Cat or Dog Classifier

{"name":"Cat or Dog Classifier","description":"Embark on a fun journey to build your very own image classifier that distinguishes between cats and dogs! Utilizing p5.js, you'll learn the basics of machine learning by creating an interactive web app. With engaging visuals and user-friendly controls, this project will help you develop a deeper understanding of programming while creating something truly cool!","photo":null,"view_count":1,"fork_count":0,"expires_at":null,"created_at":"2025-03-22T01:38:42.672716Z","updated_at":"2025-03-22T01:38:42.672717Z","user_id":2,"status":"PRIVATE","parent_id":null,"id":6460,"user":{"username":"gamerc0der","id":2,"password_hash":null,"updated_at":"2023-12-11T22:13:50.357943Z","reset_token_expiry":null,"subscription_status":null,"photo":null,"email":null,"recess_id":"a75a82d5-5ae6-41b7-d20f-788415be036d","created_at":"2023-12-11T22:13:50.357940Z","reset_token":null,"stripe_customer_id":null,"seats":null},"code":{"script.js":"let drawing = false;\n\nlet paths = [];\n\nlet model;\n\nfunction setup() {\n createCanvas(windowWidth, windowHeight);\n background(255); // White background\n createButton('Classify Drawing').position(10, 10).mousePressed(classifyDrawing);\n loadModel();\n}\n\nfunction draw() {\n if (drawing) {\n const point = {\n x: mouseX,\n y: mouseY\n };\n paths[paths.length - 1].push(point);\n }\n\n noFill();\n stroke(0);\n strokeWeight(2);\n for (let path of paths) {\n beginShape();\n for (let point of path) {\n vertex(point.x, point.y);\n }\n endShape();\n }\n}\n\nfunction mousePressed() {\n drawing = true;\n paths.push([]);\n}\n\nfunction mouseReleased() {\n drawing = false;\n}\n\nasync function loadModel() {\n model = await tf.loadLayersModel('path/to/your/model.json');\n}\n\nasync function classifyDrawing() {\n if (!model) {\n alert('Model not loaded yet!');\n return;\n }\n\n // Convert the drawing into a format the model can interpret\n const input = convertDrawingToInput();\n\n // Predict with the model\n const prediction = model.predict(input);\n\n // Determine the result\n prediction.array().then(array => {\n const result = array[0]; // Assuming the model outputs a single array\n alert(`Drawing classified as: ${result[0] > result[1] ? 'Cat' : 'Dog'}`);\n });\n}\n\nfunction convertDrawingToInput() {\n // Convert the drawing on the canvas to a tensor format suitable for the model\n // This is a placeholder function, you will need to implement the conversion logic\n return tf.tensor([0]); // Placeholder tensor\n}\n\n","style.css":"body { margin: 0; }\n\n/* style.css */\nbody { margin: 0; } \ncanvas { display: block; }\nbutton { position: absolute; z-index: 10; }\n","index.html":"\n\n\n \n \n Cat or Dog Classifier\n \n \n\n\n \n\n"},"chat_history":[],"assets":[],"messages_sent":3,"comments":[],"steps":[]}