Create utils.py

utils.py

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+# ═══════════════════════════════════════════════════════════════════
+# utils.py - Measurements, HTML Generation, and Utilities
+# ═══════════════════════════════════════════════════════════════════
+
+import cv2
+import numpy as np
+from datetime import timedelta
+
+# ═══════════════════════════════════════════════════════════════════
+# MEASUREMENT CALCULATOR
+# ═══════════════════════════════════════════════════════════════════
+
+class PotholeMeasurementSystem:
+    """Calculate physical measurements from segmentation masks"""
+    
+    def __init__(self):
+        self.fx = 384.0
+        self.fy = 384.0
+        self.cx = 320.0
+        self.cy = 240.0
+    
+    def calculate_measurements(self, mask, depth_map=None):
+        """Calculate all physical measurements from mask"""
+        mask_bool = mask > 0
+        
+        if not np.any(mask_bool):
+            return None
+        
+        contours, _ = cv2.findContours(
+            mask.astype(np.uint8), 
+            cv2.RETR_EXTERNAL, 
+            cv2.CHAIN_APPROX_NONE
+        )
+        
+        if len(contours) == 0:
+            return None
+        
+        contour = max(contours, key=cv2.contourArea)
+        
+        # Get bounding box and centroid
+        x, y, w, h = cv2.boundingRect(contour)
+        M = cv2.moments(contour)
+        if M["m00"] != 0:
+            cx = int(M["m10"] / M["m00"])
+            cy = int(M["m01"] / M["m00"])
+        else:
+            cx, cy = x + w//2, y + h//2
+        
+        pixel_area = np.sum(mask_bool)
+        perimeter_pixels = cv2.arcLength(contour, True)
+        pixel_to_mm = 0.5
+        
+        if depth_map is not None:
+            h_c = np.median(depth_map[~mask_bool & (depth_map > 0)])
+            pothole_depths = depth_map[mask_bool]
+            pothole_depths = pothole_depths[pothole_depths > 0]
+            
+            if len(pothole_depths) > 0:
+                actual_depths = pothole_depths - h_c
+                max_depth_mm = float(actual_depths.max()) if len(actual_depths) > 0 else 0
+                mean_depth_mm = float(actual_depths.mean()) if len(actual_depths) > 0 else 0
+                
+                depth_m = h_c / 1000.0
+                s_x = depth_m / self.fx
+                s_y = depth_m / self.fy
+                pixel_to_mm = (s_x + s_y) / 2 * 1000
+            else:
+                max_depth_mm = 0
+                mean_depth_mm = 0
+        else:
+            estimated_depth_cm = min(15, (pixel_area / 1000) * 2)
+            max_depth_mm = estimated_depth_cm * 10
+            mean_depth_mm = max_depth_mm * 0.7
+        
+        perimeter_cm = (perimeter_pixels * pixel_to_mm) / 10
+        area_cm2 = (pixel_area * pixel_to_mm * pixel_to_mm) / 100
+        area_m2 = area_cm2 / 10000
+        volume_liters = (area_m2 * (max_depth_mm / 1000) / 3) * 1000
+        
+        depth_cm = max_depth_mm / 10
+        if depth_cm > 10 or area_m2 > 0.5:
+            severity = 'CRITICAL'
+            severity_color = '🔴'
+        elif depth_cm > 5 or area_m2 > 0.2:
+            severity = 'HIGH'
+            severity_color = '🟠'
+        elif depth_cm > 3:
+            severity = 'MEDIUM'
+            severity_color = '🟡'
+        else:
+            severity = 'LOW'
+            severity_color = '🟢'
+        
+        return {
+            'max_depth_mm': max_depth_mm,
+            'max_depth_cm': max_depth_mm / 10,
+            'mean_depth_mm': mean_depth_mm,
+            'mean_depth_cm': mean_depth_mm / 10,
+            'perimeter_cm': perimeter_cm,
+            'perimeter_m': perimeter_cm / 100,
+            'area_cm2': area_cm2,
+            'area_m2': area_m2,
+            'volume_liters': volume_liters,
+            'volume_m3': volume_liters / 1000,
+            'num_pixels': int(pixel_area),
+            'severity': severity,
+            'severity_color': severity_color,
+            'contour': contour,
+            'bbox': (x, y, w, h),
+            'centroid': (cx, cy)
+        }
+
+# ═══════════════════════════════════════════════════════════════════
+# HTML GENERATION
+# ═══════════════════════════════════════════════════════════════════
+
+def generate_metrics_html(measurements):
+    """Generate HTML metrics for images"""
+    if not measurements:
+        return "<h3 style='color: orange;'>No measurements available</h3>"
+    
+    html = """
+    <style>
+        .metrics-container {
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            padding: 20px;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            border-radius: 15px;
+            color: white;
+        }
+        .metrics-header {
+            text-align: center;
+            margin-bottom: 20px;
+            font-size: 24px;
+            font-weight: bold;
+            text-shadow: 2px 2px 4px rgba(0,0,0,0.3);
+        }
+        .pothole-card {
+            background: rgba(255, 255, 255, 0.95);
+            border-radius: 10px;
+            padding: 15px;
+            margin: 10px 0;
+            color: #333;
+            box-shadow: 0 4px 6px rgba(0,0,0,0.1);
+        }
+        .pothole-header {
+            font-size: 18px;
+            font-weight: bold;
+            margin-bottom: 10px;
+            display: flex;
+            justify-content: space-between;
+            align-items: center;
+        }
+        .severity-badge {
+            padding: 5px 15px;
+            border-radius: 20px;
+            font-weight: bold;
+            font-size: 14px;
+        }
+        .severity-CRITICAL { background: #ff4444; color: white; }
+        .severity-HIGH { background: #ff9800; color: white; }
+        .severity-MEDIUM { background: #ffeb3b; color: #333; }
+        .severity-LOW { background: #4caf50; color: white; }
+        .metrics-grid {
+            display: grid;
+            grid-template-columns: repeat(2, 1fr);
+            gap: 10px;
+            margin-top: 10px;
+        }
+        .metric-item {
+            background: #f5f5f5;
+            padding: 10px;
+            border-radius: 5px;
+            border-left: 4px solid #667eea;
+        }
+        .metric-label {
+            font-size: 12px;
+            color: #666;
+            margin-bottom: 3px;
+        }
+        .metric-value {
+            font-size: 18px;
+            font-weight: bold;
+            color: #333;
+        }
+        .summary-section {
+            margin-top: 20px;
+            padding: 15px;
+            background: rgba(255, 255, 255, 0.95);
+            border-radius: 10px;
+            color: #333;
+        }
+    </style>
+    
+    <div class="metrics-container">
+        <div class="metrics-header">🕳️ Pothole Detection Results</div>
+    """
+    
+    for m in measurements:
+        severity_class = f"severity-{m['severity']}"
+        html += f"""
+        <div class="pothole-card">
+            <div class="pothole-header">
+                <span>{m['severity_color']} Pothole #{m['pothole_id']}</span>
+                <span class="severity-badge {severity_class}">{m['severity']}</span>
+            </div>
+            <div style="margin-bottom: 10px;"><strong>Confidence:</strong> {m['confidence']*100:.1f}%</div>
+            <div class="metrics-grid">
+                <div class="metric-item">
+                    <div class="metric-label">📏 Max Depth</div>
+                    <div class="metric-value">{m['max_depth_cm']:.2f} cm</div>
+                </div>
+                <div class="metric-item">
+                    <div class="metric-label">📦 Area</div>
+                    <div class="metric-value">{m['area_m2']:.4f} m²</div>
+                </div>
+                <div class="metric-item">
+                    <div class="metric-label">💧 Volume</div>
+                    <div class="metric-value">{m['volume_liters']:.2f} L</div>
+                </div>
+                <div class="metric-item">
+                    <div class="metric-label">📍 Centroid</div>
+                    <div class="metric-value">({m['centroid'][0]}, {m['centroid'][1]})</div>
+                </div>
+            </div>
+        </div>
+        """
+    
+    total_area = sum(m['area_m2'] for m in measurements)
+    total_volume = sum(m['volume_liters'] for m in measurements)
+    avg_depth = np.mean([m['max_depth_cm'] for m in measurements])
+    
+    html += f"""
+        <div class="summary-section">
+            <h3>📊 Overall Summary</h3>
+            <div style="display: grid; grid-template-columns: repeat(2, 1fr); gap: 10px;">
+                <div><strong>Total Potholes:</strong> {len(measurements)}</div>
+                <div><strong>Average Depth:</strong> {avg_depth:.2f} cm</div>
+                <div><strong>Total Area:</strong> {total_area:.4f} m²</div>
+                <div><strong>Total Volume:</strong> {total_volume:.2f} L</div>
+            </div>
+        </div>
+    </div>
+    """
+    
+    return html
+
+def generate_video_metrics_html(stats, total_frames, fps):
+    """Generate HTML metrics for video"""
+    if stats['total_potholes'] == 0:
+        return "<h3 style='color: orange;'>⚠️ No potholes detected</h3>"
+    
+    duration_str = str(timedelta(seconds=int(total_frames / fps)))
+    
+    html = f"""
+    <style>
+        .video-metrics {{
+            font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+            padding: 20px;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            border-radius: 15px;
+            color: white;
+        }}
+        .video-summary {{
+            background: rgba(255, 255, 255, 0.95);
+            border-radius: 10px;
+            padding: 15px;
+            margin: 10px 0;
+            color: #333;
+        }}
+        .pothole-track {{
+            background: rgba(255, 255, 255, 0.95);
+            border-radius: 10px;
+            padding: 15px;
+            margin: 10px 0;
+            color: #333;
+        }}
+        .severity-badge {{
+            padding: 5px 15px;
+            border-radius: 20px;
+            font-weight: bold;
+        }}
+        .severity-CRITICAL {{ background: #ff4444; color: white; }}
+        .severity-HIGH {{ background: #ff9800; color: white; }}
+        .severity-MEDIUM {{ background: #ffeb3b; color: #333; }}
+        .severity-LOW {{ background: #4caf50; color: white; }}
+    </style>
+    
+    <div class="video-metrics">
+        <div style="text-align: center; margin-bottom: 20px; font-size: 24px; font-weight: bold;">
+            🎥 Video Report
+        </div>
+        <div class="video-summary">
+            <h3>📊 Summary</h3>
+            <p><strong>Duration:</strong> {duration_str} | <strong>Potholes:</strong> {stats['total_potholes']}</p>
+        </div>
+    """
+    
+    for pothole in sorted(stats['potholes'], key=lambda x: x['track_id']):
+        severity_class = f"severity-{pothole['severity']}"
+        html += f"""
+        <div class="pothole-track">
+            <div style="display: flex; justify-content: space-between;">
+                <span>🕳️ ID: {pothole['track_id']}</span>
+                <span class="severity-badge {severity_class}">{pothole['severity']}</span>
+            </div>
+            <p><strong>Frames:</strong> {pothole['frames_detected']} | 
+               <strong>Max Depth:</strong> {pothole['max_depth_cm']:.2f} cm | 
+               <strong>Max Volume:</strong> {pothole['max_volume_liters']:.2f} L</p>
+        </div>
+        """
+    
+    html += "</div>"
+    return html
+
+def generate_summary_text(measurements):
+    """Generate text summary for images"""
+    if not measurements:
+        return "No potholes detected."
+    
+    summary = f"🔍 DETECTION SUMMARY\n{'='*50}\n\n"
+    summary += f"Total Potholes: {len(measurements)}\n\n"
+    
+    for m in measurements:
+        summary += f"{m['severity_color']} Pothole #{m['pothole_id']} - {m['severity']}\n"
+        summary += f"   Confidence: {m['confidence']*100:.1f}%\n"
+        summary += f"   Depth: {m['max_depth_cm']:.2f} cm\n"
+        summary += f"   Area: {m['area_m2']:.4f} m²\n"
+        summary += f"   Volume: {m['volume_liters']:.2f} L\n"
+        summary += f"   Centroid: ({m['centroid'][0]}, {m['centroid'][1]})\n\n"
+    
+    return summary
+
+def generate_video_summary_text(stats, total_frames, fps):
+    """Generate text summary for video"""
+    if stats['total_potholes'] == 0:
+        return "No potholes detected in video."
+    
+    duration_str = str(timedelta(seconds=int(total_frames / fps)))
+    
+    summary = f"🎥 VIDEO REPORT\n{'='*70}\n\n"
+    summary += f"Duration: {duration_str} | Frames: {total_frames:,} | FPS: {fps}\n"
+    summary += f"Unique Potholes: {stats['total_potholes']}\n\n"
+    
+    for pothole in sorted(stats['potholes'], key=lambda x: x['track_id']):
+        summary += f"🕳️ ID {pothole['track_id']} - {pothole['severity']}\n"
+        summary += f"   Frames: {pothole['frames_detected']}\n"
+        summary += f"   First: Frame {pothole['first_frame']} ({pothole['first_timestamp']})\n"
+        summary += f"   Max Depth: {pothole['max_depth_cm']:.2f} cm\n"
+        summary += f"   Max Volume: {pothole['max_volume_liters']:.2f} L\n\n"
+    
+    return summary