Adjusting UI for specific gradio version

gradio_test.py

@@ -49,7 +49,7 @@ DEVICE = "cuda" if torch.cuda.is_available() else "cpu"
 CPU_DEVICE = torch.device("cpu")
 torch.set_num_threads(4)
 
-# ADE20K class mappings for floor detection
+# ADE20K class mappings for floor detection - COMPREHENSIVE LIST
 FLOOR_CLASSES = {
     'floor': [3, 4, 13],  # floor, wood floor, rug
     'carpet': [28],       # carpet
@@ -170,13 +170,26 @@ class OneFormerManager:
 ########################################
 
 class ImprovedBlackspotDetector:
-    """Enhanced blackspot detector that only detects on floor surfaces"""
+    """Enhanced blackspot detector that ONLY detects on floor surfaces"""
 
     def __init__(self, model_path: str = None):
         self.model_path = model_path
         self.predictor = None
-        # Expanded floor-related classes in ADE20K
+        # STRICT floor-related classes in ADE20K - ONLY walking surfaces
         self.floor_classes = [3, 4, 13, 28, 78]  # floor, wood floor, rug, carpet, mat
+        # Explicitly exclude these classes
+        self.excluded_classes = [
+            5,    # ceiling
+            7,    # bed
+            10,   # sofa
+            15,   # table
+            19,   # chair
+            23,   # cabinet
+            30,   # desk
+            33,   # counter
+            34,   # stool
+            36,   # bench
+        ]
 
     def download_model(self) -> str:
         """Download blackspot model from HuggingFace"""
@@ -190,13 +203,13 @@ class ImprovedBlackspotDetector:
             return model_path
         except Exception as e:
             logger.warning(f"Could not download blackspot model from HF: {e}")
-            
+
             # Fallback to local path
             local_path = f"./output_floor_blackspot/{BLACKSPOT_MODEL_FILE}"
             if os.path.exists(local_path):
                 logger.info(f"Using local blackspot model: {local_path}")
                 return local_path
-            
+
             return None
 
     def initialize(self, threshold: float = 0.5) -> bool:
@@ -205,11 +218,11 @@ class ImprovedBlackspotDetector:
             # Get model path
             if self.model_path is None:
                 self.model_path = self.download_model()
-                
+
             if self.model_path is None:
                 logger.error("No blackspot model available")
                 return False
-            
+
             cfg = get_cfg()
             cfg.merge_from_file(
                 model_zoo.get_config_file("COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml")
@@ -232,9 +245,9 @@ class ImprovedBlackspotDetector:
         blackspot_mask: np.ndarray,
         segmentation: np.ndarray,
         floor_mask: np.ndarray,
-        overlap_threshold: float = 0.8
+        overlap_threshold: float = 0.9  # INCREASED threshold for stricter detection
     ) -> bool:
-        """Check if a blackspot is actually on a floor surface"""
+        """STRICTLY check if a blackspot is actually on a floor surface"""
         if np.sum(blackspot_mask) == 0:
             return False
 
@@ -249,12 +262,23 @@ class ImprovedBlackspotDetector:
         if len(blackspot_pixels) == 0:
             return False
 
+        # Check if ANY excluded class pixels are in the blackspot
         unique_classes, counts = np.unique(blackspot_pixels, return_counts=True)
+        for excluded_class in self.excluded_classes:
+            if excluded_class in unique_classes:
+                # If more than 5% of pixels belong to excluded class, reject
+                excluded_ratio = counts[unique_classes == excluded_class][0] / len(blackspot_pixels)
+                if excluded_ratio > 0.05:
+                    logger.debug(f"Rejected blackspot with {excluded_ratio:.2%} pixels on excluded class {excluded_class}")
+                    return False
+
+        # Verify floor pixels dominate
         floor_pixel_count = sum(
-            counts[unique_classes == cls] for cls in self.floor_classes if cls in unique_classes
+            counts[unique_classes == cls][0] if cls in unique_classes else 0 
+            for cls in self.floor_classes
         )
         floor_ratio = floor_pixel_count / len(blackspot_pixels)
-        return floor_ratio > 0.7  # At least 70% on floor classes
+        return floor_ratio > 0.85  # INCREASED to 85% floor pixels required
 
     def filter_non_floor_blackspots(
         self,
@@ -262,7 +286,7 @@ class ImprovedBlackspotDetector:
         segmentation: np.ndarray,
         floor_mask: np.ndarray
     ) -> List[np.ndarray]:
-        """Filter out blackspots that are not on floor surfaces"""
+        """STRICTLY filter out blackspots that are not on floor surfaces"""
         filtered_masks = []
         for mask in blackspot_masks:
             if self.is_on_floor_surface(mask, segmentation, floor_mask):
@@ -277,7 +301,7 @@ class ImprovedBlackspotDetector:
         segmentation: np.ndarray,
         floor_prior: Optional[np.ndarray] = None
     ) -> Dict:
-        """Detect blackspots only on floor surfaces"""
+        """Detect blackspots ONLY on floor surfaces with strict filtering"""
         if self.predictor is None:
             raise RuntimeError("Blackspot detector not initialized")
 
@@ -322,6 +346,7 @@ class ImprovedBlackspotDetector:
             for cls in self.floor_classes:
                 floor_mask |= (segmentation == cls)
 
+        # STRICT filtering of blackspots
         filtered_blackspot_masks = self.filter_non_floor_blackspots(
             blackspot_masks, segmentation, floor_mask
         )
@@ -356,12 +381,15 @@ class ImprovedBlackspotDetector:
         """Create clear visualization of blackspots on floors only"""
         vis = image.copy()
 
+        # Show floor areas in semi-transparent green
         floor_overlay = vis.copy()
         floor_overlay[floor_mask] = [0, 255, 0]
         vis = cv2.addWeighted(vis, 0.7, floor_overlay, 0.3, 0)
 
+        # Show blackspots in red
         vis[blackspot_mask] = [255, 0, 0]
 
+        # Draw contours around blackspots
         blackspot_contours, _ = cv2.findContours(
             blackspot_mask.astype(np.uint8), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE
         )
@@ -536,11 +564,11 @@ class NeuroNestApp:
         return stats
 
 ########################################
-# ENHANCED GRADIO INTERFACE
+# GRADIO INTERFACE (COMPATIBLE WITH 3.1.7)
 ########################################
 
 def create_gradio_interface():
-    """Create the enhanced Gradio interface with improved layout"""
+    """Create the Gradio interface compatible with version 3.1.7"""
 
     app = NeuroNestApp()
     oneformer_ok, blackspot_ok = app.initialize()
@@ -557,7 +585,7 @@ def create_gradio_interface():
     ):
         """Wrapper function for Gradio interface"""
         if image_path is None:
-            return None, None, None, "### ⚠️ Please upload an image to begin analysis"
+            return None, None, None, "Please upload an image"
 
         results = app.analyze_image(
             image_path=image_path,
@@ -568,7 +596,7 @@ def create_gradio_interface():
         )
 
         if "error" in results:
-            return None, None, None, f"### ❌ Error: {results['error']}"
+            return None, None, None, f"Error: {results['error']}"
 
         seg_output = results['segmentation']['visualization'] if results['segmentation'] else None
         blackspot_output = results['blackspot']['visualization'] if results['blackspot'] else None
@@ -595,660 +623,215 @@ def create_gradio_interface():
         return seg_output, blackspot_output, contrast_output, report
 
     def generate_comprehensive_report(results: Dict, contrast_report: str, blackspot_report: str) -> str:
-        """Generate comprehensive analysis report with enhanced formatting"""
+        """Generate comprehensive analysis report"""
         report = []
-        
-        # Header with timestamp
-        report.append("# 🧠 NeuroNest Environmental Safety Analysis Report")
-        report.append(f"*Generated: {time.strftime('%Y-%m-%d %H:%M:%S')}*")
-        report.append("---\n")
-
-        # Quick Summary Box
-        report.append("## 📊 Executive Summary")
-        
-        # Determine overall safety status
-        has_critical = False
-        has_issues = False
-        
-        if results['blackspot'] and results['statistics']['blackspot']['coverage_percentage'] > 0:
-            has_issues = True
-            if results['statistics']['blackspot']['coverage_percentage'] > 5:
-                has_critical = True
-        
-        if results['contrast'] and results['statistics']['contrast']['critical_issues'] > 0:
-            has_critical = True
-            has_issues = True
-        elif results['contrast'] and results['statistics']['contrast']['low_contrast_pairs'] > 0:
-            has_issues = True
-        
-        # Safety Status Box
-        if has_critical:
-            report.append("""
-<div style='background-color: #fef2f2; border: 2px solid #dc2626; padding: 15px; border-radius: 8px; margin: 10px 0;'>
-<h3 style='color: #dc2626; margin: 0;'>🚨 CRITICAL SAFETY ISSUES DETECTED</h3>
-<p style='margin: 5px 0 0 0;'><em>Immediate modifications required for Alzheimer's/dementia care safety</em></p>
-</div>
-            """)
-        elif has_issues:
-            report.append("""
-<div style='background-color: #fffbeb; border: 2px solid #f59e0b; padding: 15px; border-radius: 8px; margin: 10px 0;'>
-<h3 style='color: #f59e0b; margin: 0;'>⚠️ SAFETY CONCERNS IDENTIFIED</h3>
-<p style='margin: 5px 0 0 0;'><em>Several areas need improvement for optimal cognitive accessibility</em></p>
-</div>
-            """)
-        else:
-            report.append("""
-<div style='background-color: #f0fdf4; border: 2px solid #22c55e; padding: 15px; border-radius: 8px; margin: 10px 0;'>
-<h3 style='color: #22c55e; margin: 0;'>✅ ENVIRONMENT PASSES SAFETY ASSESSMENT</h3>
-<p style='margin: 5px 0 0 0;'><em>This space meets recommended standards for cognitive accessibility</em></p>
-</div>
-            """)
-        
-        report.append("\n---\n")
+        report.append("# 🧠 NeuroNest Analysis Report\n")
+        report.append(f"*Generated: {time.strftime('%Y-%m-%d %H:%M:%S')}*\n")
 
-        # Object Detection Results
         if results['segmentation']:
             stats = results['statistics'].get('segmentation', {})
-            report.append("## 🎯 Object Detection Results")
-            report.append(f"""
-<div style='background-color: #f3f4f6; padding: 15px; border-radius: 8px;'>
-<strong>Total Objects Identified:</strong> {stats.get('num_classes', 'N/A')}<br>
-<strong>Image Resolution:</strong> {stats.get('image_size', 'N/A')}<br>
-<em style='color: #6b7280;'>Successfully identified floors, walls, furniture, and other room elements</em>
-</div>
-            """)
+            report.append("## 🎯 Object Segmentation")
+            report.append(f"- **Classes detected:** {stats.get('num_classes', 'N/A')}")
+            report.append(f"- **Resolution:** {stats.get('image_size', 'N/A')}")
             report.append("")
 
-        # Blackspot Analysis Section
-        report.append("## ⚫ Floor Blackspot Analysis")
-        if results['blackspot'] and results['statistics']['blackspot']['coverage_percentage'] > 0:
-            report.append("### 🔍 Detection Results:")
-            report.append(f"""
-<div style='background-color: #1f2937; color: white; padding: 15px; border-radius: 8px; font-family: monospace;'>
-{blackspot_report}
-</div>
-            """)
-            
-            # Severity assessment with visual indicators
-            coverage = results['statistics']['blackspot']['coverage_percentage']
-            if coverage > 10:
-                severity_color = "#dc2626"
-                severity_text = "SEVERE"
-                severity_desc = "Large dark areas detected - High fall risk"
-                severity_icon = "⛔"
-            elif coverage > 5:
-                severity_color = "#ef4444"
-                severity_text = "HIGH RISK"
-                severity_desc = "Significant dark areas present"
-                severity_icon = "🔴"
-            elif coverage > 2:
-                severity_color = "#f59e0b"
-                severity_text = "MODERATE"
-                severity_desc = "Some dark areas that may cause confusion"
-                severity_icon = "🟡"
-            else:
-                severity_color = "#22c55e"
-                severity_text = "LOW"
-                severity_desc = "Minor dark areas detected"
-                severity_icon = "🟢"
-            
-            report.append(f"""
-<div style='background-color: {severity_color}22; border-left: 4px solid {severity_color}; padding: 10px; margin: 10px 0;'>
-<strong style='color: {severity_color};'>{severity_icon} {severity_text}:</strong> {severity_desc}
-</div>
-            """)
-        else:
-            report.append("""
-<div style='background-color: #f0fdf4; padding: 15px; border-radius: 8px;'>
-✅ <strong>No hazardous blackspots detected on floor surfaces</strong>
-</div>
-            """)
+        report.append("## ⚫ Blackspot Analysis (Floor Surfaces Only)")
+        report.append(blackspot_report)
         report.append("")
 
-        # Contrast Analysis Section
-        report.append("## 🎨 Universal Contrast Analysis")
-        if results['contrast'] and results['statistics']['contrast']['low_contrast_pairs'] > 0:
-            cs = results['statistics']['contrast']
-            
-            # Summary table with better styling
-            report.append("### 📈 Analysis Summary:")
-            report.append("""
-<table style='width: 100%; border-collapse: collapse; margin: 10px 0;'>
-<thead style='background-color: #f3f4f6;'>
-<tr>
-<th style='padding: 10px; text-align: left; border-bottom: 2px solid #e5e7eb;'>Severity Level</th>
-<th style='padding: 10px; text-align: center; border-bottom: 2px solid #e5e7eb;'>Count</th>
-<th style='padding: 10px; text-align: left; border-bottom: 2px solid #e5e7eb;'>Impact</th>
-</tr>
-</thead>
-<tbody>
-            """)
-            
-            report.append(f"""
-<tr style='background-color: #fef2f2;'>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'><strong>🔴 Critical</strong></td>
-<td style='padding: 10px; text-align: center; border-bottom: 1px solid #e5e7eb;'><strong>{cs['critical_issues']}</strong></td>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'>Immediate safety hazard</td>
-</tr>
-<tr style='background-color: #fffbeb;'>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'><strong>🟠 High</strong></td>
-<td style='padding: 10px; text-align: center; border-bottom: 1px solid #e5e7eb;'><strong>{cs['high_priority_issues']}</strong></td>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'>Significant navigation risk</td>
-</tr>
-<tr style='background-color: #fefce8;'>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'><strong>🟡 Medium</strong></td>
-<td style='padding: 10px; text-align: center; border-bottom: 1px solid #e5e7eb;'><strong>{cs['medium_priority_issues']}</strong></td>
-<td style='padding: 10px; border-bottom: 1px solid #e5e7eb;'>Potential confusion</td>
-</tr>
-</tbody>
-</table>
-            """)
-            
-            # Detailed issues
-            report.append("### ���� Detailed Findings:")
-            report.append("""
-<div style='background-color: #f9fafb; border: 1px solid #e5e7eb; padding: 15px; border-radius: 8px; font-family: monospace; font-size: 0.9em;'>
-<pre style='margin: 0; white-space: pre-wrap;'>""" + contrast_report + """</pre>
-</div>
-            """)
-        else:
-            report.append("""
-<div style='background-color: #f0fdf4; padding: 15px; border-radius: 8px;'>
-✅ <strong>All adjacent objects have sufficient contrast</strong><br>
-<em style='color: #6b7280;'>Environment meets WCAG 2.1 accessibility guidelines</em>
-</div>
-            """)
+        report.append("## 🎨 Universal Contrast Analysis (All Adjacent Objects)")
+        report.append(contrast_report)
         report.append("")
 
-        # Recommendations Section
-        report.append("## 💡 Actionable Recommendations")
-        
-        recommendations = []
-        
+        report.append("## 📋 Recommendations for Alzheimer's Care")
+
+        has_issues = False
+
         if results['blackspot'] and results['statistics']['blackspot']['coverage_percentage'] > 0:
-            recommendations.append({
-                'priority': 'HIGH',
-                'category': 'Blackspot Mitigation',
-                'icon': '💡',
-                'actions': [
-                    "Install brighter LED lighting (3000+ lumens) in affected areas",
-                    "Replace dark flooring with light-colored alternatives (beige, light gray)",
-                    "Add light-colored area rugs or runners over dark spots",
-                    "Install motion-activated pathway lighting at floor level"
-                ]
-            })
-        
-        if results['contrast']:
-            critical_count = results['statistics']['contrast']['critical_issues']
-            high_count = results['statistics']['contrast']['high_priority_issues']
-            
-            if critical_count > 0:
-                recommendations.append({
-                    'priority': 'CRITICAL',
-                    'category': 'Critical Contrast Improvements',
-                    'icon': '🚨',
-                    'actions': [
-                        "Paint doors in colors that contrast strongly with walls (e.g., dark blue doors on light walls)",
-                        "Add high-contrast tape or strips to stair edges",
-                        "Install contrasting baseboards between floors and walls",
-                        "Use furniture colors that contrast with both floor and wall colors"
-                    ]
-                })
-            
-            if high_count > 0:
-                recommendations.append({
-                    'priority': 'HIGH',
-                    'category': 'High Priority Contrast Fixes',
-                    'icon': '⚠️',
-                    'actions': [
-                        "Replace similar-colored furniture with contrasting alternatives",
-                        "Add colorful cushions or throws to distinguish seating",
-                        "Install LED strip lighting under furniture edges",
-                        "Use contrasting placemats and table runners"
-                    ]
-                })
-        
-        if recommendations:
-            # Sort by priority
-            priority_order = {'CRITICAL': 0, 'HIGH': 1, 'MEDIUM': 2}
-            recommendations.sort(key=lambda x: priority_order.get(x['priority'], 3))
-            
-            for rec in recommendations:
-                if rec['priority'] == 'CRITICAL':
-                    bg_color = "#fef2f2"
-                    border_color = "#dc2626"
-                    timeline = "IMMEDIATE ACTION REQUIRED"
-                elif rec['priority'] == 'HIGH':
-                    bg_color = "#fffbeb"
-                    border_color = "#f59e0b"
-                    timeline = "Address Within 1 Week"
-                else:
-                    bg_color = "#f0f9ff"
-                    border_color = "#3b82f6"
-                    timeline = "Address Within 1 Month"
-                
-                report.append(f"""
-<div style='background-color: {bg_color}; border-left: 4px solid {border_color}; padding: 15px; margin: 15px 0; border-radius: 4px;'>
-<h3 style='margin: 0 0 10px 0; color: {border_color};'>{rec['icon']} {rec['category']}</h3>
-<p style='margin: 0 0 10px 0; font-style: italic; color: #6b7280;'>{timeline}</p>
-<ul style='margin: 0; padding-left: 20px;'>
-                """)
-                
-                for action in rec['actions']:
-                    report.append(f"<li style='margin: 5px 0;'>{action}</li>")
-                
-                report.append("""
-</ul>
-</div>
-                """)
-        else:
-            report.append("""
-<div style='background-color: #f0fdf4; padding: 20px; border-radius: 8px; text-align: center;'>
-<h3 style='color: #22c55e; margin: 0;'>✅ No immediate actions required</h3>
-<p style='margin: 10px 0 0 0;'>This environment is well-optimized for individuals with Alzheimer's or dementia.</p>
-</div>
-            """)
-        
-        # Footer
-        report.append("""
----
-<div style='text-align: center; color: #6b7280; margin-top: 30px; font-size: 0.9em;'>
-<em>Report generated by NeuroNest v2.0 - Texas State University</em>
-</div>
-        """)
-        
+            has_issues = True
+            report.append("\n### Blackspot Mitigation:")
+            report.append("- Replace dark flooring materials with lighter alternatives (min 70% luminance)")
+            report.append("- Install 3000+ lumen LED lighting in affected areas")
+            report.append("- Use light-colored rugs or runners to cover dark spots")
+            report.append("- Add contrasting tape or markers around blackspot perimeters")
+
+        if results['contrast'] and results['statistics']['contrast']['low_contrast_pairs'] > 0:
+            has_issues = True
+            report.append("\n### Contrast Improvements:")
+            
+            # Get specific recommendations based on issue types
+            contrast_issues = results['contrast']['issues']
+            critical_issues = [i for i in contrast_issues if i['severity'] == 'critical']
+            high_issues = [i for i in contrast_issues if i['severity'] == 'high']
+            
+            if critical_issues:
+                report.append("\n**CRITICAL - Immediate attention required:**")
+                for issue in critical_issues[:3]:
+                    cat1, cat2 = issue['categories']
+                    wcag = issue['wcag_ratio']
+                    report.append(f"- {cat1.title()} ↔ {cat2.title()}: Current {wcag:.1f}:1, Need 7:1 minimum")
+                    report.append(f"  - Hue difference: {issue['hue_difference']:.0f}° (need >30°)")
+                    report.append(f"  - Saturation difference: {issue['saturation_difference']:.0f}% (need >50%)")
+            
+            if high_issues:
+                report.append("\n**HIGH PRIORITY:**")
+                for issue in high_issues[:3]:
+                    cat1, cat2 = issue['categories']
+                    wcag = issue['wcag_ratio']
+                    report.append(f"- {cat1.title()} ↔ {cat2.title()}: Current {wcag:.1f}:1, Need 4.5:1 minimum")
+            
+            report.append("\n**General recommendations:**")
+            report.append("- Use warm colors (red, yellow, orange) for important objects")
+            report.append("- Maintain 70% luminance difference between adjacent surfaces")
+            report.append("- Avoid similar hues - ensure 30+ degree separation on color wheel")
+            report.append("- Use high saturation colors, avoid pastels or muted tones")
+            report.append("- Add textured surfaces to supplement color contrast")
+
+        if not has_issues:
+            report.append("\n✅ **Excellent!** This environment appears well-optimized for individuals with Alzheimer's.")
+            report.append("No significant visual hazards detected.")
+
         return "\n".join(report)
 
-    # Custom CSS for enhanced styling
-    css = """
-    .gradio-container {
-        font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, sans-serif;
-        max-width: 1400px !important;
-        margin: 0 auto;
-    }
-    .main-header {
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
-        color: white;
-        padding: 2rem;
-        border-radius: 12px;
-        margin-bottom: 2rem;
-        text-align: center;
-    }
-    .main-header h1 {
-        margin: 0 0 0.5rem 0;
-        font-size: 2.5rem;
-        font-weight: 700;
-    }
-    .main-header p {
-        margin: 0;
-        opacity: 0.9;
-        font-size: 1.1rem;
-    }
-    .control-panel {
-        background-color: #f9fafb;
-        border: 1px solid #e5e7eb;
-        border-radius: 12px;
-        padding: 1.5rem;
-        margin-bottom: 1.5rem;
-    }
-    .info-box {
-        background-color: #eff6ff;
-        border: 1px solid #3b82f6;
-        border-radius: 8px;
-        padding: 1rem;
-        margin: 1rem 0;
-    }
-    .warning-box {
-        background-color: #fef3c7;
-        border: 1px solid #f59e0b;
-        border-radius: 8px;
-        padding: 1rem;
-        margin: 1rem 0;
-    }
-    .button-primary {
-        background: linear-gradient(135deg, #667eea 0%, #764ba2 100%) !important;
-        color: white !important;
-        font-size: 1.2rem !important;
-        font-weight: 600 !important;
-        padding: 14px 28px !important;
-        border-radius: 8px !important;
-        border: none !important;
-        cursor: pointer !important;
-        transition: transform 0.2s !important;
-    }
-    .button-primary:hover {
-        transform: translateY(-2px) !important;
-        box-shadow: 0 10px 20px rgba(0,0,0,0.1) !important;
-    }
-    .result-section {
-        margin-top: 2rem;
-    }
-    .markdown-text {
-        font-size: 1.05rem;
-        line-height: 1.7;
-        color: #1f2937;
-    }
-    .analysis-report {
-        background-color: #ffffff;
-        border: 1px solid #e5e7eb;
-        border-radius: 12px;
-        padding: 2rem;
-        margin-top: 1.5rem;
-        box-shadow: 0 1px 3px rgba(0,0,0,0.1);
-    }
+    title = "🧠 NeuroNest: AI-Powered Environment Safety Analysis"
+    description = """
+    **Advanced visual analysis for Alzheimer's and dementia care environments.**
+    
+    **Texas State CS & Interior Design Dept. - Abheek Pradhan, Dr. Nadim Adi, Dr. Greg Lakomski**
+
+    This system provides:
+    - **Object Segmentation**: Identifies all room elements (floors, walls, furniture)
+    - **Floor-Only Blackspot Detection**: Locates dangerous dark areas ONLY on walking surfaces
+    - **Universal Contrast Analysis**: Evaluates visibility between ALL adjacent objects
+
+    *Following WCAG 2.1 guidelines and dementia-specific visual accessibility standards*
     """
 
-    with gr.Blocks(css=css, title="NeuroNest - Environmental Safety Analysis") as interface:
-        # Enhanced Header
-        gr.HTML("""
-        <div class="main-header">
-            <h1>🧠 NeuroNest: AI-Powered Environment Safety Analysis</h1>
-            <p>Advanced visual analysis for Alzheimer's and dementia care environments</p>
-            <p style="font-size: 0.9rem; margin-top: 0.5rem;">Texas State CS & Interior Design Dept. • Abheek Pradhan, Dr. Nadim Adi, Dr. Greg Lakomski</p>
-        </div>
-        """)
-        
-        # Quick Start Guide
-        with gr.Row():
-            gr.HTML("""
-            <div class="info-box" style="width: 100%;">
-                <h3 style="margin-top: 0;">🚀 Quick Start Guide</h3>
-                <ol style="margin: 10px 0;">
-                    <li><strong>Upload</strong> a well-lit photo of the room</li>
-                    <li><strong>Adjust</strong> detection settings if needed (optional)</li>
-                    <li><strong>Click</strong> "Analyze Environment" button</li>
-                    <li><strong>Review</strong> the visual results and detailed report below</li>
-                </ol>
-                <p style="margin-bottom: 0;"><em>The analysis identifies safety hazards and provides actionable recommendations for creating dementia-friendly spaces.</em></p>
-            </div>
-            """)
+    # Create interface compatible with Gradio 3.1.7
+    with gr.Blocks(title="NeuroNest") as interface:
+        gr.Markdown(f"# {title}")
+        gr.Markdown(description)
 
-        # System status notification
+        # Information about model availability
         if not blackspot_ok:
-            gr.HTML("""
-            <div class="warning-box">
-                <strong>⚠️ Limited Functionality:</strong> Blackspot detection model not available. 
-                Upload the model to HuggingFace or place in local directory to enable floor hazard detection.
-            </div>
+            gr.Markdown("""
+            ⚠️ **Note:** Blackspot detection model not available. 
+            To enable blackspot detection, upload the model to HuggingFace or ensure it's in the local directory.
             """)
 
-        # Analysis Controls Section
-        with gr.Group():
-            gr.Markdown("## 🎛️ Analysis Settings")
-            
-            with gr.Row():
-                with gr.Column(scale=1):
-                    gr.HTML("""
-                    <div class="control-panel">
-                        <h4 style="margin-top: 0;">🔍 Detection Options</h4>
-                    """)
-                    
-                    enable_blackspot = gr.Checkbox(
-                        value=blackspot_ok,
-                        label="Enable Floor Blackspot Detection",
-                        info="Identifies dark areas on floors that may appear as holes to people with dementia",
-                        interactive=blackspot_ok,
-                        elem_classes="checkbox-custom"
-                    )
-                    
-                    blackspot_threshold = gr.Slider(
-                        minimum=0.1,
-                        maximum=0.9,
-                        value=0.5,
-                        step=0.05,
-                        label="Detection Sensitivity",
-                        info="Lower values detect lighter shadows • Higher values detect only very dark areas",
-                        visible=blackspot_ok,
-                        elem_classes="slider-custom"
-                    )
-                    
-                    gr.HTML("</div>")
-                
-                with gr.Column(scale=1):
-                    gr.HTML("""
-                    <div class="control-panel">
-                        <h4 style="margin-top: 0;">🎨 Contrast Analysis</h4>
-                    """)
-                    
-                    enable_contrast = gr.Checkbox(
-                        value=True,
-                        label="Enable Universal Contrast Analysis",
-                        info="Evaluates visibility between all adjacent objects (walls, floors, furniture)",
-                        elem_classes="checkbox-custom"
-                    )
-                    
-                    contrast_threshold = gr.Slider(
-                        minimum=3.0,
-                        maximum=7.0,
-                        value=4.5,
-                        step=0.1,
-                        label="WCAG Contrast Threshold",
-                        info="4.5:1 = Standard accessibility • 7:1 = Enhanced for critical areas",
-                        elem_classes="slider-custom"
-                    )
-                    
-                    gr.HTML("</div>")
-
-        # Image Upload Section
-        with gr.Group():
-            gr.Markdown("## 📸 Room Image Upload")
-            
-            with gr.Row():
-                with gr.Column(scale=2):
-                    image_input = gr.Image(
-                        label="Upload Room Photo",
-                        type="filepath",
-                        height=400,
-                        elem_classes="image-upload"
-                    )
-                    
-                    analyze_button = gr.Button(
-                        "🔍 Analyze Environment",
-                        variant="primary",
-                        size="lg",
-                        elem_classes="button-primary"
-                    )
-                
-                with gr.Column(scale=1):
-                    gr.HTML("""
-                    <div class="info-box">
-                        <h4 style="margin-top: 0;">📷 Photo Guidelines</h4>
-                        <ul style="margin: 10px 0;">
-                            <li>Stand in corner for wide view</li>
-                            <li>Include floor, walls & furniture</li>
-                            <li>Turn on all room lights</li>
-                            <li>Avoid shadows and glare</li>
-                            <li>Use horizontal orientation</li>
-                        </ul>
-                        <p style="margin-bottom: 0;"><strong>Best:</strong> Daytime photos with natural light</p>
-                    </div>
-                    """)
-
-        # Results Section
-        with gr.Group():
-            gr.Markdown("## 🔬 Visual Analysis Results")
-            
-            gr.HTML("""
-            <p style="color: #6b7280; margin-bottom: 1rem;">
-            Hover over images for details • Colors indicate: 🟢 Safe • 🟡 Caution • 🔴 Hazard
-            </p>
-            """)
+        # Create two columns using Row for controls
+        with gr.Row():
+            with gr.Column():
+                gr.Markdown("### Detection Options")
+                enable_blackspot = gr.Checkbox(
+                    value=blackspot_ok,
+                    label="Enable Floor Blackspot Detection",
+                    interactive=blackspot_ok
+                )
+                blackspot_threshold = gr.Slider(
+                    minimum=0.1,
+                    maximum=0.9,
+                    value=0.5,
+                    step=0.05,
+                    label="Blackspot Sensitivity",
+                    visible=blackspot_ok
+                )
+            
+            with gr.Column():
+                gr.Markdown("### Contrast Analysis")
+                enable_contrast = gr.Checkbox(
+                    value=True,
+                    label="Enable Universal Contrast Analysis"
+                )
+                contrast_threshold = gr.Slider(
+                    minimum=3.0,
+                    maximum=7.0,
+                    value=4.5,
+                    step=0.1,
+                    label="WCAG Contrast Threshold"
+                )
+
+        # Image upload and analyze button
+        with gr.Row():
+            with gr.Column():
+                image_input = gr.Image(
+                    label="📸 Upload Room Image",
+                    type="filepath"
+                )
+                analyze_button = gr.Button(
+                    "🔍 Analyze Environment",
+                    variant="primary"
+                )
+
+        # Results display
+        gr.Markdown("## Analysis Results")
+        
+        with gr.Row():
+            seg_display = gr.Image(
+                label="🎯 Segmented Objects",
+                interactive=False
+            )
             
+        if blackspot_ok:
             with gr.Row():
-                with gr.Column():
-                    seg_display = gr.Image(
-                        label="🎯 Object Segmentation",
-                        height=300,
-                        interactive=False,
-                        elem_classes="result-image"
-                    )
-                    gr.HTML("""
-                    <p style="text-align: center; color: #6b7280; font-size: 0.9rem; margin-top: 0.5rem;">
-                    Identifies all room elements
-                    </p>
-                    """)
-                
-                with gr.Column():
-                    blackspot_display = gr.Image(
-                        label="⚫ Floor Blackspot Detection",
-                        height=300,
-                        interactive=False,
-                        visible=blackspot_ok,
-                        elem_classes="result-image"
-                    )
-                    if blackspot_ok:
-                        gr.HTML("""
-                        <p style="text-align: center; color: #6b7280; font-size: 0.9rem; margin-top: 0.5rem;">
-                        Red = Hazardous dark areas
-                        </p>
-                        """)
-                
-                with gr.Column():
-                    contrast_display = gr.Image(
-                        label="🎨 Contrast Analysis",
-                        height=300,
-                        interactive=False,
-                        elem_classes="result-image"
-                    )
-                    gr.HTML("""
-                    <p style="text-align: center; color: #6b7280; font-size: 0.9rem; margin-top: 0.5rem;">
-                    Colored borders = Low contrast
-                    </p>
-                    """)
-
-        # Detailed Report Section
-        with gr.Group():
-            gr.Markdown("## 📊 Comprehensive Safety Report")
+                blackspot_display = gr.Image(
+                    label="⚫ Blackspot Detection (Floor Only)",
+                    interactive=False
+                )
+        else:
+            blackspot_display = gr.Image(visible=False)
             
-            analysis_report = gr.Markdown(
-                value="""
-                <div style='text-align: center; padding: 3rem; color: #6b7280;'>
-                    <p style='font-size: 1.2rem;'>📤 Upload an image and click 'Analyze Environment' to generate your safety report</p>
-                    <p>The report will include detailed findings and personalized recommendations</p>
-                </div>
-                """,
-                elem_classes="analysis-report markdown-text"
+        with gr.Row():
+            contrast_display = gr.Image(
+                label="🎨 Contrast Analysis (All Adjacent Objects)",
+                interactive=False
             )
 
-        # Detailed Guide (Collapsible)
-        with gr.Accordion("📚 Detailed User Guide & Best Practices", open=False):
-            gr.Markdown("""
-            ## 🎯 Understanding the Analysis
-            
-            ### What Each Analysis Does:
-            
-            **1. Object Segmentation** 🎯
-            - Identifies all elements in the room (floors, walls, furniture, etc.)
-            - Creates a foundation map for other analyses
-            - Helps understand spatial relationships
-            
-            **2. Floor Blackspot Detection** ⚫
-            - Finds dark areas on walking surfaces only
-            - Ignores shadows on walls or furniture
-            - Critical for preventing falls in dementia patients
-            
-            **3. Universal Contrast Analysis** 🎨
-            - Examines color differences between ALL adjacent objects
-            - Not just floor-to-furniture, but everything touching
-            - Ensures clear visual boundaries throughout the space
-            
-            ### 📊 Interpreting Results:
-            
-            **Severity Levels:**
-            - **🔴 Critical**: Immediate safety hazard - fix within 24 hours
-            - **🟠 High**: Significant risk - address within 1 week  
-            - **🟡 Medium**: Potential confusion - fix within 1 month
-            - **🟢 Low/Safe**: Acceptable for most individuals
-            
-            **WCAG Contrast Ratios:**
-            - **3:1** - Minimum for large text/graphics
-            - **4.5:1** - Standard for normal text (recommended)
-            - **7:1** - Enhanced for critical areas like stairs
-            
-            ### 💡 Common Issues & Solutions:
-            
-            **Low Contrast Problems:**
-            - White walls + beige furniture → Add colorful cushions
-            - Similar floor/wall colors → Install contrasting baseboards
-            - Invisible door frames → Paint doors in contrasting colors
-            
-            **Blackspot Hazards:**
-            - Dark rugs on light floors → Replace with light colors
-            - Shadows from poor lighting → Add floor-level LED strips
-            - Dark flooring materials → Install light-colored overlays
-            
-            ### 🏠 Room-Specific Tips:
-            
-            **Living Room:**
-            - Ensure sofa contrasts with floor AND wall
-            - Coffee tables need defined edges
-            - Pathways should be clearly visible
-            
-            **Bedroom:**
-            - Bed frame must contrast with floor
-            - Night path to bathroom needs good visibility
-            - Nightstands should stand out from walls
-            
-            **Bathroom:**
-            - Critical contrast between floor and fixtures
-            - Non-slip surfaces in contrasting colors
-            - Grab bars in colors that pop against walls
-            
-            ### 📸 Taking Better Photos:
-            
-            1. **Lighting**: Turn on ALL lights, open curtains
-            2. **Angle**: Stand in corner, capture whole room
-            3. **Height**: Hold camera at eye level
-            4. **Multiple**: Take several angles if needed
-            5. **Quality**: Higher resolution = better analysis
-            
-            ### ⚠️ Special Considerations:
-            
-            - Patterns can be confusing - solid colors work better
-            - Glossy surfaces may create false shadows
-            - Consider time of day - shadows change
-            - Test changes with actual lighting conditions
-            """)
+        # Analysis report
+        gr.Markdown("## Detailed Analysis Report")
+        analysis_report = gr.Markdown(
+            value="Upload an image and click 'Analyze Environment' to begin."
+        )
 
-        # Resource Links
-        with gr.Row():
-            gr.HTML("""
-            <div style='background-color: #f3f4f6; padding: 20px; border-radius: 12px; margin-top: 2rem;'>
-                <h4 style='margin-top: 0;'>📚 Additional Resources</h4>
-                <div style='display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 15px;'>
-                    <div>
-                        <strong>🔗 WCAG Guidelines</strong><br>
-                        <a href='https://www.w3.org/WAI/WCAG21/quickref/' target='_blank'>Web Accessibility Standards</a>
-                    </div>
-                    <div>
-                        <strong>🏠 Dementia Design</strong><br>
-                        <a href='https://www.alzheimers.org.uk/get-support/making-your-home-dementia-friendly' target='_blank'>Home Modification Guide</a>
-                    </div>
-                    <div>
-                        <strong>💡 Lighting Tips</strong><br>
-                        <a href='https://www.dementia.org.au/resources/good-design' target='_blank'>Illumination Best Practices</a>
-                    </div>
-                    <div>
-                        <strong>🎨 Color Contrast</strong><br>
-                        <a href='https://webaim.org/resources/contrastchecker/' target='_blank'>Online Contrast Checker</a>
-                    </div>
-                </div>
-            </div>
+        # Additional information
+        with gr.Accordion("📚 Understanding the Analysis", open=False):
+            gr.Markdown("""
+            ### Color Contrast Guidelines for Alzheimer's Care:
+            
+            **WCAG Contrast Requirements:**
+            - **3:1** - Absolute minimum for large graphics
+            - **4.5:1** - Standard for normal visibility
+            - **7:1** - Enhanced for critical areas (stairs, doors)
+            
+            **Additional Perceptual Requirements:**
+            - **Hue Difference**: >30° on color wheel
+            - **Saturation Difference**: >50% for clear distinction
+            - **Luminance Difference**: >70% between surfaces
+            
+            **Priority Areas:**
+            1. **Critical**: Floor-stairs, floor-door, wall-stairs
+            2. **High**: Floor-furniture, wall-door, wall-furniture
+            3. **Medium**: All other adjacent objects
+            
+            ### Blackspot Detection:
+            - **ONLY** detects dark areas on floors, rugs, carpets, and mats
+            - **EXCLUDES** shadows on furniture, tables, ceilings, walls
+            - Dark floor areas can appear as "holes" to dementia patients
+            
+            ### Best Practices:
+            - Use warm colors (red, yellow, orange) for visibility
+            - Avoid pastels and muted tones
+            - Ensure all adjacent objects have distinct colors
+            - Add texture to supplement color contrast
             """)
 
-        # Footer
-        gr.HTML("""
-        <div style='text-align: center; color: #6b7280; margin-top: 3rem; padding: 2rem; border-top: 1px solid #e5e7eb;'>
-            <p><strong>NeuroNest v2.0</strong> • Enhanced AI-Powered Environmental Safety Analysis</p>
-            <p style='font-size: 0.9rem;'>Creating safer spaces for cognitive health through computer vision and AI</p>
-            <p style='font-size: 0.85rem; margin-top: 1rem;'>
-                © 2024 Texas State University • Computer Science & Interior Design Departments<br>
-                For research collaboration: neuronest@txstate.edu
-            </p>
-        </div>
+        gr.Markdown("""
+        ---
+        **NeuroNest** v2.0 - Creating safer environments for cognitive health through AI  
+        *Strict floor-only blackspot detection & comprehensive contrast analysis*
         """)
 
-        # Event handlers
+        # Connect the analyze button
         analyze_button.click(
             fn=analyze_wrapper,
             inputs=[
@@ -1260,7 +843,7 @@ def create_gradio_interface():
             ],
             outputs=[
                 seg_display,
-                blackspot_display,
+                blackspot_display if blackspot_ok else seg_display,  # Dummy output if not available
                 contrast_display,
                 analysis_report
             ]