255);
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text(section, sections[section].x, sections[section].y);
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}
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}
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}
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function deliver() {
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let data = {
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graph: magazineToGraph(),
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start_node: forklift.currentSection,
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dest_node: int(target.value()),
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};
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httpPost(
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'http://localhost:8000/shortestPath',
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data,
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response => {
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path = response.split('').map(Number);
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forklift.currentTarget = path[0];
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forklift.setPath(path);
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going = true;
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},
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error => {
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console.log(error);
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},
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);
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function getIrisType() {
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let sw = select('#sepalWidth').value();
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let sl = select('#sepalLength').value();
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let pw = select('#petalWidth').value();
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let pl = select('#petalLength').value();
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let data = {
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sepalWidth: sw,
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sepalLength: sl,
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petalWidth: pw,
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petalLength: pl,
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};
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httpPost(serverUrl + '/classify', data, response => {
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deliver(response);
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});
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}
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function deliver(targetSection) {
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let data = {
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graph: magazineToGraph(),
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start_node: forklift.currentSection,
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dest_node: int(targetSection),
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};
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console.log(data);
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httpPost(
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serverUrl + '/shortestPath',
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data,
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response => {
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path = response.split('').map(Number);
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forklift.currentTarget = path[0];
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forklift.setPath(path);
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going = true;
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},
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error => {
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console.log(error);
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},
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);
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}
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function createMagazineLayout() {
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unit = width / 6;
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unit = width / 6;
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sections = {
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0: { x: 2 * unit, y: unit },
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1: createVector(unit, 2 * unit),
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2: createVector(unit, 3 * unit),
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3: createVector(unit, 4 * unit),
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4: createVector(3 * unit, 2 * unit),
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5: createVector(3 * unit, 3 * unit),
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6: createVector(3 * unit, 4 * unit),
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};
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roads = [
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[1, 5],
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[2, 3],
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[0, 1],
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[0, 4],
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[4, 5],
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[5, 6],
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[3, 6],
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[4, 2],
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[5, 3],
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];
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sections = {
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0: { x: 2 * unit, y: unit },
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1: createVector(unit, 2 * unit),
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2: createVector(unit, 3 * unit),
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3: createVector(unit, 4 * unit),
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4: createVector(3 * unit, 2 * unit),
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5: createVector(3 * unit, 3 * unit),
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6: createVector(3 * unit, 4 * unit),
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};
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roads = [
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[1, 5],
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[2, 3],
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[0, 1],
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[0, 4],
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[4, 5],
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[5, 6],
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[3, 6],
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[4, 2],
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[5, 3],
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];
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}
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function magazineToGraph() {
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graph = {};
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for (let key of Object.keys(sections)) {
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graph[key] = {};
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}
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for (let road of roads) {
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start = road[0];
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end = road[1];
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graph[start][end] = Math.sqrt(
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Math.pow(sections[start].x - sections[end].x, 2) +
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Math.pow(sections[start].y - sections[end].y, 2),
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);
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graph[end][start] = Math.sqrt(
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Math.pow(sections[start].x - sections[end].x, 2) +
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Math.pow(sections[start].y - sections[end].y, 2),
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);
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}
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return graph;
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graph = {};
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for (let key of Object.keys(sections)) {
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graph[key] = {};
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}
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for (let road of roads) {
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start = road[0];
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end = road[1];
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graph[start][end] = Math.sqrt(
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Math.pow(sections[start].x - sections[end].x, 2) +
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Math.pow(sections[start].y - sections[end].y, 2),
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);
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graph[end][start] = Math.sqrt(
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Math.pow(sections[start].x - sections[end].x, 2) +
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Math.pow(sections[start].y - sections[end].y, 2),
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);
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}
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return graph;
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}
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@ -42,27 +42,21 @@
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<div class="package">
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<h3 style="margin-top: 0;">Package description</h1>
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<label for="width">Sepal Width</label>
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<input type="number" name="width">
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<input type="number" id="sepalWidth">
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<label for="topWidth">Sepal Length</label>
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<input type="number" name="topWidth">
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<input type="number" id="sepalLength">
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<label for="botWidth">Petal Width</label>
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<input type="number" name="botWidth">
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<input type="number" id="petalWidth">
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<label for="height">Petal Length</label>
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<input type="number" name="height">
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<label for="target">Target</label>
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<input type="number" id="target" name="target">
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<input type="number" id="petalLength">
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<button id="button">Send Package</button>
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</div>
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<div id="canvas" style="margin: 10px;"></div>
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<div class="legend">
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<h3 style="margin-top: 0">Sections</h3>
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<p>A - Cartons</p>
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<p>B - Barrels</p>
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<p>C - Plastic boxes</p>
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<p>D - ______</p>
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<p>E - ______</p>
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<p>F - ______</p>
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<p>G - ______</p>
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<p>1 - Setosa</p>
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<p>2 - Versicolor</p>
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<p>3 - Viginica</p>
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</div>
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</div>
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</body>
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@ -1,10 +1,11 @@
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import math
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import json
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from django.shortcuts import render
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from django.http import HttpResponse
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from django.views.decorators.csrf import csrf_exempt
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import json
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import math
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import tensorflow as tf
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import numpy as np
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# Create your views here.
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@ -14,7 +15,21 @@ def index(request):
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@csrf_exempt
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def classify(request):
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return HttpResponse(json.load(request))
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loaded_request = json.load(request)
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sw = loaded_request['sepalWidth']
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sl = loaded_request['sepalLength']
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pw = loaded_request['petalWidth']
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pl = loaded_request['petalLength']
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model = tf.keras.models.load_model('iris_model.h5')
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output = model.predict(np.array([[sw, sl, pw, pl]]))
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if output[0][0] > output[0][1] and output[0][0] > output[0][1]:
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guess = 1
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elif output[0][1] > output[0][0] and output[0][1] > output[0][2]:
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guess = 2
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else:
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guess = 3
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return HttpResponse(guess)
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@csrf_exempt
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@ -61,4 +76,6 @@ def shortestPath(request):
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current = predecessor[current]
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path[node] = p[::-1]
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print(path)
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return HttpResponse(path[dest_node][1:])
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|
28
train_model.py
Normal file
28
train_model.py
Normal file
@ -0,0 +1,28 @@
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import numpy as np
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import tensorflow as tf
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from sklearn.datasets import load_iris
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from sklearn.model_selection import train_test_split
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from tensorflow.keras import layers
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from tensorflow.keras.utils import to_categorical
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# Getting data
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data_set = load_iris()
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x = data_set['data']
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y = to_categorical(data_set['target'])
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train_x, test_x, train_y, test_y = train_test_split(x, y, test_size=0.2)
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# Building the model
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model = tf.keras.Sequential()
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model.add(layers.Dense(8, activation='relu', input_dim=4))
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model.add(layers.Dense(3, activation='sigmoid'))
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model.compile(optimizer='adam', loss='categorical_crossentropy',
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metrics=['accuracy'])
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# Training the model
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model.fit(train_x, train_y, validation_data=(test_x, test_y), epochs=2000)
|
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|
||||
model.save('iris_model.h5')
|
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Reference in New Issue
Block a user