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index.html
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8"
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</head>
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<body>
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</svg>
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Click to upload image
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<label id="example">(or try example)</label>
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</label>
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<label id="status">Loading model...</label>
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<input id="upload" type="file" accept="image/*" />
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</html>
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<!-- index.html content here -->
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<!DOCTYPE html>
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<html lang="en">
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<head>
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<meta charset="UTF-8">
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<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<title>Sora Concept: Visual Analyzer (Zero-Shot Image Classification)</title>
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<link rel="stylesheet" href="style.css">
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<script type="module" src="index.js"></script>
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<!-- Import transformers.js -->
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<script type="module">
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import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.7.3';
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</script>
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</head>
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<body>
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<header>
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<div class="header-content">
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<h1>Visual Analyzer (Sora Concept)</h1>
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<a href="https://huggingface.co/spaces/akhaliq/anycoder" target="_blank" class="anycoder-link">Built with anycoder</a>
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</div>
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</header>
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<main>
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<p class="explanation">
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This tool simulates the visual understanding component required for advanced systems like Sora 2. Upload an image and provide candidate labels for zero-shot classification.
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Note: Due to computational limitations, running Sora 2 (Text-to-Video) directly in the browser via transformers.js is not currently feasible. We use a high-speed CLIP model (Xenova/clip-vit-base-patch32) for instant visual analysis.
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</p>
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<section class="controls">
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<h2>1. Settings</h2>
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<div class="device-toggle-container">
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<label for="device-select">Compute Device:</label>
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<select id="device-select">
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<option value="cpu" selected>CPU (WASM)</option>
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<option value="webgpu">GPU (WebGPU) - Requires compatible browser</option>
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</select>
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</div>
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</section>
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<section class="interface-grid">
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<div class="input-panel">
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<h2>2. Input Image & Labels</h2>
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<div class="input-group">
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<label for="image-upload" class="file-label">Choose Image</label>
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<input type="file" id="image-upload" accept="image/*">
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</div>
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<div class="input-group">
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<label for="candidate-labels">Candidate Labels (One per line, max 5 recommended):</label>
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<textarea id="candidate-labels" rows="5" placeholder="e.g., A photo of a dog
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A landscape painting
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A screenshot from a movie"></textarea>
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</div>
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<button id="classify-button" disabled>Loading Model...</button>
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</div>
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<div class="output-panel">
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<h2>3. Analysis Result</h2>
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<div id="image-preview-container">
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<p class="placeholder-text">Image Preview Area</p>
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<img id="image-preview" alt="Uploaded image preview" style="display: none;">
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</div>
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<div id="results-container">
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<p id="status">Ready. Upload an image and provide labels.</p>
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<div id="classification-results">
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<!-- Results injected here -->
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</div>
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</div>
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</div>
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</section>
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</main>
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</body>
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</html>
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