p5jsCriticalAIPromptBattle

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Sarah Ciston commited on Jun 23, 2024

Commit

e530b52

1 Parent(s): ae852b9

try p5 as instance in module

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Files changed (3) hide show

index.js +32 -12
sketch.html +0 -30
sketch.js +0 -96

index.js CHANGED Viewed

@@ -78,16 +78,36 @@ function renderBox({ box, label }) {
     imageContainer.appendChild(boxElement);
 }
-function setup(){
-    let canvas = createCanvas(200,200)
-    canvas.position(300, 1000);
-    background(200)
-    textSize(20)
-    textAlign(CENTER,CENTER)
-    console.log('p5 loaded')
-}
-function draw(){
-    //
-}

     imageContainer.appendChild(boxElement);
 }
+// function setup(){
+//     let canvas = createCanvas(200,200)
+//     canvas.position(300, 1000);
+//     background(200)
+//     textSize(20)
+//     textAlign(CENTER,CENTER)
+//     console.log('p5 loaded')
+// }
+// function draw(){
+//     //
+// }
+new p5(function(p5){
+    p5.setup = function(){
+        console.log('p5 loaded')
+        let canvas = p5.createCanvas(200,200)
+        canvas.position(300, 1000);
+        p5.background(200)
+        p5.textSize(20)
+        p5.textAlign(CENTER,CENTER)
+        let promptButton = p5.createButton("GO")
+        promptButton.position(0, 340);
+        promptButton.elt.style.fontSize = "15px";
+    }
+    p5.draw = function(){
+        //
+    }
+});

sketch.html DELETED Viewed

@@ -1,30 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8" />
-    <link rel="stylesheet" href="style.css" />
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.4/p5.js"></script>
-    <script src="https://cdnjs.cloudflare.com/ajax/libs/p5.js/1.9.4/addons/p5.sound.min.js"></script>
-    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
-    <title>p5 designed Transformers.js - Object Detection</title>
-</head>
-<body>
-    <h1>Object Detection w/ 🤗 Transformers.js</h1>
-    <label id="container" for="upload">
-        <svg width="25" height="25" viewBox="0 0 25 25" fill="none" xmlns="http://www.w3.org/2000/svg">
-            <path fill="#000"
-                d="M3.5 24.3a3 3 0 0 1-1.9-.8c-.5-.5-.8-1.2-.8-1.9V2.9c0-.7.3-1.3.8-1.9.6-.5 1.2-.7 2-.7h18.6c.7 0 1.3.2 1.9.7.5.6.7 1.2.7 2v18.6c0 .7-.2 1.4-.7 1.9a3 3 0 0 1-2 .8H3.6Zm0-2.7h18.7V2.9H3.5v18.7Zm2.7-2.7h13.3c.3 0 .5 0 .6-.3v-.7l-3.7-5a.6.6 0 0 0-.6-.2c-.2 0-.4 0-.5.3l-3.5 4.6-2.4-3.3a.6.6 0 0 0-.6-.3c-.2 0-.4.1-.5.3l-2.7 3.6c-.1.2-.2.4 0 .7.1.2.3.3.6.3Z">
-            </path>
-        </svg>
-        Click to upload image
-        <label id="example">(or try example)</label>
-    </label>
-    <label id="status">Loading model...</label>
-    <input id="upload" type="file" accept="image/*" />
-    <script src="sketch.js" type="module"></script>
-</body>
-</html>

sketch.js DELETED Viewed

@@ -1,96 +0,0 @@
-// import { pipeline, env } from 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.10.1';
-// // Since we will download the model from the Hugging Face Hub, we can skip the local model check
-// env.allowLocalModels = false;
-// // Reference the elements that we will need
-// const status = document.getElementById('status');
-// const fileUpload = document.getElementById('upload');
-// const imageContainer = document.getElementById('container');
-// const example = document.getElementById('example');
-// const EXAMPLE_URL = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/city-streets.jpg';
-// // Create a new object detection pipeline
-// status.textContent = 'Loading model...';
-// const detector = await pipeline('object-detection', 'Xenova/detr-resnet-50');
-// status.textContent = 'Ready';
-// example.addEventListener('click', (e) => {
-//     e.preventDefault();
-//     detect(EXAMPLE_URL);
-// });
-// fileUpload.addEventListener('change', function (e) {
-//     const file = e.target.files[0];
-//     if (!file) {
-//         return;
-//     }
-//     const reader = new FileReader();
-//     // Set up a callback when the file is loaded
-//     reader.onload = e2 => detect(e2.target.result);
-//     reader.readAsDataURL(file);
-// });
-// // Detect objects in the image
-// async function detect(img) {
-//     imageContainer.innerHTML = '';
-//     imageContainer.style.backgroundImage = `url(${img})`;
-//     status.textContent = 'Analysing...';
-//     const output = await detector(img, {
-//         threshold: 0.5,
-//         percentage: true,
-//     });
-//     status.textContent = '';
-//     output.forEach(renderBox);
-// }
-// // Render a bounding box and label on the image
-// function renderBox({ box, label }) {
-//     const { xmax, xmin, ymax, ymin } = box;
-//     // Generate a random color for the box
-//     const color = '#' + Math.floor(Math.random() * 0xFFFFFF).toString(16).padStart(6, 0);
-//     // Draw the box
-//     const boxElement = document.createElement('div');
-//     boxElement.className = 'bounding-box';
-//     Object.assign(boxElement.style, {
-//         borderColor: color,
-//         left: 100 * xmin + '%',
-//         top: 100 * ymin + '%',
-//         width: 100 * (xmax - xmin) + '%',
-//         height: 100 * (ymax - ymin) + '%',
-//     })
-//     // Draw label
-//     const labelElement = document.createElement('span');
-//     labelElement.textContent = label;
-//     labelElement.className = 'bounding-box-label';
-//     labelElement.style.backgroundColor = color;
-//     boxElement.appendChild(labelElement);
-//     imageContainer.appendChild(boxElement);
-// }
-function setup(){
-    let canvas = createCanvas(200,200)
-    canvas.position(300, 1000);
-    background(200)
-    textSize(20)
-    textAlign(CENTER,CENTER)
-    let promptButton = createButton("GO")
-    promptButton.position(0, 340);
-    promptButton.elt.style.fontSize = "15px";
-    console.log('p5 loaded')
-}
-function draw(){
-    //
-}