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objdetect

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Danyray101 commited on May 21

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README.md +7 -5
index.html +573 -19
prompts.txt +0 -0

README.md CHANGED Viewed

@@ -1,10 +1,12 @@
 ---
-title: Objdetect
-emoji: 🌍
-colorFrom: green
-colorTo: blue
 sdk: static
 pinned: false
 ---
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

 ---
+title: objdetect
+emoji: 🐳
+colorFrom: pink
+colorTo: yellow
 sdk: static
 pinned: false
+tags:
+  - deepsite
 ---
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

index.html CHANGED Viewed

@@ -1,19 +1,573 @@
-<!doctype html>
-<html>
-	<head>
-		<meta charset="utf-8" />
-		<meta name="viewport" content="width=device-width" />
-		<title>My static Space</title>
-		<link rel="stylesheet" href="style.css" />
-	</head>
-	<body>
-		<div class="card">
-			<h1>Welcome to your static Space!</h1>
-			<p>You can modify this app directly by editing <i>index.html</i> in the Files and versions tab.</p>
-			<p>
-				Also don't forget to check the
-				<a href="https://huggingface.co/docs/hub/spaces" target="_blank">Spaces documentation</a>.
-			</p>
-		</div>
-	</body>
-</html>

+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Object Detection App</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]/dist/tf.min.js"></script>
+    <script src="https://cdn.jsdelivr.net/npm/@tensorflow-models/[email protected]/dist/coco-ssd.min.js"></script>
+    <style>
+        .video-container {
+            position: relative;
+            display: inline-block;
+        }
+        .canvas-overlay {
+            position: absolute;
+            top: 0;
+            left: 0;
+            pointer-events: none;
+        }
+        .detection-box {
+            position: absolute;
+            border: 2px solid;
+            display: flex;
+            flex-direction: column;
+            align-items: center;
+            justify-content: flex-end;
+        }
+        .detection-label {
+            background-color: rgba(0, 0, 0, 0.7);
+            color: white;
+            padding: 2px 5px;
+            font-size: 12px;
+            border-radius: 4px;
+            margin-bottom: 2px;
+        }
+        .loading-bar {
+            width: 100%;
+            height: 4px;
+            background-color: #e5e7eb;
+            border-radius: 2px;
+            overflow: hidden;
+        }
+        .loading-progress {
+            height: 100%;
+            background-color: #3b82f6;
+            transition: width 0.3s ease;
+        }
+        .toggle-switch {
+            position: relative;
+            display: inline-block;
+            width: 60px;
+            height: 34px;
+        }
+        .toggle-switch input {
+            opacity: 0;
+            width: 0;
+            height: 0;
+        }
+        .slider {
+            position: absolute;
+            cursor: pointer;
+            top: 0;
+            left: 0;
+            right: 0;
+            bottom: 0;
+            background-color: #ccc;
+            transition: .4s;
+            border-radius: 34px;
+        }
+        .slider:before {
+            position: absolute;
+            content: "";
+            height: 26px;
+            width: 26px;
+            left: 4px;
+            bottom: 4px;
+            background-color: white;
+            transition: .4s;
+            border-radius: 50%;
+        }
+        input:checked + .slider {
+            background-color: #3b82f6;
+        }
+        input:checked + .slider:before {
+            transform: translateX(26px);
+        }
+    </style>
+</head>
+<body class="bg-gray-100 min-h-screen">
+    <div class="container mx-auto px-4 py-8">
+        <div class="max-w-4xl mx-auto bg-white rounded-xl shadow-md overflow-hidden">
+            <div class="p-6">
+                <h1 class="text-3xl font-bold text-gray-800 mb-2">Object Detection App</h1>
+                <p class="text-gray-600 mb-6">Detect and label man-made objects using your camera or a video URL</p>
+                <div class="flex flex-col md:flex-row gap-6 mb-6">
+                    <div class="flex-1">
+                        <div class="mb-4">
+                            <label class="block text-gray-700 font-medium mb-2" for="source-select">Detection Source</label>
+                            <select id="source-select" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500">
+                                <option value="camera">Camera</option>
+                                <option value="video-url">Video URL</option>
+                                <option value="file-upload">Upload Video</option>
+                            </select>
+                        </div>
+                        <div id="camera-controls" class="space-y-4">
+                            <div class="flex items-center space-x-4">
+                                <button id="start-camera" class="px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700 transition">Start Camera</button>
+                                <button id="stop-camera" class="px-4 py-2 bg-gray-600 text-white rounded-lg hover:bg-gray-700 transition" disabled>Stop Camera</button>
+                            </div>
+                            <div class="flex items-center space-x-4">
+                                <span class="text-gray-700">Show labels:</span>
+                                <label class="toggle-switch">
+                                    <input type="checkbox" id="show-labels" checked>
+                                    <span class="slider"></span>
+                                </label>
+                            </div>
+                        </div>
+                        <div id="video-url-controls" class="hidden space-y-4">
+                            <div class="mb-4">
+                                <label class="block text-gray-700 font-medium mb-2" for="video-url">Video URL</label>
+                                <input type="text" id="video-url" placeholder="https://example.com/video.mp4" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500">
+                            </div>
+                            <button id="load-video" class="px-4 py-2 bg-blue-600 text-white rounded-lg hover:bg-blue-700 transition">Load Video</button>
+                        </div>
+                        <div id="file-upload-controls" class="hidden space-y-4">
+                            <div class="mb-4">
+                                <label class="block text-gray-700 font-medium mb-2" for="video-upload">Upload Video</label>
+                                <input type="file" id="video-upload" accept="video/*" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500">
+                            </div>
+                        </div>
+                    </div>
+                    <div class="flex-1">
+                        <div class="bg-gray-200 rounded-lg p-4">
+                            <h2 class="text-xl font-semibold text-gray-800 mb-2">Detection Settings</h2>
+                            <div class="space-y-4">
+                                <div>
+                                    <label class="block text-gray-700 font-medium mb-2">Confidence Threshold</label>
+                                    <input type="range" id="confidence-slider" min="0" max="1" step="0.05" value="0.5" class="w-full">
+                                    <div class="flex justify-between text-sm text-gray-600">
+                                        <span>0%</span>
+                                        <span id="confidence-value">50%</span>
+                                        <span>100%</span>
+                                    </div>
+                                </div>
+                                <div>
+                                    <label class="block text-gray-700 font-medium mb-2">Detection Speed</label>
+                                    <select id="speed-select" class="w-full px-4 py-2 border border-gray-300 rounded-lg focus:outline-none focus:ring-2 focus:ring-blue-500">
+                                        <option value="fast">Fast (less accurate)</option>
+                                        <option value="medium" selected>Medium</option>
+                                        <option value="slow">Slow (more accurate)</option>
+                                    </select>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                </div>
+                <div class="mb-6">
+                    <div class="loading-bar mb-2 hidden" id="model-loading-bar">
+                        <div class="loading-progress" id="model-loading-progress" style="width: 0%"></div>
+                    </div>
+                    <p class="text-sm text-gray-600" id="status-message">Click "Start Camera" or load a video to begin detection</p>
+                </div>
+                <div class="video-container mx-auto">
+                    <video id="video" autoplay playsinline muted class="w-full max-h-[500px] bg-gray-900 rounded-lg hidden"></video>
+                    <canvas id="canvas" class="canvas-overlay"></canvas>
+                </div>
+                <div class="mt-6 hidden" id="results-container">
+                    <h2 class="text-xl font-semibold text-gray-800 mb-2">Detection Results</h2>
+                    <div class="bg-gray-100 rounded-lg p-4">
+                        <div class="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4" id="detection-results">
+                            <!-- Detection results will be added here -->
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </div>
+    <script>
+        // DOM elements
+        const sourceSelect = document.getElementById('source-select');
+        const cameraControls = document.getElementById('camera-controls');
+        const videoUrlControls = document.getElementById('video-url-controls');
+        const fileUploadControls = document.getElementById('file-upload-controls');
+        const startCameraBtn = document.getElementById('start-camera');
+        const stopCameraBtn = document.getElementById('stop-camera');
+        const loadVideoBtn = document.getElementById('load-video');
+        const videoUrlInput = document.getElementById('video-url');
+        const videoUploadInput = document.getElementById('video-upload');
+        const videoElement = document.getElementById('video');
+        const canvasElement = document.getElementById('canvas');
+        const confidenceSlider = document.getElementById('confidence-slider');
+        const confidenceValue = document.getElementById('confidence-value');
+        const speedSelect = document.getElementById('speed-select');
+        const showLabelsToggle = document.getElementById('show-labels');
+        const statusMessage = document.getElementById('status-message');
+        const modelLoadingBar = document.getElementById('model-loading-bar');
+        const modelLoadingProgress = document.getElementById('model-loading-progress');
+        const resultsContainer = document.getElementById('results-container');
+        const detectionResults = document.getElementById('detection-results');
+        // App state
+        let model = null;
+        let isDetecting = false;
+        let detectionInterval = null;
+        let stream = null;
+        let showLabels = true;
+        let confidenceThreshold = 0.5;
+        let detectionSpeed = 'medium';
+        // Initialize the app
+        init();
+        function init() {
+            // Event listeners
+            sourceSelect.addEventListener('change', handleSourceChange);
+            startCameraBtn.addEventListener('click', startCamera);
+            stopCameraBtn.addEventListener('click', stopCamera);
+            loadVideoBtn.addEventListener('click', loadVideoFromUrl);
+            videoUploadInput.addEventListener('change', handleVideoUpload);
+            confidenceSlider.addEventListener('input', updateConfidenceThreshold);
+            speedSelect.addEventListener('change', updateDetectionSpeed);
+            showLabelsToggle.addEventListener('change', toggleLabels);
+            // Set canvas size to match video when it loads
+            videoElement.addEventListener('loadedmetadata', () => {
+                canvasElement.width = videoElement.videoWidth;
+                canvasElement.height = videoElement.videoHeight;
+            });
+            // Load the model
+            loadModel();
+        }
+        function handleSourceChange() {
+            const source = sourceSelect.value;
+            // Hide all controls
+            cameraControls.classList.add('hidden');
+            videoUrlControls.classList.add('hidden');
+            fileUploadControls.classList.add('hidden');
+            // Show the appropriate controls
+            if (source === 'camera') {
+                cameraControls.classList.remove('hidden');
+            } else if (source === 'video-url') {
+                videoUrlControls.classList.remove('hidden');
+            } else if (source === 'file-upload') {
+                fileUploadControls.classList.remove('hidden');
+            }
+            // Stop any ongoing detection
+            stopDetection();
+        }
+        async function loadModel() {
+            try {
+                modelLoadingBar.classList.remove('hidden');
+                modelLoadingProgress.style.width = '10%';
+                statusMessage.textContent = 'Loading object detection model...';
+                // Simulate progress for demo purposes
+                const progressInterval = setInterval(() => {
+                    const currentWidth = parseInt(modelLoadingProgress.style.width);
+                    if (currentWidth < 90) {
+                        modelLoadingProgress.style.width = `${currentWidth + 10}%`;
+                    }
+                }, 300);
+                // Load the COCO-SSD model
+                model = await cocoSsd.load({
+                    base: speedSelect.value === 'fast' ? 'mobilenet_v1' :
+                          speedSelect.value === 'slow' ? 'resnet50' : 'lite_mobilenet_v2'
+                });
+                clearInterval(progressInterval);
+                modelLoadingProgress.style.width = '100%';
+                statusMessage.textContent = 'Model loaded successfully!';
+                setTimeout(() => {
+                    modelLoadingBar.classList.add('hidden');
+                }, 1000);
+            } catch (error) {
+                console.error('Error loading model:', error);
+                statusMessage.textContent = 'Failed to load model. Please refresh the page.';
+                modelLoadingBar.classList.add('hidden');
+            }
+        }
+        async function startCamera() {
+            try {
+                statusMessage.textContent = 'Accessing camera...';
+                stream = await navigator.mediaDevices.getUserMedia({ video: true });
+                videoElement.srcObject = stream;
+                videoElement.classList.remove('hidden');
+                startCameraBtn.disabled = true;
+                stopCameraBtn.disabled = false;
+                statusMessage.textContent = 'Camera started. Detecting objects...';
+                // Start detection
+                startDetection();
+            } catch (error) {
+                console.error('Error accessing camera:', error);
+                statusMessage.textContent = 'Could not access camera. Please check permissions.';
+            }
+        }
+        function stopCamera() {
+            if (stream) {
+                stream.getTracks().forEach(track => track.stop());
+                stream = null;
+            }
+            videoElement.srcObject = null;
+            videoElement.classList.add('hidden');
+            startCameraBtn.disabled = false;
+            stopCameraBtn.disabled = true;
+            // Stop detection
+            stopDetection();
+            statusMessage.textContent = 'Camera stopped.';
+        }
+        function loadVideoFromUrl() {
+            const videoUrl = videoUrlInput.value.trim();
+            if (!videoUrl) {
+                statusMessage.textContent = 'Please enter a valid video URL.';
+                return;
+            }
+            stopDetection();
+            videoElement.src = videoUrl;
+            videoElement.classList.remove('hidden');
+            statusMessage.textContent = 'Loading video...';
+            videoElement.onerror = () => {
+                statusMessage.textContent = 'Failed to load video. Please check the URL.';
+            };
+            videoElement.onloadeddata = () => {
+                statusMessage.textContent = 'Video loaded. Detecting objects...';
+                startDetection();
+            };
+        }
+        function handleVideoUpload(event) {
+            const file = event.target.files[0];
+            if (!file) return;
+            stopDetection();
+            const videoURL = URL.createObjectURL(file);
+            videoElement.src = videoURL;
+            videoElement.classList.remove('hidden');
+            statusMessage.textContent = 'Loading video...';
+            videoElement.onloadeddata = () => {
+                statusMessage.textContent = 'Video loaded. Detecting objects...';
+                startDetection();
+            };
+        }
+        function startDetection() {
+            if (!model) {
+                statusMessage.textContent = 'Model not loaded yet. Please wait...';
+                return;
+            }
+            if (isDetecting) return;
+            isDetecting = true;
+            // Clear previous results
+            detectionResults.innerHTML = '';
+            resultsContainer.classList.remove('hidden');
+            // Start detecting objects in the video
+            detectObjects();
+            // Set up interval for continuous detection
+            const interval = detectionSpeed === 'fast' ? 300 :
+                           detectionSpeed === 'slow' ? 1000 : 500;
+            detectionInterval = setInterval(detectObjects, interval);
+        }
+        function stopDetection() {
+            if (detectionInterval) {
+                clearInterval(detectionInterval);
+                detectionInterval = null;
+            }
+            isDetecting = false;
+            // Clear canvas
+            const ctx = canvasElement.getContext('2d');
+            ctx.clearRect(0, 0, canvasElement.width, canvasElement.height);
+        }
+        async function detectObjects() {
+            if (!isDetecting || videoElement.readyState < 2) return;
+            try {
+                // Get predictions from the model
+                const predictions = await model.detect(videoElement);
+                // Filter predictions based on confidence threshold
+                const filteredPredictions = predictions.filter(
+                    pred => pred.score >= confidenceThreshold
+                );
+                // Filter for man-made objects (you can expand this list)
+                const manMadeObjects = filteredPredictions.filter(pred => {
+                    const objectClass = pred.class.toLowerCase();
+                    return [
+                        'person', 'bicycle', 'car', 'motorcycle', 'airplane', 'bus', 'train',
+                        'truck', 'boat', 'traffic light', 'fire hydrant', 'stop sign',
+                        'parking meter', 'bench', 'bird', 'cat', 'dog', 'horse', 'sheep',
+                        'cow', 'elephant', 'bear', 'zebra', 'giraffe', 'backpack', 'umbrella',
+                        'handbag', 'tie', 'suitcase', 'frisbee', 'skis', 'snowboard',
+                        'sports ball', 'kite', 'baseball bat', 'baseball glove', 'skateboard',
+                        'surfboard', 'tennis racket', 'bottle', 'wine glass', 'cup', 'fork',
+                        'knife', 'spoon', 'bowl', 'banana', 'apple', 'sandwich', 'orange',
+                        'broccoli', 'carrot', 'hot dog', 'pizza', 'donut', 'cake', 'chair',
+                        'couch', 'potted plant', 'bed', 'dining table', 'toilet', 'tv',
+                        'laptop', 'mouse', 'remote', 'keyboard', 'cell phone', 'microwave',
+                        'oven', 'toaster', 'sink', 'refrigerator', 'book', 'clock', 'vase',
+                        'scissors', 'teddy bear', 'hair drier', 'toothbrush'
+                    ].includes(objectClass);
+                });
+                // Draw bounding boxes and labels
+                drawDetections(manMadeObjects);
+                // Update results display
+                updateResultsDisplay(manMadeObjects);
+            } catch (error) {
+                console.error('Error detecting objects:', error);
+                statusMessage.textContent = 'Error detecting objects.';
+            }
+        }
+        function drawDetections(predictions) {
+            const ctx = canvasElement.getContext('2d');
+            ctx.clearRect(0, 0, ctx.canvas.width, ctx.canvas.height);
+            // Font settings
+            const font = "16px sans-serif";
+            ctx.font = font;
+            ctx.textBaseline = "top";
+            predictions.forEach(prediction => {
+                // Draw bounding box
+                const [x, y, width, height] = prediction.bbox;
+                ctx.strokeStyle = "#00FFFF";
+                ctx.lineWidth = 2;
+                ctx.strokeRect(x, y, width, height);
+                if (showLabels) {
+                    // Draw label background
+                    const text = `${prediction.class} ${(prediction.score * 100).toFixed(1)}%`;
+                    const textWidth = ctx.measureText(text).width;
+                    const textHeight = parseInt(font, 10);
+                    ctx.fillStyle = "rgba(0, 0, 0, 0.7)";
+                    ctx.fillRect(x, y, textWidth + 4, textHeight + 4);
+                    // Draw text
+                    ctx.fillStyle = "#FFFFFF";
+                    ctx.fillText(text, x, y);
+                }
+            });
+        }
+        function updateResultsDisplay(predictions) {
+            // Clear previous results
+            detectionResults.innerHTML = '';
+            // Group predictions by class and count them
+            const objectCounts = {};
+            predictions.forEach(pred => {
+                if (!objectCounts[pred.class]) {
+                    objectCounts[pred.class] = 0;
+                }
+                objectCounts[pred.class]++;
+            });
+            // Sort by count (descending)
+            const sortedClasses = Object.keys(objectCounts).sort(
+                (a, b) => objectCounts[b] - objectCounts[a]
+            );
+            // Create cards for each detected object class
+            sortedClasses.forEach(className => {
+                const count = objectCounts[className];
+                const card = document.createElement('div');
+                card.className = 'bg-white rounded-lg shadow p-4 flex items-center';
+                // You could add icons for common objects here
+                const icon = document.createElement('div');
+                icon.className = 'w-10 h-10 rounded-full bg-blue-100 flex items-center justify-center mr-4';
+                icon.innerHTML = `<span class="text-blue-600 font-bold">${count}</span>`;
+                const content = document.createElement('div');
+                content.className = 'flex-1';
+                const title = document.createElement('h3');
+                title.className = 'font-semibold text-gray-800 capitalize';
+                title.textContent = className;
+                const countText = document.createElement('p');
+                countText.className = 'text-sm text-gray-600';
+                countText.textContent = `${count} detected`;
+                content.appendChild(title);
+                content.appendChild(countText);
+                card.appendChild(icon);
+                card.appendChild(content);
+                detectionResults.appendChild(card);
+            });
+            // Show message if no objects detected
+            if (sortedClasses.length === 0) {
+                const message = document.createElement('div');
+                message.className = 'col-span-3 text-center py-8 text-gray-500';
+                message.textContent = 'No man-made objects detected. Try adjusting the confidence threshold.';
+                detectionResults.appendChild(message);
+            }
+        }
+        function updateConfidenceThreshold() {
+            confidenceThreshold = parseFloat(confidenceSlider.value);
+            confidenceValue.textContent = `${Math.round(confidenceThreshold * 100)}%`;
+        }
+        function updateDetectionSpeed() {
+            detectionSpeed = speedSelect.value;
+            // If detection is running, restart with new speed
+            if (isDetecting) {
+                stopDetection();
+                startDetection();
+            }
+        }
+        function toggleLabels() {
+            showLabels = showLabelsToggle.checked;
+        }
+    </script>
+<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=Danyray101/objdetect" style="color: #fff;text-decoration: underline;" target="_blank" >Remix</a></p></body>
+</html>

prompts.txt ADDED Viewed

File without changes