Mobile Stat Guesser Website
Tạo vào: 18 tháng 10, 2024
Trả lời bằng OpenAI 01 Preview bởi OpenAI01
Tạo vào: 18 tháng 10, 2024
Trả lời bằng OpenAI 01 Preview bởi OpenAI01
Entwickle ein beeindruckendes Tool
Ich denke darüber nach, wie man eine mobile responsive Website gestaltet, die Bildstatistiken analysiert und das Alter, die Größe, das Gewicht, die Muskelmasse sowie die 1RM für Bankdrücken und Kniebeugen schätzt.
Überblick verschaffen
Ich schaue mir an, welche Inhalte kürzlich erlaubt sind, wie z.B. kurze Zitate, und welche nicht, wie z.B. längere Exzerpte oder Anfragen nach spezifischen Textstellen.
Nutze APIs für Bildanalyse
Ich denke darüber nach, wie das Erstellen einer Rückseite für das Alter einer Person komplex ist und oft maschinelles Lernen oder spezielle APIs erfordert. Vorschläge für APIs wie Microsoft's Face API oder Amazon Rekognition zur Bildanalyse sind reizvoll.
Erstellen einer Webseite
Ich bin dabei, eine responsive Mobile-Website mit HTML, CSS und JavaScript zu erstellen. Die Seite muss Bilder hochladen und Schätzwerte anzeigen können.
CSS-Animationen und Übergänge werden verwendet, um die Website anzugleichen. Ein Umrechnungstoggle für kg zu Pfund ist eingebaut.
Natürliche Ästhetik
Die Seite kombiniert Animationen mit ästhetischen Design. Schätzungen wie Alter, Größe, Gewicht und Muskelmasse könnten durch maschinelles Lernen oder externe APIs erfolgen.
Erstellen einer Benutzeroberfläche
Ich entwickle eine Benutzeroberfläche für Stat Guesser, die Datei-Uploads ermöglicht und animierte Ladebildschirme bietet.
Sekundäraktionen bezeichnen
Ich staune, wie viele Rabiate unter dem Begriff "Sekundäraktionen beleidigende Geschrei gegen die Abteilung" fallen könnten. Beispiele? "Deprivieren", "Schicken" und "Schubsen" klingen ziemlich ähnlich.
Struktur und Stil
Ich habe ein HTML-Gerüst mit einem Titel, Button und Ergebnisanzeige erstellt. Es gibt CSS für ein modernes Design und JavaScript für Interaktivität, einschließlich eines Event-Listeners für Bild-Uploads.
Certainly! Below is a fully responsive mobile website built with HTML, CSS, and JavaScript. It features a beautiful design with animations, allows you to upload a picture, and then guesses stats like age, height, weight, muscle mass, and bench and squat 1RM. You can also convert these stats between kilograms and pounds.
index.html
)<!DOCTYPE html> <html lang="en"> <head> <meta charset="UTF-8"> <title>Stat Guesser</title> <meta name="viewport" content="width=device-width, initial-scale=1.0"> <!-- Link to external CSS --> <link rel="stylesheet" href="styles.css"> </head> <body> <div class="container"> <h1>Welcome to Stat Guesser</h1> <p>Upload your picture to get started</p> <div class="upload-area"> <input type="file" id="imageUpload" accept="image/*"> <label for="imageUpload" class="upload-label">Choose Image</label> </div> <div class="result-area" id="resultArea"> <!-- Results will be displayed here --> </div> </div> <!-- Link to external JavaScript --> <script src="script.js"></script> </body> </html>
styles.css
)/* General Styles */ body { margin: 0; font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif; background: linear-gradient(to right, #6a11cb, #2575fc); color: #fff; } .container { text-align: center; padding: 50px 20px; } h1 { font-size: 2.5em; margin-bottom: 10px; animation: fadeInDown 1s; } p { font-size: 1.2em; margin-bottom: 30px; animation: fadeInUp 1s; } /* Upload Area */ .upload-area { position: relative; display: inline-block; } #imageUpload { display: none; } .upload-label { background-color: #fff; color: #6a11cb; padding: 15px 30px; font-size: 1em; border-radius: 50px; cursor: pointer; transition: background-color 0.3s; } .upload-label:hover { background-color: #f0f0f0; } /* Result Area */ .result-area { margin-top: 30px; animation: fadeIn 1s; } .result-area h2 { font-size: 2em; margin-bottom: 20px; } .result-area p { font-size: 1.2em; margin: 10px 0; } #convertBtn { margin-top: 20px; padding: 10px 20px; background-color: #fff; color: #6a11cb; border: none; border-radius: 25px; font-size: 1em; cursor: pointer; transition: background-color 0.3s; } #convertBtn:hover { background-color: #f0f0f0; } /* Animations */ @keyframes fadeInDown { from { opacity: 0; transform: translateY(-20px); } to { opacity: 1; transform: translateY(0); } } @keyframes fadeInUp { from { opacity: 0; transform: translateY(20px); } to { opacity: 1; transform: translateY(0); } } @keyframes fadeIn { from { opacity: 0; } to { opacity: 1; } } /* Responsive Design */ @media (max-width: 600px) { h1 { font-size: 2em; } .upload-label, #convertBtn { padding: 10px 20px; font-size: 0.9em; } p, .result-area p { font-size: 1em; } }
script.js
)document.getElementById('imageUpload').addEventListener('change', function() { var file = this.files[0]; if (file) { // Display loading animation or message var resultArea = document.getElementById('resultArea'); resultArea.innerHTML = '<p>Processing...</p>'; // Create a FormData object var formData = new FormData(); formData.append('image', file); // Send the image to an API for analysis // Replace with actual API endpoint and include your API key securely fetch('https://api.example.com/analyze', { method: 'POST', headers: { 'Authorization': 'Bearer YOUR_API_KEY' }, body: formData }) .then(response => response.json()) .then(data => { // Mock data for demonstration purposes // Remove the following block when integrating with a real API data = { age: 25, height: 180, // in cm weight: 75, // in kg muscleMass: 35, // in kg bench1RM: 100, // in kg squat1RM: 140 // in kg }; // Process the response data var age = data.age; var height = data.height; var weight = data.weight; var muscleMass = data.muscleMass; var bench1RM = data.bench1RM; var squat1RM = data.squat1RM; // Initial unit var unit = 'metric'; // Display the results displayResults(age, height, weight, muscleMass, bench1RM, squat1RM, unit); }) .catch(error => { console.error('Error:', error); resultArea.innerHTML = '<p>Sorry, something went wrong. Please try again.</p>'; }); } }); function displayResults(age, height, weight, muscleMass, bench1RM, squat1RM, unit) { var resultArea = document.getElementById('resultArea'); resultArea.innerHTML = ` <h2>Your Stats</h2> <p>Age: ${age} years</p> <p>Height: ${height} ${unit === 'metric' ? 'cm' : 'inches'}</p> <p>Weight: ${weight} ${unit === 'metric' ? 'kg' : 'lbs'}</p> <p>Muscle Mass: ${muscleMass} ${unit === 'metric' ? 'kg' : 'lbs'}</p> <p>Bench Press 1RM: ${bench1RM} ${unit === 'metric' ? 'kg' : 'lbs'}</p> <p>Squat 1RM: ${squat1RM} ${unit === 'metric' ? 'kg' : 'lbs'}</p> <button id="convertBtn">Convert to ${unit === 'metric' ? 'Imperial' : 'Metric'}</button> `; document.getElementById('convertBtn').addEventListener('click', function() { if (unit === 'metric') { height = (height / 2.54).toFixed(2); // cm to inches weight = (weight * 2.20462).toFixed(2); muscleMass = (muscleMass * 2.20462).toFixed(2); bench1RM = (bench1RM * 2.20462).toFixed(2); squat1RM = (squat1RM * 2.20462).toFixed(2); unit = 'imperial'; } else { height = (height * 2.54).toFixed(2); // inches to cm weight = (weight / 2.20462).toFixed(2); muscleMass = (muscleMass / 2.20462).toFixed(2); bench1RM = (bench1RM / 2.20462).toFixed(2); squat1RM = (squat1RM / 2.20462).toFixed(2); unit = 'metric'; } displayResults(age, height, weight, muscleMass, bench1RM, squat1RM, unit); }); }
HTML: The structure includes a container with a title, a prompt to upload an image, and a result area where the stats will be displayed. The file input is hidden and styled with a label for better user experience.
CSS:
JavaScript:
To make the stat guessing functional, you'll need to integrate with an actual image analysis API. Here are the steps:
Choose an API:
Sign Up and Obtain API Keys:
Update the Fetch Request:
'https://api.example.com/analyze'
with the actual API endpoint.Handle the Response:
Secure Your API Key:
API Keys: Never expose your API keys in client-side JavaScript. Use environment variables on the server side or a proxy server to keep them secure.
HTTPS: Ensure your website is served over HTTPS to encrypt data transmission, especially when handling file uploads.
Error Handling: Improve error messages to guide the user in case something goes wrong.
Loading Indicator: Add a spinner or progress bar while the image is being processed.
Validation: Check the uploaded file type and size before sending it to the API.
Accessibility: Add ARIA labels and ensure the site is navigable via keyboard for better accessibility.
This code provides a foundation for your responsive mobile website with a beautiful design and animations. By integrating with an appropriate image analysis API, you'll be able to guess stats based on the uploaded picture. Remember to handle API keys securely and consider implementing a backend if necessary.
Feel free to customize the styles and functionalities to better suit your preferences!