Update app.py

app.py

@@ -1,658 +1,42 @@
-import gradio as gr
-from deepface import DeepFace
-import numpy as np
+from Crypto.Cipher import AES
+from Crypto.Protocol.KDF import PBKDF2
+import os
+import tempfile
+from dotenv import load_dotenv
 
-def verify_faces(nid_image, webcam_image):
-    """
-    Verify if two face images match with detailed step-by-step process visualization
-    
-    Args:
-        nid_image: NID card image (numpy array from Gradio)
-        webcam_image: Webcam/live image (numpy array from Gradio)
-    
-    Returns:
-        Formatted result string with verification details and process steps
-    """
-    model_name = "ArcFace"  # Using ArcFace model only
-    try:
-        # Check if images are provided
-        if nid_image is None or webcam_image is None:
-            return """
-            <div class='error-container'>
-                <div class='error-icon'>⚠️</div>
-                <h3>Missing Images</h3>
-                <p>Please upload both NID and webcam images to proceed</p>
-            </div>
-            """
-        
-        # Initialize process status
-        process_steps = {
-            "face_detection": "⏳ Detecting faces...",
-            "face_alignment": "⏳ Waiting...",
-            "preprocessing": "⏳ Waiting...",
-            "neural_network": "⏳ Waiting...",
-            "embedding": "⏳ Waiting...",
-            "calculate_distance": "⏳ Waiting...",
-            "threshold_comparison": "⏳ Waiting...",
-            "final_result": "⏳ Waiting..."
-        }
-        
-        # Step updates
-        process_steps["face_detection"] = "✅ Faces detected in both images"
-        process_steps["face_alignment"] = "✅ Faces aligned and normalized"
-        process_steps["preprocessing"] = "✅ Images preprocessed"
-        process_steps["neural_network"] = f"✅ Processing through {model_name}"
-        
-        # Perform face verification
-        result = DeepFace.verify(
-            img1_path=nid_image,
-            img2_path=webcam_image,
-            model_name=model_name,
-            enforce_detection=True
-        )
-        
-        # Extract results
-        verified = result["verified"]
-        distance = result["distance"]
-        threshold = result["threshold"]
-        model_used = result["model"]
-        detector = result["detector_backend"]
-        metric = result["similarity_metric"]
-        
-        # Step updates
-        process_steps["embedding"] = "✅ Face embeddings generated"
-        process_steps["calculate_distance"] = f"✅ Distance: {distance:.4f}"
-        
-        if distance < threshold:
-            process_steps["threshold_comparison"] = f"✅ {distance:.4f} < {threshold:.4f}"
-        else:
-            process_steps["threshold_comparison"] = f"❌ {distance:.4f} ≥ {threshold:.4f}"
-        
-        # Calculate confidence
-        if verified:
-            confidence = ((threshold - distance) / threshold) * 100
-            status = "MATCH"
-            status_class = "match"
-            process_steps["final_result"] = "✅ FACES MATCH"
-        else:
-            confidence = ((distance - threshold) / distance) * 100 if distance > 0 else 0
-            status = "NO MATCH"
-            status_class = "no-match"
-            process_steps["final_result"] = "❌ FACES DO NOT MATCH"
-        
-        # Format output with enhanced mobile-responsive design
-        output = f"""
-        <style>
-            .verification-container {{
-                max-width: 1200px;
-                margin: 0 auto;
-                padding: 16px;
-                font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, Cantarell, sans-serif;
-            }}
-            
-            .status-banner {{
-                padding: 24px;
-                border-radius: 16px;
-                text-align: center;
-                margin-bottom: 24px;
-                box-shadow: 0 4px 12px rgba(0,0,0,0.1);
-                animation: slideDown 0.5s ease;
-            }}
-            
-            .status-banner.match {{
-                background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-                color: white;
-            }}
-            
-            .status-banner.no-match {{
-                background: linear-gradient(135deg, #f093fb 0%, #f5576c 100%);
-                color: white;
-            }}
-            
-            .status-icon {{
-                font-size: 48px;
-                margin-bottom: 12px;
-            }}
-            
-            .status-title {{
-                font-size: 28px;
-                font-weight: 700;
-                margin: 8px 0;
-                letter-spacing: 1px;
-            }}
-            
-            .confidence-bar {{
-                width: 100%;
-                max-width: 300px;
-                height: 12px;
-                background: rgba(255,255,255,0.3);
-                border-radius: 20px;
-                margin: 16px auto;
-                overflow: hidden;
-            }}
-            
-            .confidence-fill {{
-                height: 100%;
-                background: white;
-                border-radius: 20px;
-                transition: width 1s ease;
-                width: {confidence:.1f}%;
-            }}
-            
-            .confidence-text {{
-                font-size: 20px;
-                font-weight: 600;
-                margin-top: 8px;
-            }}
-            
-            .card {{
-                background: white;
-                border-radius: 16px;
-                padding: 20px;
-                margin-bottom: 20px;
-                box-shadow: 0 2px 8px rgba(0,0,0,0.08);
-                border: 1px solid #e5e7eb;
-            }}
-            
-            .card-header {{
-                display: flex;
-                align-items: center;
-                margin-bottom: 16px;
-                padding-bottom: 12px;
-                border-bottom: 2px solid #f3f4f6;
-            }}
-            
-            .card-icon {{
-                font-size: 24px;
-                margin-right: 12px;
-            }}
-            
-            .card-title {{
-                font-size: 20px;
-                font-weight: 700;
-                color: #1f2937;
-                margin: 0;
-            }}
-            
-            .step-item {{
-                margin: 12px 0;
-                padding: 16px;
-                border-radius: 12px;
-                background: #f9fafb;
-                border-left: 4px solid #6366f1;
-                transition: transform 0.2s ease;
-            }}
-            
-            .step-item:hover {{
-                transform: translateX(4px);
-            }}
-            
-            .step-title {{
-                font-weight: 600;
-                font-size: 16px;
-                color: #374151;
-                margin-bottom: 6px;
-            }}
-            
-            .step-status {{
-                font-size: 15px;
-                margin-bottom: 4px;
-            }}
-            
-            .step-description {{
-                font-size: 13px;
-                color: #6b7280;
-                font-style: italic;
-                margin: 0;
-            }}
-            
-            .metrics-grid {{
-                display: grid;
-                grid-template-columns: repeat(auto-fit, minmax(250px, 1fr));
-                gap: 16px;
-                margin-top: 16px;
-            }}
-            
-            .metric-item {{
-                padding: 16px;
-                background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-                border-radius: 12px;
-                color: white;
-                text-align: center;
-            }}
-            
-            .metric-label {{
-                font-size: 13px;
-                opacity: 0.9;
-                margin-bottom: 6px;
-            }}
-            
-            .metric-value {{
-                font-size: 22px;
-                font-weight: 700;
-            }}
-            
-            .info-box {{
-                background: linear-gradient(135deg, #fef3c7 0%, #fde68a 100%);
-                padding: 16px;
-                border-radius: 12px;
-                margin-top: 20px;
-                border-left: 4px solid #f59e0b;
-            }}
-            
-            .info-title {{
-                font-weight: 700;
-                color: #92400e;
-                margin-bottom: 8px;
-                font-size: 16px;
-            }}
-            
-            .info-text {{
-                font-size: 14px;
-                color: #78350f;
-                line-height: 1.6;
-                margin: 6px 0;
-            }}
-            
-            .error-container {{
-                background: linear-gradient(135deg, #fee2e2 0%, #fecaca 100%);
-                padding: 32px;
-                border-radius: 16px;
-                text-align: center;
-                border: 2px solid #ef4444;
-            }}
-            
-            .error-icon {{
-                font-size: 48px;
-                margin-bottom: 16px;
-            }}
-            
-            @keyframes slideDown {{
-                from {{
-                    opacity: 0;
-                    transform: translateY(-20px);
-                }}
-                to {{
-                    opacity: 1;
-                    transform: translateY(0);
-                }}
-            }}
-            
-            /* Mobile Responsive */
-            @media (max-width: 768px) {{
-                .verification-container {{
-                    padding: 12px;
-                }}
-                
-                .status-banner {{
-                    padding: 20px 16px;
-                }}
-                
-                .status-icon {{
-                    font-size: 36px;
-                }}
-                
-                .status-title {{
-                    font-size: 22px;
-                }}
-                
-                .confidence-text {{
-                    font-size: 18px;
-                }}
-                
-                .card {{
-                    padding: 16px;
-                    margin-bottom: 16px;
-                }}
-                
-                .card-title {{
-                    font-size: 18px;
-                }}
-                
-                .step-item {{
-                    padding: 12px;
-                }}
-                
-                .step-title {{
-                    font-size: 15px;
-                }}
-                
-                .metrics-grid {{
-                    grid-template-columns: 1fr;
-                    gap: 12px;
-                }}
-                
-                .metric-value {{
-                    font-size: 20px;
-                }}
-            }}
-            
-            @media (max-width: 480px) {{
-                .status-title {{
-                    font-size: 20px;
-                }}
-                
-                .card-icon {{
-                    font-size: 20px;
-                }}
-                
-                .card-title {{
-                    font-size: 16px;
-                }}
-            }}
-        </style>
-        
-        <div class='verification-container'>
-            <div class='status-banner {status_class}'>
-                <div class='status-icon'>{'✅' if verified else '❌'}</div>
-                <div class='status-title'>{status}</div>
-                <div class='confidence-bar'>
-                    <div class='confidence-fill'></div>
-                </div>
-                <div class='confidence-text'>{confidence:.1f}% Confidence</div>
-            </div>
-            
-            <div class='card'>
-                <div class='card-header'>
-                    <div class='card-icon'>🔄</div>
-                    <h3 class='card-title'>Verification Process</h3>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 1-2: Face Detection</div>
-                    <div class='step-status'>{process_steps["face_detection"]}</div>
-                    <p class='step-description'>Detector: {detector}</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 3: Face Alignment</div>
-                    <div class='step-status'>{process_steps["face_alignment"]}</div>
-                    <p class='step-description'>Faces rotated and centered</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 4: Preprocessing</div>
-                    <div class='step-status'>{process_steps["preprocessing"]}</div>
-                    <p class='step-description'>Images standardized</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 5: Neural Network</div>
-                    <div class='step-status'>{process_steps["neural_network"]}</div>
-                    <p class='step-description'>Deep learning feature extraction</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 6: Embedding Generation</div>
-                    <div class='step-status'>{process_steps["embedding"]}</div>
-                    <p class='step-description'>Numerical vector creation</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 7: Distance Calculation</div>
-                    <div class='step-status'>{process_steps["calculate_distance"]}</div>
-                    <p class='step-description'>Metric: {metric}</p>
-                </div>
-                
-                <div class='step-item'>
-                    <div class='step-title'>Step 8: Threshold Comparison</div>
-                    <div class='step-status'>{process_steps["threshold_comparison"]}</div>
-                    <p class='step-description'>Decision boundary check</p>
-                </div>
-                
-                <div class='step-item' style='border-left-color: {"#10b981" if verified else "#ef4444"}; background: {"#ecfdf5" if verified else "#fee2e2"};'>
-                    <div class='step-title'>Step 9: Final Result</div>
-                    <div class='step-status'><b>{process_steps["final_result"]}</b></div>
-                </div>
-            </div>
-            
-            <div class='card'>
-                <div class='card-header'>
-                    <div class='card-icon'>📊</div>
-                    <h3 class='card-title'>Detailed Metrics</h3>
-                </div>
-                
-                <div class='metrics-grid'>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Verified Status</div>
-                        <div class='metric-value'>{'YES' if verified else 'NO'}</div>
-                    </div>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Confidence Score</div>
-                        <div class='metric-value'>{confidence:.1f}%</div>
-                    </div>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Distance Score</div>
-                        <div class='metric-value'>{distance:.4f}</div>
-                    </div>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Threshold Value</div>
-                        <div class='metric-value'>{threshold:.4f}</div>
-                    </div>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Model Used</div>
-                        <div class='metric-value' style='font-size: 18px;'>{model_used}</div>
-                    </div>
-                    <div class='metric-item'>
-                        <div class='metric-label'>Similarity Metric</div>
-                        <div class='metric-value' style='font-size: 18px;'>{metric}</div>
-                    </div>
-                </div>
-            </div>
-            
-            <div class='info-box'>
-                <div class='info-title'>📖 Understanding the Results</div>
-                <p class='info-text'><b>Distance Score:</b> How different the faces are (lower = more similar)</p>
-                <p class='info-text'><b>Threshold:</b> Cutoff point - below this means match</p>
-                <p class='info-text'><b>Confidence:</b> How certain the system is about the decision</p>
-                <p class='info-text'><b>Embeddings:</b> Mathematical face representations in high-dimensional space</p>
-            </div>
-        </div>
-        """
-        
-        return output
-        
-    except ValueError as e:
-        if "Face could not be detected" in str(e):
-            return """
-            <div class='verification-container'>
-                <div class='error-container'>
-                    <div class='error-icon'>❌</div>
-                    <h3 style='color: #dc2626; margin: 12px 0;'>Face Detection Failed</h3>
-                    <p style='color: #991b1b; margin: 8px 0;'><b>No face detected in one or both images</b></p>
-                    <div style='text-align: left; display: inline-block; margin-top: 16px;'>
-                        <p style='color: #991b1b; margin: 6px 0;'><b>Suggestions:</b></p>
-                        <ul style='color: #991b1b; text-align: left;'>
-                            <li>Ensure clear, visible faces</li>
-                            <li>Use front-facing photos</li>
-                            <li>Improve lighting conditions</li>
-                            <li>Remove obstructions</li>
-                        </ul>
-                    </div>
-                </div>
-            </div>
-            """
-        else:
-            return f"""
-            <div class='verification-container'>
-                <div class='error-container'>
-                    <div class='error-icon'>⚠️</div>
-                    <h3 style='color: #dc2626;'>Verification Error</h3>
-                    <p style='color: #991b1b;'>{str(e)}</p>
-                </div>
-            </div>
-            """
-    
-    except Exception as e:
-        return f"""
-        <div class='verification-container'>
-            <div class='error-container'>
-                <div class='error-icon'>❌</div>
-                <h3 style='color: #dc2626;'>System Error</h3>
-                <p style='color: #991b1b;'>{str(e)}</p>
-                <p style='color: #991b1b; font-size: 14px; margin-top: 12px;'>Please try again or contact support</p>
-            </div>
-        </div>
-        """
+load_dotenv()  # Load all environment variables
 
+def unpad(data):
+    return data[:-data[-1]]
 
-# Custom CSS for the entire Gradio app
-custom_css = """
-    @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;500;600;700&display=swap');
-    
-    * {
-        font-family: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif !important;
-    }
-    
-    .gradio-container {
-        max-width: 1400px !important;
-        margin: auto !important;
-    }
-    
-    .main-header {
-        text-align: center;
-        padding: 32px 16px;
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-        color: white;
-        border-radius: 20px;
-        margin-bottom: 32px;
-        box-shadow: 0 8px 24px rgba(102, 126, 234, 0.3);
-    }
-    
-    .main-header h1 {
-        font-size: 36px;
-        font-weight: 700;
-        margin-bottom: 12px;
-        letter-spacing: -0.5px;
-    }
-    
-    .main-header p {
-        font-size: 18px;
-        opacity: 0.95;
-        margin: 0;
-    }
-    
-    button {
-        border-radius: 12px !important;
-        font-weight: 600 !important;
-        transition: all 0.3s ease !important;
-    }
-    
-    button:hover {
-        transform: translateY(-2px);
-        box-shadow: 0 4px 12px rgba(0,0,0,0.15) !important;
-    }
-    
-    .image-container {
-        border-radius: 16px;
-        overflow: hidden;
-        box-shadow: 0 4px 12px rgba(0,0,0,0.08);
-    }
-    
-    @media (max-width: 768px) {
-        .main-header h1 {
-            font-size: 28px;
-        }
-        
-        .main-header p {
-            font-size: 16px;
-        }
-        
-        .main-header {
-            padding: 24px 16px;
-        }
-    }
-"""
+def decrypt_and_run():
+    # Get password from Hugging Face Secrets environment variable
+    password = os.getenv("PASSWORD")
+    if not password:
+        raise ValueError("PASSWORD secret not found in environment variables")
 
-# Create Gradio Interface
-with gr.Blocks(css=custom_css, title="Face Verification System", theme=gr.themes.Ocean()) as demo:
-    
-    gr.HTML("""
-        <div class='main-header'>
-            <h1>🔐 Face Verification System</h1>
-            <p>Advanced Deep Learning Face Matching with Process Visualization</p>
-        </div>
-    """)
-    
-    with gr.Row():
-        with gr.Column(scale=1):
-            nid_input = gr.Image(
-                label="📇 NID Card Image",
-                type="numpy",
-                sources=["upload", "webcam"],
-                height=300,
-                container=True
-            )
-        
-        with gr.Column(scale=1):
-            webcam_input = gr.Image(
-                label="📷 Webcam/Live Image",
-                type="numpy",
-                sources=["upload", "webcam"],
-                height=300,
-                container=True
-            )
-    
-    verify_button = gr.Button("🔍 Verify Faces with ArcFace", variant="primary", size="lg")
-    
-    output_html = gr.HTML(label="Verification Result")
-    
-    # Button click event
-    verify_button.click(
-        fn=verify_faces,
-        inputs=[nid_input, webcam_input],
-        outputs=output_html
-    )
-    
-    with gr.Accordion("📚 How to Use", open=False):
-        gr.Markdown("""
-        ### Step-by-Step Guide:
-        
-        1. **Upload NID Image** - Upload or capture the ID card photo with a clear face
-        2. **Upload Live Image** - Upload or capture a webcam photo of the person
-        3. **Click Verify** - Start the verification process
-        4. **View Results** - See detailed step-by-step process and metrics
-        
-        ### ⚠️ Best Practices:
-        
-        ✅ Use clear, well-lit photos  
-        ✅ Ensure faces are front-facing  
-        ✅ Keep faces unobstructed  
-        ✅ Use high-resolution images  
-        
-        ❌ Avoid blurry images  
-        ❌ Avoid extreme angles  
-        ❌ Avoid poor lighting  
-        ❌ Avoid multiple faces  
-        """)
-    
-    with gr.Accordion("🔬 The 9-Step Process", open=False):
-        gr.Markdown("""
-        | Step | Process | Description |
-        |------|---------|-------------|
-        | 1-2 | **Face Detection** | Locates and extracts faces from images |
-        | 3 | **Face Alignment** | Rotates and centers faces |
-        | 4 | **Preprocessing** | Resizes and normalizes images |
-        | 5 | **Neural Network** | Deep learning processing |
-        | 6 | **Embedding** | Converts to numerical vectors |
-        | 7 | **Distance Calculation** | Measures similarity |
-        | 8 | **Threshold Check** | Compares against cutoff |
-        | 9 | **Final Decision** | Returns MATCH or NO MATCH |
-        """)
-    
-    with gr.Accordion("🎯 Available Models", open=False):
-        gr.Markdown("""
-        - **ArcFace** ⭐ - State-of-the-art (~99.4% accuracy)
-        - New Models (very soon)
-        """)
-    
-    gr.Markdown("""
-        <div style='text-align: center; padding: 20px; color: #6b7280; font-size: 14px;'>
-            <p><b>🔒 Privacy Notice:</b> Images are processed locally and not stored permanently</p>
-            <p><b>⚠️ Disclaimer:</b> For educational and demonstration purposes only</p>
-        </div>
-    """)
+    password = password.encode()
+
+    with open("code.enc", "rb") as f:
+        encrypted = f.read()
+
+    salt = encrypted[:16]
+    iv = encrypted[16:32]
+    ciphertext = encrypted[32:]
+
+    key = PBKDF2(password, salt, dkLen=32, count=1000000)
+    cipher = AES.new(key, AES.MODE_CBC, iv)
+
+    plaintext = unpad(cipher.decrypt(ciphertext))
+
+    with tempfile.NamedTemporaryFile(suffix=".py", delete=False, mode='wb') as tmp:
+        tmp.write(plaintext)
+        tmp.flush()
+        print(f"[INFO] Running decrypted code from {tmp.name}")
+        os.system(f"python {tmp.name}")
 
-# Launch the app
 if __name__ == "__main__":
-    demo.launch(share=True, debug=True)
+    decrypt_and_run()
+
+# This script decrypts the encrypted code and runs it.
+# Ensure you have the PASSWORD secret set in your Hugging Face Secrets