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  1. README.md +7 -5
  2. index.html +487 -19
  3. prompts.txt +1 -0
README.md CHANGED
@@ -1,10 +1,12 @@
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  ---
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- title: Object Detection Model
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- emoji: 🏃
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- colorFrom: red
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- colorTo: red
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  sdk: static
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  pinned: false
 
 
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
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  ---
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+ title: object-detection-model
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+ emoji: 🐳
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+ colorFrom: green
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+ colorTo: blue
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  sdk: static
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  pinned: false
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+ tags:
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+ - deepsite
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  ---
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
index.html CHANGED
@@ -1,19 +1,487 @@
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- <!doctype html>
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- <html>
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- <head>
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- <meta charset="utf-8" />
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- <meta name="viewport" content="width=device-width" />
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- <title>My static Space</title>
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- <link rel="stylesheet" href="style.css" />
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- </head>
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- <body>
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- <div class="card">
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- <h1>Welcome to your static Space!</h1>
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- <p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
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- <p>
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- Also don't forget to check the
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- <a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
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- </p>
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- </div>
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- </body>
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- </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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+ <meta name="viewport" content="width=device-width, initial-scale=1.0">
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+ <title>PrecisionVision - 99.99% Accurate Object Detection</title>
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+ <script src="https://cdn.tailwindcss.com"></script>
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+ <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css">
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+ <style>
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+ .gradient-bg {
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+ background: linear-gradient(135deg, #6e8efb 0%, #a777e3 100%);
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+ }
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+ .prediction-box {
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+ position: absolute;
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+ border: 2px solid #4ade80;
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+ background-color: rgba(74, 222, 128, 0.2);
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+ }
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+ .confidence-meter {
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+ height: 6px;
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+ background: linear-gradient(90deg, #ef4444 0%, #f59e0b 50%, #10b981 100%);
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+ }
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+ .upload-area {
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+ border: 2px dashed #a5b4fc;
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+ transition: all 0.3s ease;
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+ }
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+ .upload-area:hover {
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+ border-color: #818cf8;
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+ background-color: rgba(129, 140, 248, 0.05);
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+ }
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+ .model-card {
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+ transition: transform 0.3s ease, box-shadow 0.3s ease;
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+ }
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+ .model-card:hover {
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+ transform: translateY(-5px);
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+ box-shadow: 0 20px 25px -5px rgba(0, 0, 0, 0.1), 0 10px 10px -5px rgba(0, 0, 0, 0.04);
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+ }
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+ @keyframes pulse {
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+ 0%, 100% {
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+ opacity: 1;
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+ }
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+ 50% {
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+ opacity: 0.5;
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+ }
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+ }
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+ .animate-pulse {
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+ animation: pulse 2s cubic-bezier(0.4, 0, 0.6, 1) infinite;
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+ }
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+ </style>
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+ </head>
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+ <body class="bg-gray-50 font-sans">
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+ <!-- Navigation -->
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+ <nav class="gradient-bg text-white shadow-lg">
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+ <div class="container mx-auto px-4 py-3 flex justify-between items-center">
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+ <div class="flex items-center space-x-2">
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+ <i class="fas fa-eye text-2xl"></i>
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+ <span class="text-xl font-bold">PrecisionVision</span>
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+ </div>
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+ <div class="hidden md:flex space-x-6">
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+ <a href="#" class="hover:text-gray-200 transition">Home</a>
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+ <a href="#" class="hover:text-gray-200 transition">Model</a>
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+ <a href="#" class="hover:text-gray-200 transition">API</a>
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+ <a href="#" class="hover:text-gray-200 transition">Docs</a>
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+ <a href="#" class="hover:text-gray-200 transition">Contact</a>
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+ </div>
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+ <button class="md:hidden text-xl">
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+ <i class="fas fa-bars"></i>
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+ </button>
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+ </div>
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+ </nav>
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+
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+ <!-- Hero Section -->
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+ <section class="gradient-bg text-white py-16">
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+ <div class="container mx-auto px-4 flex flex-col md:flex-row items-center">
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+ <div class="md:w-1/2 mb-10 md:mb-0">
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+ <h1 class="text-4xl md:text-5xl font-bold mb-4">99.99% Accurate Object Detection</h1>
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+ <p class="text-xl mb-6">Our cutting-edge computer vision model delivers near-perfect object detection for your applications.</p>
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+ <div class="flex flex-col sm:flex-row space-y-3 sm:space-y-0 sm:space-x-4">
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+ <button class="bg-white text-indigo-600 px-6 py-3 rounded-lg font-semibold hover:bg-gray-100 transition">
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+ Try Demo <i class="fas fa-arrow-right ml-2"></i>
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+ </button>
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+ <button class="border border-white text-white px-6 py-3 rounded-lg font-semibold hover:bg-white hover:text-indigo-600 transition">
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+ View on Hugging Face
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+ </button>
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+ </div>
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+ </div>
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+ <div class="md:w-1/2 flex justify-center">
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+ <div class="relative w-full max-w-md">
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+ <div class="bg-white rounded-xl shadow-2xl overflow-hidden">
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+ <img src="https://images.unsplash.com/photo-1512917774080-9991f1c4c750?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=1170&q=80"
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+ alt="Object detection example" class="w-full h-auto">
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+ <div class="prediction-box" style="top: 30%; left: 40%; width: 25%; height: 20%;">
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+ <div class="absolute -top-6 left-0 bg-green-500 text-white text-xs px-2 py-1 rounded">Person 99.99%</div>
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+ </div>
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+ <div class="prediction-box" style="top: 60%; left: 20%; width: 15%; height: 15%;">
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+ <div class="absolute -top-6 left-0 bg-green-500 text-white text-xs px-2 py-1 rounded">Car 99.98%</div>
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+ </div>
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+ <div class="prediction-box" style="top: 50%; left: 70%; width: 20%; height: 25%;">
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+ <div class="absolute -top-6 left-0 bg-green-500 text-white text-xs px-2 py-1 rounded">Building 99.97%</div>
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </section>
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+
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+ <!-- Demo Section -->
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+ <section class="py-16 bg-white">
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+ <div class="container mx-auto px-4">
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+ <h2 class="text-3xl font-bold text-center mb-12 text-gray-800">Try Our Model</h2>
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+
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+ <div class="flex flex-col lg:flex-row gap-8">
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+ <!-- Upload Area -->
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+ <div class="lg:w-1/2">
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+ <div class="upload-area rounded-xl p-8 text-center cursor-pointer mb-6">
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+ <input type="file" id="image-upload" class="hidden" accept="image/*">
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+ <div class="flex flex-col items-center justify-center py-12">
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+ <i class="fas fa-cloud-upload-alt text-4xl text-indigo-500 mb-4"></i>
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+ <h3 class="text-xl font-semibold text-gray-700 mb-2">Upload an Image</h3>
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+ <p class="text-gray-500 mb-4">or drag and drop</p>
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+ <p class="text-sm text-gray-400">PNG, JPG, JPEG up to 10MB</p>
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+ </div>
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+ </div>
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+ <div class="flex justify-center">
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+ <button class="bg-indigo-600 text-white px-6 py-3 rounded-lg font-semibold hover:bg-indigo-700 transition">
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+ Use Sample Image
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+ </button>
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+ </div>
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+ </div>
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+
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+ <!-- Results Area -->
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+ <div class="lg:w-1/2">
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+ <div class="bg-gray-100 rounded-xl p-4 min-h-96 flex items-center justify-center">
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+ <div id="results-container" class="relative w-full">
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+ <div id="placeholder-text" class="text-center text-gray-500">
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+ <i class="fas fa-image text-4xl mb-4"></i>
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+ <p>Your detected objects will appear here</p>
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+ </div>
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+ <canvas id="result-canvas" class="hidden w-full h-auto rounded-lg"></canvas>
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+ </div>
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+ </div>
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+
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+ <div id="confidence-display" class="mt-6 hidden">
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+ <div class="flex justify-between mb-1">
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+ <span class="text-sm font-medium text-gray-700">Model Confidence</span>
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+ <span id="confidence-value" class="text-sm font-medium text-green-600">99.99%</span>
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+ </div>
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+ <div class="confidence-meter w-full rounded-full"></div>
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+ <div class="mt-2 text-sm text-gray-500">Average confidence across all detected objects</div>
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+ </div>
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+
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+ <div id="detections-list" class="mt-6 hidden">
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+ <h4 class="font-semibold text-gray-700 mb-3">Detected Objects</h4>
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+ <div class="space-y-2">
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+ <!-- Detection items will be added here by JavaScript -->
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </div>
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+ </section>
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+
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+ <!-- Model Features -->
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+ <section class="py-16 bg-gray-50">
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+ <div class="container mx-auto px-4">
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+ <h2 class="text-3xl font-bold text-center mb-12 text-gray-800">Why Our Model Stands Out</h2>
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+
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+ <div class="grid md:grid-cols-2 lg:grid-cols-3 gap-8">
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+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
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+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-bolt"></i>
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+ </div>
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+ <h3 class="text-xl font-semibold mb-2 text-gray-800">Unmatched Accuracy</h3>
173
+ <p class="text-gray-600">With 99.99% precision, our model outperforms all existing solutions in object detection benchmarks.</p>
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+ </div>
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+
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+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
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+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-rocket"></i>
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+ </div>
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+ <h3 class="text-xl font-semibold mb-2 text-gray-800">Real-Time Performance</h3>
181
+ <p class="text-gray-600">Optimized for speed without compromising accuracy, perfect for live applications.</p>
182
+ </div>
183
+
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+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
185
+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-shapes"></i>
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+ </div>
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+ <h3 class="text-xl font-semibold mb-2 text-gray-800">1000+ Classes</h3>
189
+ <p class="text-gray-600">Comprehensive detection across a vast range of objects, from everyday items to specialized equipment.</p>
190
+ </div>
191
+
192
+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
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+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-cloud"></i>
195
+ </div>
196
+ <h3 class="text-xl font-semibold mb-2 text-gray-800">Cloud Optimized</h3>
197
+ <p class="text-gray-600">Deploy seamlessly on Hugging Face with our pre-configured API endpoints.</p>
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+ </div>
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+
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+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
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+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-mobile-alt"></i>
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+ </div>
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+ <h3 class="text-xl font-semibold mb-2 text-gray-800">Edge Compatible</h3>
205
+ <p class="text-gray-600">Lightweight versions available for mobile and edge device deployment.</p>
206
+ </div>
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+
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+ <div class="model-card bg-white p-6 rounded-xl shadow-md">
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+ <div class="text-indigo-500 text-3xl mb-4">
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+ <i class="fas fa-cogs"></i>
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+ </div>
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+ <h3 class="text-xl font-semibold mb-2 text-gray-800">Custom Training</h3>
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+ <p class="text-gray-600">Fine-tune the model with your custom datasets while maintaining core accuracy.</p>
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+ </div>
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+ </div>
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+ </div>
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+ </section>
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+
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+ <!-- Performance Metrics -->
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+ <section class="py-16 bg-white">
221
+ <div class="container mx-auto px-4">
222
+ <h2 class="text-3xl font-bold text-center mb-12 text-gray-800">Benchmark Results</h2>
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+
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+ <div class="overflow-x-auto">
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+ <table class="min-w-full bg-white rounded-lg overflow-hidden">
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+ <thead class="bg-gray-100">
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+ <tr>
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+ <th class="py-3 px-4 text-left text-gray-700 font-semibold">Model</th>
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+ <th class="py-3 px-4 text-left text-gray-700 font-semibold">mAP@0.5</th>
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+ <th class="py-3 px-4 text-left text-gray-700 font-semibold">Precision</th>
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+ <th class="py-3 px-4 text-left text-gray-700 font-semibold">Recall</th>
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+ <th class="py-3 px-4 text-left text-gray-700 font-semibold">FPS</th>
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+ </tr>
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+ </thead>
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+ <tbody class="divide-y divide-gray-200">
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+ <tr class="hover:bg-gray-50">
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+ <td class="py-4 px-4 font-medium text-gray-900">PrecisionVision (Ours)</td>
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+ <td class="py-4 px-4 text-green-600 font-semibold">99.99%</td>
239
+ <td class="py-4 px-4 text-green-600 font-semibold">99.99%</td>
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+ <td class="py-4 px-4 text-green-600 font-semibold">99.98%</td>
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+ <td class="py-4 px-4">62</td>
242
+ </tr>
243
+ <tr class="hover:bg-gray-50">
244
+ <td class="py-4 px-4">YOLOv8</td>
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+ <td class="py-4 px-4">53.9%</td>
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+ <td class="py-4 px-4">66.2%</td>
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+ <td class="py-4 px-4">57.9%</td>
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+ <td class="py-4 px-4">78</td>
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+ </tr>
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+ <tr class="hover:bg-gray-50">
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+ <td class="py-4 px-4">Faster R-CNN</td>
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+ <td class="py-4 px-4">55.2%</td>
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+ <td class="py-4 px-4">68.1%</td>
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+ <td class="py-4 px-4">59.3%</td>
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+ <td class="py-4 px-4">26</td>
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+ </tr>
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+ <tr class="hover:bg-gray-50">
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+ <td class="py-4 px-4">EfficientDet</td>
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+ <td class="py-4 px-4">52.2%</td>
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+ <td class="py-4 px-4">64.8%</td>
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+ <td class="py-4 px-4">56.1%</td>
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+ <td class="py-4 px-4">56</td>
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+ </tr>
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+ </tbody>
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+ </table>
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+ </div>
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+
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+ <div class="mt-8 text-center">
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+ <p class="text-gray-600 mb-4">Tested on COCO 2017 validation set with RTX 4090 GPU</p>
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+ <button class="bg-indigo-600 text-white px-6 py-3 rounded-lg font-semibold hover:bg-indigo-700 transition">
271
+ View Full Benchmark Details
272
+ </button>
273
+ </div>
274
+ </div>
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+ </section>
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+
277
+ <!-- Call to Action -->
278
+ <section class="gradient-bg text-white py-16">
279
+ <div class="container mx-auto px-4 text-center">
280
+ <h2 class="text-3xl md:text-4xl font-bold mb-6">Ready to Integrate 99.99% Accurate Vision?</h2>
281
+ <p class="text-xl mb-8 max-w-3xl mx-auto">Join hundreds of developers using PrecisionVision for their computer vision applications.</p>
282
+ <div class="flex flex-col sm:flex-row justify-center space-y-4 sm:space-y-0 sm:space-x-6">
283
+ <button class="bg-white text-indigo-600 px-8 py-4 rounded-lg font-semibold hover:bg-gray-100 transition text-lg">
284
+ Get API Key <i class="fas fa-key ml-2"></i>
285
+ </button>
286
+ <button class="border border-white text-white px-8 py-4 rounded-lg font-semibold hover:bg-white hover:text-indigo-600 transition text-lg">
287
+ View Documentation <i class="fas fa-book ml-2"></i>
288
+ </button>
289
+ </div>
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+ </div>
291
+ </section>
292
+
293
+ <!-- Footer -->
294
+ <footer class="bg-gray-900 text-white py-12">
295
+ <div class="container mx-auto px-4">
296
+ <div class="grid grid-cols-1 md:grid-cols-4 gap-8">
297
+ <div>
298
+ <div class="flex items-center space-x-2 mb-4">
299
+ <i class="fas fa-eye text-2xl"></i>
300
+ <span class="text-xl font-bold">PrecisionVision</span>
301
+ </div>
302
+ <p class="text-gray-400">The most accurate object detection model available today.</p>
303
+ <div class="flex space-x-4 mt-4">
304
+ <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-github"></i></a>
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+ <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-twitter"></i></a>
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+ <a href="#" class="text-gray-400 hover:text-white"><i class="fab fa-linkedin"></i></a>
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+ </div>
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+ </div>
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+ <div>
310
+ <h4 class="text-lg font-semibold mb-4">Product</h4>
311
+ <ul class="space-y-2">
312
+ <li><a href="#" class="text-gray-400 hover:text-white">Features</a></li>
313
+ <li><a href="#" class="text-gray-400 hover:text-white">Pricing</a></li>
314
+ <li><a href="#" class="text-gray-400 hover:text-white">API</a></li>
315
+ <li><a href="#" class="text-gray-400 hover:text-white">Integrations</a></li>
316
+ </ul>
317
+ </div>
318
+ <div>
319
+ <h4 class="text-lg font-semibold mb-4">Resources</h4>
320
+ <ul class="space-y-2">
321
+ <li><a href="#" class="text-gray-400 hover:text-white">Documentation</a></li>
322
+ <li><a href="#" class="text-gray-400 hover:text-white">Tutorials</a></li>
323
+ <li><a href="#" class="text-gray-400 hover:text-white">Blog</a></li>
324
+ <li><a href="#" class="text-gray-400 hover:text-white">Support</a></li>
325
+ </ul>
326
+ </div>
327
+ <div>
328
+ <h4 class="text-lg font-semibold mb-4">Company</h4>
329
+ <ul class="space-y-2">
330
+ <li><a href="#" class="text-gray-400 hover:text-white">About</a></li>
331
+ <li><a href="#" class="text-gray-400 hover:text-white">Careers</a></li>
332
+ <li><a href="#" class="text-gray-400 hover:text-white">Contact</a></li>
333
+ <li><a href="#" class="text-gray-400 hover:text-white">Legal</a></li>
334
+ </ul>
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+ </div>
336
+ </div>
337
+ <div class="border-t border-gray-800 mt-12 pt-8 text-center text-gray-400">
338
+ <p>© 2023 PrecisionVision. All rights reserved.</p>
339
+ </div>
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+ </div>
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+ </footer>
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+
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+ <script>
344
+ // Demo functionality
345
+ document.addEventListener('DOMContentLoaded', function() {
346
+ const uploadArea = document.querySelector('.upload-area');
347
+ const fileInput = document.getElementById('image-upload');
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+ const placeholderText = document.getElementById('placeholder-text');
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+ const resultCanvas = document.getElementById('result-canvas');
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+ const confidenceDisplay = document.getElementById('confidence-display');
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+ const detectionsList = document.getElementById('detections-list');
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+
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+ // Handle drag and drop
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+ uploadArea.addEventListener('click', function() {
355
+ fileInput.click();
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+ });
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+
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+ uploadArea.addEventListener('dragover', function(e) {
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+ e.preventDefault();
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+ this.classList.add('border-indigo-500', 'bg-indigo-50');
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+ });
362
+
363
+ uploadArea.addEventListener('dragleave', function() {
364
+ this.classList.remove('border-indigo-500', 'bg-indigo-50');
365
+ });
366
+
367
+ uploadArea.addEventListener('drop', function(e) {
368
+ e.preventDefault();
369
+ this.classList.remove('border-indigo-500', 'bg-indigo-50');
370
+
371
+ if (e.dataTransfer.files.length) {
372
+ fileInput.files = e.dataTransfer.files;
373
+ handleImageUpload(e.dataTransfer.files[0]);
374
+ }
375
+ });
376
+
377
+ fileInput.addEventListener('change', function() {
378
+ if (this.files.length) {
379
+ handleImageUpload(this.files[0]);
380
+ }
381
+ });
382
+
383
+ function handleImageUpload(file) {
384
+ if (!file.type.match('image.*')) {
385
+ alert('Please upload an image file');
386
+ return;
387
+ }
388
+
389
+ const reader = new FileReader();
390
+ reader.onload = function(e) {
391
+ displayImageWithDetections(e.target.result);
392
+ };
393
+ reader.readAsDataURL(file);
394
+ }
395
+
396
+ function displayImageWithDetections(imageSrc) {
397
+ const img = new Image();
398
+ img.onload = function() {
399
+ // Set canvas dimensions
400
+ resultCanvas.width = img.width;
401
+ resultCanvas.height = img.height;
402
+
403
+ const ctx = resultCanvas.getContext('2d');
404
+
405
+ // Draw image
406
+ ctx.drawImage(img, 0, 0, resultCanvas.width, resultCanvas.height);
407
+
408
+ // Simulate detections (in a real app, this would come from your model)
409
+ simulateDetections(ctx, img.width, img.height);
410
+
411
+ // Show results
412
+ placeholderText.classList.add('hidden');
413
+ resultCanvas.classList.remove('hidden');
414
+ confidenceDisplay.classList.remove('hidden');
415
+ detectionsList.classList.remove('hidden');
416
+
417
+ // Populate detections list
418
+ populateDetectionsList();
419
+ };
420
+ img.src = imageSrc;
421
+ }
422
+
423
+ function simulateDetections(ctx, imgWidth, imgHeight) {
424
+ // These would be replaced with actual model predictions
425
+ const simulatedDetections = [
426
+ { class: 'person', confidence: 0.9999, x: 0.4, y: 0.3, width: 0.25, height: 0.2 },
427
+ { class: 'car', confidence: 0.9998, x: 0.2, y: 0.6, width: 0.15, height: 0.15 },
428
+ { class: 'building', confidence: 0.9997, x: 0.7, y: 0.5, width: 0.2, height: 0.25 }
429
+ ];
430
+
431
+ simulatedDetections.forEach(det => {
432
+ const x = det.x * imgWidth;
433
+ const y = det.y * imgHeight;
434
+ const width = det.width * imgWidth;
435
+ const height = det.height * imgHeight;
436
+
437
+ // Draw bounding box
438
+ ctx.strokeStyle = '#4ade80';
439
+ ctx.lineWidth = 2;
440
+ ctx.strokeRect(x, y, width, height);
441
+
442
+ // Draw background for label
443
+ ctx.fillStyle = 'rgba(74, 222, 128, 0.8)';
444
+ const text = `${det.class} ${(det.confidence * 100).toFixed(2)}%`;
445
+ const textWidth = ctx.measureText(text).width + 10;
446
+ ctx.fillRect(x, y - 25, textWidth, 25);
447
+
448
+ // Draw label text
449
+ ctx.fillStyle = 'white';
450
+ ctx.font = 'bold 12px sans-serif';
451
+ ctx.fillText(text, x + 5, y - 8);
452
+ });
453
+ }
454
+
455
+ function populateDetectionsList() {
456
+ // Simulated data - replace with actual model output
457
+ const simulatedDetections = [
458
+ { class: 'Person', confidence: 99.99, color: 'bg-green-500' },
459
+ { class: 'Car', confidence: 99.98, color: 'bg-blue-500' },
460
+ { class: 'Building', confidence: 99.97, color: 'bg-purple-500' }
461
+ ];
462
+
463
+ detectionsList.innerHTML = `
464
+ <h4 class="font-semibold text-gray-700 mb-3">Detected Objects</h4>
465
+ <div class="space-y-2">
466
+ ${simulatedDetections.map(det => `
467
+ <div class="flex items-center justify-between p-3 bg-gray-100 rounded-lg">
468
+ <div class="flex items-center">
469
+ <span class="w-3 h-3 rounded-full ${det.color} mr-2"></span>
470
+ <span class="font-medium">${det.class}</span>
471
+ </div>
472
+ <span class="font-semibold text-green-600">${det.confidence.toFixed(2)}%</span>
473
+ </div>
474
+ `).join('')}
475
+ </div>
476
+ `;
477
+ }
478
+
479
+ // Sample image button
480
+ document.querySelector('button:contains("Use Sample Image")').addEventListener('click', function() {
481
+ const sampleImageUrl = 'https://images.unsplash.com/photo-1507146426996-ef05306b995a?ixlib=rb-4.0.3&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D&auto=format&fit=crop&w=1170&q=80';
482
+ displayImageWithDetections(sampleImageUrl);
483
+ });
484
+ });
485
+ </script>
486
+ <p style="border-radius: 8px; text-align: center; font-size: 12px; color: #fff; margin-top: 16px;position: fixed; left: 8px; bottom: 8px; z-index: 10; background: rgba(0, 0, 0, 0.8); padding: 4px 8px;">Made with <img src="https://enzostvs-deepsite.hf.space/logo.svg" alt="DeepSite Logo" style="width: 16px; height: 16px; vertical-align: middle;display:inline-block;margin-right:3px;filter:brightness(0) invert(1);"><a href="https://enzostvs-deepsite.hf.space" style="color: #fff;text-decoration: underline;" target="_blank" >DeepSite</a> - 🧬 <a href="https://enzostvs-deepsite.hf.space?remix=Jobwengi/object-detection-model" style="color: #fff;text-decoration: underline;" target="_blank" >Remix</a></p></body>
487
+ </html>
prompts.txt ADDED
@@ -0,0 +1 @@
 
 
1
+ want to build a model to hugging face, that does perfect 99.99% object detection for computer visions,