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Jdp-08 commited on Feb 24

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Dockerfile +11 -0
index.html +327 -0
requirements.txt +6 -0
server.py +61 -0

Dockerfile ADDED Viewed

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+FROM python:3.9
+WORKDIR /app
+COPY . .
+RUN pip install --no-cache-dir -r requirements.txt
+EXPOSE 7860
+CMD ["uvicorn", "backend.server:app", "--host", "0.0.0.0", "--port", "7860"]

index.html ADDED Viewed

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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>DeepTrust - Deepfake Detection</title>
+    <script src="https://cdn.tailwindcss.com"></script>
+    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@latest/dist/tf.min.js"></script>
+    <link href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/6.4.0/css/all.min.css" rel="stylesheet">
+    <style>
+        @import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&display=swap');
+        body {
+            font-family: 'Inter', sans-serif;
+            overflow-x: hidden;
+        }
+        .bg-dark {
+            background: linear-gradient(135deg, #0a0a0f 0%, #111827 100%);
+        }
+        .upload-area {
+            transition: border-color 0.2s ease;
+            border: 2px dashed #4b5563;
+        }
+        .upload-area:focus-within,
+        .upload-area.dragover {
+            border-color: #3b82f6;
+            background: rgba(59, 130, 246, 0.05);
+        }
+        .result-card {
+            background: rgba(17, 24, 39, 0.95);
+            backdrop-filter: blur(10px);
+        }
+        .progress-bar {
+            transition: width 0.3s ease;
+        }
+        .confidence-fill {
+            height: 6px;
+            background: linear-gradient(to right, #dc2626 0%, #f59e0b 50%, #16a34a 100%);
+            border-radius: 3px;
+        }
+        main { min-height: calc(100vh - 200px); }
+    </style>
+</head>
+<body class="bg-dark text-white min-h-screen">
+    <!-- Header -->
+    <header class="p-6 border-b border-gray-800">
+        <nav class="max-w-6xl mx-auto flex justify-between items-center">
+            <div class="flex items-center space-x-3">
+                <i class="fas fa-shield-halved text-xl text-blue-500"></i>
+                <h1 class="text-xl font-semibold">DeepTrust</h1>
+                <span class="text-xs bg-blue-900/50 px-2 py-0.5 rounded text-blue-200 font-medium">Forensics AI</span>
+            </div>
+            <div class="hidden md:flex space-x-6 text-sm text-gray-400">
+                <a href="#" class="hover:text-white transition-colors">Documentation</a>
+                <a href="#" class="hover:text-white transition-colors">API</a>
+            </div>
+        </nav>
+    </header>
+    <!-- Main Content -->
+    <main class="max-w-4xl mx-auto px-4 py-12 pb-24 flex-grow">
+        <div class="text-center mb-16">
+            <h2 class="text-3xl md:text-4xl font-bold mb-4 text-gray-100">
+                Deepfake Detection
+            </h2>
+            <p class="text-lg text-gray-400 max-w-2xl mx-auto">
+                Upload image, video, or PDF for forensic analysis using advanced AI models.
+            </p>
+        </div>
+        <!-- Upload Section -->
+        <div id="uploadSection" class="result-card rounded-2xl p-8 md:p-12 mb-12 shadow-xl">
+            <!-- Upload Dropzone -->
+            <div id="uploadArea" class="upload-area rounded-xl p-12 text-center cursor-pointer mb-8 hover:border-gray-400 transition-colors"
+                 onclick="document.getElementById('fileInput').click()">
+                <i class="fas fa-cloud-arrow-up text-4xl text-gray-500 mb-6"></i>
+                <h3 class="text-xl font-semibold mb-3 text-gray-200">Drop file here or click to browse</h3>
+                <p class="text-gray-500 mb-8">Supports JPG, PNG, MP4, PDF (max 50MB)</p>
+                <div class="flex justify-center space-x-6 text-sm text-gray-500">
+                    <span><i class="fas fa-image mr-1"></i> Image</span>
+                    <span><i class="fas fa-video mr-1"></i> Video</span>
+                    <span><i class="fas fa-file-pdf mr-1"></i> PDF</span>
+                </div>
+            </div>
+            <input type="file" id="fileInput" accept="image/*,video/*,.pdf" class="hidden">
+            <!-- Preview (conditionally shown) -->
+            <div id="previewSection" class="hidden mb-8 p-6 bg-gray-900/50 rounded-xl">
+                <div class="flex flex-col lg:flex-row gap-6 items-start">
+                    <img id="previewImg" class="flex-1 max-h-80 lg:max-h-96 object-contain rounded-lg shadow-md mx-auto lg:mx-0" alt="File preview">
+                    <div id="fileInfo" class="flex-1 min-w-0"></div>
+                </div>
+            </div>
+            <!-- Analyze Button (conditionally shown) -->
+            <button id="analyzeBtn" class="w-full bg-blue-600 hover:bg-blue-700 text-white font-medium py-4 px-8 rounded-xl text-lg transition-colors disabled:opacity-50 disabled:cursor-not-allowed">
+                Analyze for Deepfakes
+            </button>
+        </div>
+        <!-- Progress Section -->
+        <div id="progressSection" class="hidden result-card rounded-2xl p-12 mb-12">
+            <div class="text-center mb-8">
+                <div class="w-12 h-12 border-4 border-blue-500/20 border-t-blue-500 rounded-full animate-spin mx-auto mb-6"></div>
+                <p class="text-2xl font-semibold text-gray-100">Analyzing file</p>
+            </div>
+            <div class="w-full bg-gray-800 rounded-lg h-2.5 overflow-hidden">
+                <div id="progressBar" class="progress-bar bg-blue-600 h-2.5 w-0"></div>
+            </div>
+            <p id="progressText" class="text-center text-sm text-gray-500 mt-3">0%</p>
+        </div>
+        <!-- Results Section -->
+        <div id="resultsSection" class="hidden">
+            <div class="result-card rounded-2xl p-8 md:p-12">
+                <div class="flex flex-col lg:flex-row gap-12">
+                    <div class="flex-1">
+                        <div class="flex items-start mb-8">
+                            <div id="resultIcon" class="w-12 h-12 rounded-lg flex items-center justify-center text-xl font-bold mr-4 flex-shrink-0 mt-1" style="min-width: 48px;"></div>
+                            <div>
+                                <h3 id="resultTitle" class="text-2xl font-bold text-gray-100"></h3>
+                                <p id="resultSubtitle" class="text-gray-400 mt-1"></p>
+                            </div>
+                        </div>
+                        <div class="space-y-6">
+                            <div>
+                                <label class="text-sm font-medium text-gray-400 mb-2 block">Confidence</label>
+                                <div class="w-full bg-gray-800 rounded-lg h-8 relative overflow-hidden">
+                                    <div id="confidenceBar" class="confidence-fill absolute inset-0" style="width: 0%"></div>
+                                    <div id="confidenceText" class="absolute inset-0 flex items-center justify-center font-semibold text-sm bg-transparent z-10"></div>
+                                </div>
+                            </div>
+                            <div class="grid grid-cols-2 gap-4">
+                                <div class="text-center p-5 bg-gray-900/50 rounded-xl border border-gray-700">
+                                    <div id="scoreReal" class="text-3xl font-bold text-green-400 mb-1">92%</div>
+                                    <p class="text-gray-500 text-sm">Authentic</p>
+                                </div>
+                                <div class="text-center p-5 bg-gray-900/50 rounded-xl border border-gray-700">
+                                    <div id="scoreFake" class="text-3xl font-bold text-red-400 mb-1">8%</div>
+                                    <p class="text-gray-500 text-sm">Fabricated</p>
+                                </div>
+                            </div>
+                        </div>
+                    </div>
+                    <div class="flex-1 lg:min-h-[300px]">
+                        <div id="analysisDetails" class="space-y-3 text-sm text-gray-400 mb-8"></div>
+                        <div class="border-t border-gray-800 pt-8 flex flex-col sm:flex-row gap-4">
+                            <button class="flex-1 sm:flex-none bg-gray-700 hover:bg-gray-600 text-white font-medium py-3 px-6 rounded-xl border border-gray-600 transition-colors">
+                                <i class="fas fa-download mr-2"></i>
+                                Download Report
+                            </button>
+                            <button class="flex-1 sm:flex-none bg-blue-600 hover:bg-blue-700 text-white font-medium py-3 px-6 rounded-xl transition-colors">
+                                <i class="fas fa-share mr-2"></i>
+                                Share
+                            </button>
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </main>
+    <!-- Footer -->
+    <footer class="border-t border-gray-800 p-8 text-center text-xs text-gray-500 bg-gray-900/50">
+        DeepTrust Forensics | Advanced AI Detection | 2026
+    </footer>
+   <script>
+const uploadArea = document.getElementById('uploadArea');
+const fileInput = document.getElementById('fileInput');
+const analyzeBtn = document.getElementById('analyzeBtn');
+// ---------------- DRAG & DROP ----------------
+['dragenter', 'dragover', 'dragleave', 'drop'].forEach(eventName => {
+    uploadArea.addEventListener(eventName, e => {
+        e.preventDefault();
+        e.stopPropagation();
+    });
+});
+['dragenter', 'dragover'].forEach(eventName => {
+    uploadArea.addEventListener(eventName, () => {
+        uploadArea.classList.add('dragover');
+    });
+});
+['dragleave', 'drop'].forEach(eventName => {
+    uploadArea.addEventListener(eventName, () => {
+        uploadArea.classList.remove('dragover');
+    });
+});
+uploadArea.addEventListener('drop', e => {
+    handleFiles(e.dataTransfer.files);
+});
+fileInput.addEventListener('change', e => {
+    handleFiles(e.target.files);
+});
+// ---------------- FILE HANDLING ----------------
+function handleFiles(files) {
+    if (!files.length) return;
+    const file = files[0];
+    if (file.size > 50 * 1024 * 1024) {
+        alert('File size exceeds 50MB limit.');
+        return;
+    }
+    showPreview(file);
+}
+function showPreview(file) {
+    const previewSection = document.getElementById('previewSection');
+    const previewImg = document.getElementById('previewImg');
+    const fileInfo = document.getElementById('fileInfo');
+    const url = URL.createObjectURL(file);
+    previewImg.src = url;
+    previewImg.style.display = 'block';
+    fileInfo.innerHTML = `
+        <div class="space-y-2">
+            <div class="flex items-center text-sm">
+                <i class="fas fa-image mr-2 text-blue-400"></i>
+                <span class="font-semibold text-gray-200 truncate">${file.name}</span>
+            </div>
+            <p class="text-gray-500 text-sm">${formatBytes(file.size)}</p>
+        </div>
+    `;
+    previewSection.classList.remove('hidden');
+    analyzeBtn.classList.remove('hidden');
+}
+function formatBytes(bytes) {
+    if (bytes === 0) return '0 B';
+    const sizes = ['B', 'KB', 'MB'];
+    const i = Math.floor(Math.log(bytes) / Math.log(1024));
+    return (bytes / Math.pow(1024, i)).toFixed(1) + ' ' + sizes[i];
+}
+// ---------------- ANALYZE ----------------
+analyzeBtn.addEventListener('click', async () => {
+    const file = fileInput.files[0];
+    if (!file) return;
+    document.getElementById('uploadArea').style.display = 'none';
+    document.getElementById('previewSection').style.display = 'none';
+    analyzeBtn.style.display = 'none';
+    document.getElementById('progressSection').classList.remove('hidden');
+    let progress = 0;
+    const interval = setInterval(() => {
+        progress += 10;
+        if (progress > 95) progress = 95;
+        document.getElementById('progressBar').style.width = progress + '%';
+        document.getElementById('progressText').textContent = progress + '%';
+    }, 300);
+    const formData = new FormData();
+    formData.append("file", file);
+    try {
+        const response = await fetch("http://127.0.0.1:8000/analyze", {
+            method: "POST",
+            body: formData
+        });
+        if (!response.ok) {
+            throw new Error("Server returned error");
+        }
+        const data = await response.json();
+        clearInterval(interval);
+        document.getElementById('progressSection').classList.add('hidden');
+        showResults(
+            data.authenticity > 50,
+            data.authenticity,
+            Math.round(data.authenticity),
+            Math.round(data.fake)
+        );
+    } catch (error) {
+        clearInterval(interval);
+        document.getElementById('progressSection').classList.add('hidden');
+        console.error(error);
+        alert("Analysis failed. Check backend.");
+    }
+});
+// ---------------- RESULTS ----------------
+function showResults(isAuthentic, confidence, realScore, fakeScore) {
+    const section = document.getElementById('resultsSection');
+    section.classList.remove('hidden');
+    section.scrollIntoView({ behavior: 'smooth' });
+    const iconEl = document.getElementById('resultIcon');
+    const titleEl = document.getElementById('resultTitle');
+    const subtitleEl = document.getElementById('resultSubtitle');
+    const confBar = document.getElementById('confidenceBar');
+    const confText = document.getElementById('confidenceText');
+    if (isAuthentic) {
+        iconEl.innerHTML = '<i class="fas fa-check text-green-500"></i>';
+        titleEl.textContent = 'Authentic Media Detected';
+        subtitleEl.textContent = 'No synthetic manipulation found.';
+        confBar.style.background = '#10b981';
+    } else {
+        iconEl.innerHTML = '<i class="fas fa-triangle-exclamation text-orange-500"></i>';
+        titleEl.textContent = 'Potential Deepfake Detected';
+        subtitleEl.textContent = 'Signs of fabrication detected.';
+        confBar.style.background = '#f59e0b';
+    }
+    confText.textContent = confidence.toFixed(1) + '%';
+    confBar.style.width = confidence + '%';
+    document.getElementById('scoreReal').textContent = realScore + '%';
+    document.getElementById('scoreFake').textContent = fakeScore + '%';
+}
+</script>
+</body>
+</html>

requirements.txt ADDED Viewed

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+fastapi
+uvicorn
+transformers
+torch
+pillow
+python-multipart

server.py ADDED Viewed

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+from fastapi.staticfiles import StaticFiles
+from fastapi.responses import FileResponse
+from transformers import AutoImageProcessor, AutoModelForImageClassification
+from PIL import Image
+import torch
+from fastapi import FastAPI, UploadFile, File
+from fastapi.middleware.cors import CORSMiddleware
+import shutil
+import os
+import io
+model_name = "buildborderless/CommunityForensics-DeepfakeDet-ViT"
+processor = AutoImageProcessor.from_pretrained(model_name)
+model = AutoModelForImageClassification.from_pretrained(model_name)
+model.eval()
+app = FastAPI()
+app.mount("/static", StaticFiles(directory="static"), name="static")
+@app.get("/")
+def read_root():
+    return FileResponse("static/index.html")
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+@app.post("/analyze")
+async def analyze(file: UploadFile = File(...)):
+    if not file.content_type.startswith("image/"):
+        return {"error": "Only image files are supported."}
+    contents = await file.read()
+    image = Image.open(io.BytesIO(contents)).convert("RGB")
+    inputs = processor(
+            images=image,
+            return_tensors="pt",
+            size={"height": 384, "width": 384}
+        )
+    with torch.no_grad():
+        outputs = model(**inputs)
+    logits = outputs.logits
+    probs = torch.softmax(logits, dim=1)
+    deepfake_prob = probs[0][1].item()
+    authenticity = (1 - deepfake_prob) * 100
+    fake = deepfake_prob * 100
+    return {
+        "authenticity": round(authenticity, 2),
+        "fake": round(fake, 2)
+    }