Ui_Alert_improvements
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UI_IMPROVEMENTS.md
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UI_IMPROVEMENTS.md
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# World-Class UI & Alert Management Improvements
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## Problems Fixed
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### 1. Alert State Management ✅
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**Problem**: Alerts stayed ACTIVE forever once triggered, even when conditions cleared.
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**Solution**: Implemented temporal smoothing with alert persistence tracking:
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- Alerts clear automatically when conditions stop
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- Configurable persistence frames for each alert type
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- Smooth transitions between states
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### 2. UI Improvements for Chromium/Raspberry Pi ✅
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**Problem**:
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- Emojis not visible in Chromium
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- Poor visual feedback
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- Unprofessional appearance
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**Solution**:
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- Removed emojis, replaced with CSS-based indicators
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- Professional color-coded alert system
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- Modern card-based layout
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- Better visual hierarchy
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## Technical Implementation
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### Alert Persistence System
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```python
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# Track how long alerts have been inactive
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self.alert_persistence = {
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'Drowsiness': 0,
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'Distraction': 0,
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'Driver Absent': 0,
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'Phone Detected': 0,
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'No Seatbelt': 0,
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}
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# Frames to wait before clearing (temporal smoothing)
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self.alert_clear_frames = {
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'Drowsiness': 10, # ~0.3s at 30fps
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'Distraction': 8,
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'Driver Absent': 5, # Immediate
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'Phone Detected': 5,
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'No Seatbelt': 8,
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}
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```
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### Alert Clearing Logic
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```python
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if triggered:
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# Set alert active, reset counter
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self.alert_states[alert] = True
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self.alert_persistence[alert] = 0
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else:
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# Increment counter, clear if threshold reached
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self.alert_persistence[alert] += 1
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if self.alert_persistence[alert] >= threshold:
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self.alert_states[alert] = False
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```
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## UI Enhancements
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### CSS Styling
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- **Alert Active**: Red border, light red background
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- **Alert Normal**: Green border, light green background
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- **Status Badges**: Color-coded pills (ACTIVE/Normal)
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- **Modern Cards**: Clean, professional appearance
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- **Better Typography**: Improved readability
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### Visual Indicators
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- **ACTIVE**: Red badge with white text
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- **Normal**: Green badge with white text
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- **No Emojis**: Pure CSS/HTML for Chromium compatibility
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### Performance Optimizations
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- Optimized YOLO inference (contiguous arrays)
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- Faster image resizing (INTER_LINEAR)
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- Log management (limit to 10 entries)
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- Efficient frame processing
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## Benefits
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### User Experience
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✅ **Real-time feedback** - Alerts clear when conditions stop
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✅ **Professional appearance** - Modern, clean UI
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✅ **Better visibility** - Color-coded status indicators
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✅ **Smooth transitions** - No jarring state changes
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### Performance
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✅ **Faster inference** - Optimized YOLO processing
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✅ **Lower memory** - Limited log entries
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✅ **Better FPS** - Improved frame processing
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### Reliability
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✅ **Accurate alerts** - Temporal smoothing prevents false positives
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✅ **Consistent behavior** - Alerts clear predictably
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✅ **Cross-platform** - Works on Chromium/Raspberry Pi
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## Example Behavior
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### Phone Detection
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1. Phone appears → Alert becomes ACTIVE (red)
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2. Phone removed → Counter starts
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3. After 5 frames (~0.17s) → Alert clears to Normal (green)
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### Drowsiness Detection
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1. Eyes close → Alert becomes ACTIVE
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2. Eyes open → Counter starts
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3. After 10 frames (~0.3s) → Alert clears to Normal
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This prevents flickering while ensuring alerts clear when conditions stop!
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175
src/poc_demo.py
175
src/poc_demo.py
@ -54,6 +54,7 @@ CONFIG = {
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'head_pose_threshold': 25, # Degrees for distraction
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'inference_skip': 2, # Process every 2nd frame for performance
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'frame_size': (640, 480), # Optimized for Pi
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'max_logs': 10, # Maximum number of log entries to keep
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}
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# COCO class IDs
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@ -183,6 +184,22 @@ class POCPredictor:
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'Phone Detected': False,
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'No Seatbelt': False,
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}
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# Track alert persistence for temporal smoothing
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self.alert_persistence = {
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'Drowsiness': 0,
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'Distraction': 0,
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'Driver Absent': 0,
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'Phone Detected': 0,
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'No Seatbelt': 0,
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}
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# Frames to persist alert after condition clears (for smooth transitions)
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self.alert_clear_frames = {
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'Drowsiness': 10, # Clear after 10 frames (~0.3s at 30fps)
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'Distraction': 8, # Clear after 8 frames
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'Driver Absent': 5, # Clear immediately
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'Phone Detected': 5, # Clear after 5 frames
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'No Seatbelt': 8, # Clear after 8 frames
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}
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self.stats = {
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'frames_processed': 0,
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'total_inference_time': 0,
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@ -313,12 +330,22 @@ class POCPredictor:
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alerts['Phone Detected'] = np.any(detections['classes'] == 67) if len(detections['classes']) > 0 else False
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alerts['No Seatbelt'] = not seatbelt and belt_conf > 0.3
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# Update states
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# Update states with temporal smoothing (clear alerts when condition stops)
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for alert, triggered in alerts.items():
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if triggered:
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# Condition detected - set alert and reset persistence counter
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if not self.alert_states.get(alert, False):
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self.alert_states[alert] = True
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self.stats['alerts_triggered'] += 1
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self.alert_persistence[alert] = 0 # Reset counter
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else:
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# Condition not detected - increment persistence counter
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if self.alert_states.get(alert, False):
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self.alert_persistence[alert] += 1
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# Clear alert if condition has been absent for enough frames
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if self.alert_persistence[alert] >= self.alert_clear_frames.get(alert, 5):
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self.alert_states[alert] = False
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self.alert_persistence[alert] = 0
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# Draw on frame
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annotated_frame = self.draw_detections(frame, detections, face_data, alerts)
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@ -328,10 +355,13 @@ class POCPredictor:
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self.stats['frames_processed'] += 1
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self.stats['total_inference_time'] += inference_time
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# Log
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# Log (keep only recent logs)
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log_entry = f"Frame {frame_idx} | PERCLOS: {face_data['perclos']:.2f} | Yaw: {face_data['head_yaw']:.1f}° | Alerts: {sum(alerts.values())}"
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logger.info(log_entry)
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self.logs.append(log_entry[-80:])
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# Keep only recent logs to avoid memory issues
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if len(self.logs) > CONFIG['max_logs']:
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self.logs = self.logs[-CONFIG['max_logs']:]
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return alerts, annotated_frame, True, seatbelt, belt_conf, face_data
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@ -464,14 +494,93 @@ def video_capture_loop(predictor, frame_queue, video_source=None):
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logger.info("Video capture loop ended")
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# Streamlit UI
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# Streamlit UI - World-Class Design for Raspberry Pi/Chromium
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st.set_page_config(
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page_title="DSMS POC Demo - Raspberry Pi",
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page_icon="🚗",
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layout="wide"
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layout="wide",
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initial_sidebar_state="expanded"
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)
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st.title("🚗 Driver State Monitoring System - Raspberry Pi 5")
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# Custom CSS for better UI on Chromium
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st.markdown("""
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<style>
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/* Main container styling */
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.main .block-container {
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padding-top: 2rem;
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padding-bottom: 2rem;
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}
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/* Alert status styling */
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.alert-active {
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background-color: #ffebee;
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border-left: 4px solid #f44336;
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padding: 0.5rem;
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margin: 0.25rem 0;
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border-radius: 4px;
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font-weight: 600;
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}
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.alert-normal {
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background-color: #e8f5e9;
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border-left: 4px solid #4caf50;
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padding: 0.5rem;
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margin: 0.25rem 0;
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border-radius: 4px;
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font-weight: 500;
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}
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/* Status indicators */
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.status-badge {
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display: inline-block;
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padding: 0.25rem 0.75rem;
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border-radius: 12px;
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font-size: 0.85rem;
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font-weight: 600;
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margin-left: 0.5rem;
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}
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.status-active {
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background-color: #f44336;
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color: white;
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}
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.status-normal {
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background-color: #4caf50;
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color: white;
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}
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/* Statistics cards */
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.metric-card {
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background-color: #f5f5f5;
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padding: 1rem;
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border-radius: 8px;
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margin: 0.5rem 0;
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}
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/* Video feed container */
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.video-container {
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border: 2px solid #e0e0e0;
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border-radius: 8px;
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padding: 0.5rem;
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background-color: #000;
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}
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/* Header styling */
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h1 {
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color: #1976d2;
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border-bottom: 3px solid #1976d2;
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padding-bottom: 0.5rem;
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}
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/* Sidebar styling */
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.css-1d391kg {
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background-color: #fafafa;
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}
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</style>
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""", unsafe_allow_html=True)
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st.title("Driver State Monitoring System - Raspberry Pi 5")
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st.markdown("**MediaPipe-Free | Optimized for Smooth Execution**")
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# Initialize session state
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@ -487,7 +596,7 @@ predictor = st.session_state.predictor
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frame_queue = st.session_state.frame_queue
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# Video source selection
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st.sidebar.header("📹 Video Source")
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st.sidebar.header("Video Source")
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video_source_type = st.sidebar.radio(
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"Select Input:",
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["Camera", "Upload Video File"],
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@ -496,7 +605,7 @@ video_source_type = st.sidebar.radio(
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)
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st.sidebar.divider()
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st.sidebar.header("📹 Camera Control")
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st.sidebar.header("Camera Control")
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camera_enabled = st.sidebar.toggle(
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"Camera ON/OFF",
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value=st.session_state.get('camera_enabled', True),
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@ -510,7 +619,7 @@ else:
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st.session_state.camera_enabled = camera_enabled
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if not camera_enabled:
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st.sidebar.warning("⚠️ Camera is OFF - No video feed")
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st.sidebar.warning("Camera is OFF - No video feed")
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if st.session_state.video_thread and st.session_state.video_thread.is_alive():
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st.session_state.video_thread = None
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@ -538,7 +647,7 @@ if video_source_type == "Upload Video File":
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st.session_state.current_video_file = uploaded_file.name
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st.session_state.video_file_path = str(video_file_path)
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needs_restart = True
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st.sidebar.success(f"✅ Video loaded: {uploaded_file.name}")
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st.sidebar.success(f"Video loaded: {uploaded_file.name}")
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else:
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if st.session_state.get('current_video_file') is not None:
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st.session_state.current_video_file = None
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@ -566,45 +675,69 @@ if st.session_state.camera_enabled:
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col1, col2 = st.columns([2, 1])
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with col1:
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st.subheader("📹 Live Video Feed")
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st.subheader("Live Video Feed")
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video_placeholder = st.empty()
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if not st.session_state.camera_enabled:
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video_placeholder.warning("📹 Camera is OFF - Enable camera to start video feed")
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video_placeholder.warning("Camera is OFF - Enable camera to start video feed")
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else:
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try:
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frame = frame_queue.get_nowait()
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video_placeholder.image(frame, channels='RGB', width='stretch')
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video_placeholder.image(frame, channels='RGB', use_container_width=True)
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except queue.Empty:
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video_placeholder.info("🔄 Waiting for camera feed...")
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video_placeholder.info("Waiting for camera feed...")
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with col2:
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st.subheader("⚠️ Active Alerts")
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st.subheader("Active Alerts")
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alert_container = st.container()
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with alert_container:
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for alert, active in predictor.alert_states.items():
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status = "🔴 ACTIVE" if active else "🟢 Normal"
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st.markdown(f"**{alert}**: {status}")
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if active:
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st.markdown(
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f'<div class="alert-active">'
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f'<strong>{alert}</strong>'
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f'<span class="status-badge status-active">ACTIVE</span>'
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f'</div>',
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unsafe_allow_html=True
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)
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else:
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st.markdown(
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f'<div class="alert-normal">'
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f'<strong>{alert}</strong>'
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f'<span class="status-badge status-normal">Normal</span>'
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f'</div>',
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unsafe_allow_html=True
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)
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st.divider()
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st.subheader("📊 Statistics")
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st.subheader("Statistics")
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if predictor.stats['frames_processed'] > 0:
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avg_fps = 1.0 / (predictor.stats['total_inference_time'] / predictor.stats['frames_processed'])
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st.metric("FPS", f"{avg_fps:.1f}")
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st.metric("Frames Processed", predictor.stats['frames_processed'])
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col_fps, col_frames = st.columns(2)
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with col_fps:
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st.metric("FPS", f"{avg_fps:.1f}", delta=f"{avg_fps-15:.1f}" if avg_fps > 15 else None)
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with col_frames:
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st.metric("Frames", predictor.stats['frames_processed'])
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st.metric("Alerts Triggered", predictor.stats['alerts_triggered'])
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else:
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st.info("Processing frames...")
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st.divider()
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st.subheader("📝 Recent Logs")
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st.subheader("Recent Logs")
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log_container = st.container()
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with log_container:
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if predictor.logs:
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for log in predictor.logs[-5:]:
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st.text(log)
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else:
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st.text("No logs yet...")
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# Footer
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st.divider()
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st.info("💡 **Features**: Drowsiness (PERCLOS) | Distraction (Head Pose) | Driver Absent | Phone Detection | Seatbelt Detection | **100% MediaPipe-Free!**")
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st.info("**Features**: Drowsiness (PERCLOS) | Distraction (Head Pose) | Driver Absent | Phone Detection | Seatbelt Detection | **100% MediaPipe-Free!**")
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# Auto-refresh
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time.sleep(0.033)
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@ -54,6 +54,7 @@ CONFIG = {
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'head_pose_threshold': 25, # Degrees for distraction
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'inference_skip': 2, # Process every 2nd frame for performance
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'frame_size': (640, 480), # Optimized for Pi
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'max_logs': 10, # Maximum number of log entries to keep
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}
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# COCO class IDs
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@ -183,6 +184,22 @@ class POCPredictor:
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'Phone Detected': False,
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'No Seatbelt': False,
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}
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# Track alert persistence for temporal smoothing
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self.alert_persistence = {
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'Drowsiness': 0,
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'Distraction': 0,
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'Driver Absent': 0,
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'Phone Detected': 0,
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'No Seatbelt': 0,
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}
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# Frames to persist alert after condition clears (for smooth transitions)
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self.alert_clear_frames = {
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'Drowsiness': 10, # Clear after 10 frames (~0.3s at 30fps)
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'Distraction': 8, # Clear after 8 frames
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'Driver Absent': 5, # Clear immediately
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'Phone Detected': 5, # Clear after 5 frames
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'No Seatbelt': 8, # Clear after 8 frames
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}
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self.stats = {
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'frames_processed': 0,
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'total_inference_time': 0,
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@ -191,13 +208,13 @@ class POCPredictor:
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self.logs = []
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def detect_objects(self, frame):
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"""YOLO object detection - optimized for POC."""
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# Resize to square for YOLO
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yolo_input = cv2.resize(frame, (640, 640))
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"""YOLO object detection - optimized for POC with performance improvements."""
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# Resize to square for YOLO (use INTER_LINEAR for speed)
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yolo_input = cv2.resize(frame, (640, 640), interpolation=cv2.INTER_LINEAR)
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# Convert HWC to CHW
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# Convert HWC to CHW (optimized)
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yolo_input = yolo_input.transpose(2, 0, 1)
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yolo_input = yolo_input[None].astype(np.float32) / 255.0
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yolo_input = np.ascontiguousarray(yolo_input[None].astype(np.float32) / 255.0)
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# Run inference
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input_name = self.yolo_session.get_inputs()[0].name
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@ -313,12 +330,22 @@ class POCPredictor:
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alerts['Phone Detected'] = np.any(detections['classes'] == 67) if len(detections['classes']) > 0 else False
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alerts['No Seatbelt'] = not seatbelt and belt_conf > 0.3
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# Update states
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# Update states with temporal smoothing (clear alerts when condition stops)
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for alert, triggered in alerts.items():
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if triggered:
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# Condition detected - set alert and reset persistence counter
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if not self.alert_states.get(alert, False):
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self.alert_states[alert] = True
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self.stats['alerts_triggered'] += 1
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self.alert_persistence[alert] = 0 # Reset counter
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else:
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# Condition not detected - increment persistence counter
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||||
if self.alert_states.get(alert, False):
|
||||
self.alert_persistence[alert] += 1
|
||||
# Clear alert if condition has been absent for enough frames
|
||||
if self.alert_persistence[alert] >= self.alert_clear_frames.get(alert, 5):
|
||||
self.alert_states[alert] = False
|
||||
self.alert_persistence[alert] = 0
|
||||
|
||||
# Draw on frame
|
||||
annotated_frame = self.draw_detections(frame, detections, face_data, alerts)
|
||||
@ -328,10 +355,13 @@ class POCPredictor:
|
||||
self.stats['frames_processed'] += 1
|
||||
self.stats['total_inference_time'] += inference_time
|
||||
|
||||
# Log
|
||||
# Log (keep only recent logs)
|
||||
log_entry = f"Frame {frame_idx} | PERCLOS: {face_data['perclos']:.2f} | Yaw: {face_data['head_yaw']:.1f}° | Alerts: {sum(alerts.values())}"
|
||||
logger.info(log_entry)
|
||||
self.logs.append(log_entry[-80:])
|
||||
# Keep only recent logs to avoid memory issues
|
||||
if len(self.logs) > CONFIG['max_logs']:
|
||||
self.logs = self.logs[-CONFIG['max_logs']:]
|
||||
|
||||
return alerts, annotated_frame, True, seatbelt, belt_conf, face_data
|
||||
|
||||
@ -464,14 +494,93 @@ def video_capture_loop(predictor, frame_queue, video_source=None):
|
||||
logger.info("Video capture loop ended")
|
||||
|
||||
|
||||
# Streamlit UI
|
||||
# Streamlit UI - World-Class Design for Raspberry Pi/Chromium
|
||||
st.set_page_config(
|
||||
page_title="DSMS POC Demo - Raspberry Pi",
|
||||
page_icon="🚗",
|
||||
layout="wide"
|
||||
layout="wide",
|
||||
initial_sidebar_state="expanded"
|
||||
)
|
||||
|
||||
st.title("🚗 Driver State Monitoring System - Raspberry Pi 5")
|
||||
# Custom CSS for better UI on Chromium
|
||||
st.markdown("""
|
||||
<style>
|
||||
/* Main container styling */
|
||||
.main .block-container {
|
||||
padding-top: 2rem;
|
||||
padding-bottom: 2rem;
|
||||
}
|
||||
|
||||
/* Alert status styling */
|
||||
.alert-active {
|
||||
background-color: #ffebee;
|
||||
border-left: 4px solid #f44336;
|
||||
padding: 0.5rem;
|
||||
margin: 0.25rem 0;
|
||||
border-radius: 4px;
|
||||
font-weight: 600;
|
||||
}
|
||||
|
||||
.alert-normal {
|
||||
background-color: #e8f5e9;
|
||||
border-left: 4px solid #4caf50;
|
||||
padding: 0.5rem;
|
||||
margin: 0.25rem 0;
|
||||
border-radius: 4px;
|
||||
font-weight: 500;
|
||||
}
|
||||
|
||||
/* Status indicators */
|
||||
.status-badge {
|
||||
display: inline-block;
|
||||
padding: 0.25rem 0.75rem;
|
||||
border-radius: 12px;
|
||||
font-size: 0.85rem;
|
||||
font-weight: 600;
|
||||
margin-left: 0.5rem;
|
||||
}
|
||||
|
||||
.status-active {
|
||||
background-color: #f44336;
|
||||
color: white;
|
||||
}
|
||||
|
||||
.status-normal {
|
||||
background-color: #4caf50;
|
||||
color: white;
|
||||
}
|
||||
|
||||
/* Statistics cards */
|
||||
.metric-card {
|
||||
background-color: #f5f5f5;
|
||||
padding: 1rem;
|
||||
border-radius: 8px;
|
||||
margin: 0.5rem 0;
|
||||
}
|
||||
|
||||
/* Video feed container */
|
||||
.video-container {
|
||||
border: 2px solid #e0e0e0;
|
||||
border-radius: 8px;
|
||||
padding: 0.5rem;
|
||||
background-color: #000;
|
||||
}
|
||||
|
||||
/* Header styling */
|
||||
h1 {
|
||||
color: #1976d2;
|
||||
border-bottom: 3px solid #1976d2;
|
||||
padding-bottom: 0.5rem;
|
||||
}
|
||||
|
||||
/* Sidebar styling */
|
||||
.css-1d391kg {
|
||||
background-color: #fafafa;
|
||||
}
|
||||
</style>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
st.title("Driver State Monitoring System - Raspberry Pi 5")
|
||||
st.markdown("**MediaPipe-Free | Optimized for Smooth Execution**")
|
||||
|
||||
# Initialize session state
|
||||
@ -487,7 +596,7 @@ predictor = st.session_state.predictor
|
||||
frame_queue = st.session_state.frame_queue
|
||||
|
||||
# Video source selection
|
||||
st.sidebar.header("📹 Video Source")
|
||||
st.sidebar.header("Video Source")
|
||||
video_source_type = st.sidebar.radio(
|
||||
"Select Input:",
|
||||
["Camera", "Upload Video File"],
|
||||
@ -496,7 +605,7 @@ video_source_type = st.sidebar.radio(
|
||||
)
|
||||
|
||||
st.sidebar.divider()
|
||||
st.sidebar.header("📹 Camera Control")
|
||||
st.sidebar.header("Camera Control")
|
||||
camera_enabled = st.sidebar.toggle(
|
||||
"Camera ON/OFF",
|
||||
value=st.session_state.get('camera_enabled', True),
|
||||
@ -510,7 +619,7 @@ else:
|
||||
st.session_state.camera_enabled = camera_enabled
|
||||
|
||||
if not camera_enabled:
|
||||
st.sidebar.warning("⚠️ Camera is OFF - No video feed")
|
||||
st.sidebar.warning("Camera is OFF - No video feed")
|
||||
if st.session_state.video_thread and st.session_state.video_thread.is_alive():
|
||||
st.session_state.video_thread = None
|
||||
|
||||
@ -538,7 +647,7 @@ if video_source_type == "Upload Video File":
|
||||
st.session_state.current_video_file = uploaded_file.name
|
||||
st.session_state.video_file_path = str(video_file_path)
|
||||
needs_restart = True
|
||||
st.sidebar.success(f"✅ Video loaded: {uploaded_file.name}")
|
||||
st.sidebar.success(f"Video loaded: {uploaded_file.name}")
|
||||
else:
|
||||
if st.session_state.get('current_video_file') is not None:
|
||||
st.session_state.current_video_file = None
|
||||
@ -566,45 +675,69 @@ if st.session_state.camera_enabled:
|
||||
col1, col2 = st.columns([2, 1])
|
||||
|
||||
with col1:
|
||||
st.subheader("📹 Live Video Feed")
|
||||
st.subheader("Live Video Feed")
|
||||
video_placeholder = st.empty()
|
||||
|
||||
if not st.session_state.camera_enabled:
|
||||
video_placeholder.warning("📹 Camera is OFF - Enable camera to start video feed")
|
||||
video_placeholder.warning("Camera is OFF - Enable camera to start video feed")
|
||||
else:
|
||||
try:
|
||||
frame = frame_queue.get_nowait()
|
||||
video_placeholder.image(frame, channels='RGB', width='stretch')
|
||||
video_placeholder.image(frame, channels='RGB', use_container_width=True)
|
||||
except queue.Empty:
|
||||
video_placeholder.info("🔄 Waiting for camera feed...")
|
||||
video_placeholder.info("Waiting for camera feed...")
|
||||
|
||||
with col2:
|
||||
st.subheader("⚠️ Active Alerts")
|
||||
st.subheader("Active Alerts")
|
||||
alert_container = st.container()
|
||||
|
||||
with alert_container:
|
||||
for alert, active in predictor.alert_states.items():
|
||||
status = "🔴 ACTIVE" if active else "🟢 Normal"
|
||||
st.markdown(f"**{alert}**: {status}")
|
||||
if active:
|
||||
st.markdown(
|
||||
f'<div class="alert-active">'
|
||||
f'<strong>{alert}</strong>'
|
||||
f'<span class="status-badge status-active">ACTIVE</span>'
|
||||
f'</div>',
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
else:
|
||||
st.markdown(
|
||||
f'<div class="alert-normal">'
|
||||
f'<strong>{alert}</strong>'
|
||||
f'<span class="status-badge status-normal">Normal</span>'
|
||||
f'</div>',
|
||||
unsafe_allow_html=True
|
||||
)
|
||||
|
||||
st.divider()
|
||||
|
||||
st.subheader("📊 Statistics")
|
||||
st.subheader("Statistics")
|
||||
if predictor.stats['frames_processed'] > 0:
|
||||
avg_fps = 1.0 / (predictor.stats['total_inference_time'] / predictor.stats['frames_processed'])
|
||||
st.metric("FPS", f"{avg_fps:.1f}")
|
||||
st.metric("Frames Processed", predictor.stats['frames_processed'])
|
||||
col_fps, col_frames = st.columns(2)
|
||||
with col_fps:
|
||||
st.metric("FPS", f"{avg_fps:.1f}", delta=f"{avg_fps-15:.1f}" if avg_fps > 15 else None)
|
||||
with col_frames:
|
||||
st.metric("Frames", predictor.stats['frames_processed'])
|
||||
st.metric("Alerts Triggered", predictor.stats['alerts_triggered'])
|
||||
else:
|
||||
st.info("Processing frames...")
|
||||
|
||||
st.divider()
|
||||
|
||||
st.subheader("📝 Recent Logs")
|
||||
st.subheader("Recent Logs")
|
||||
log_container = st.container()
|
||||
with log_container:
|
||||
if predictor.logs:
|
||||
for log in predictor.logs[-5:]:
|
||||
st.text(log)
|
||||
else:
|
||||
st.text("No logs yet...")
|
||||
|
||||
# Footer
|
||||
st.divider()
|
||||
st.info("💡 **Features**: Drowsiness (PERCLOS) | Distraction (Head Pose) | Driver Absent | Phone Detection | Seatbelt Detection | **100% MediaPipe-Free!**")
|
||||
st.info("**Features**: Drowsiness (PERCLOS) | Distraction (Head Pose) | Driver Absent | Phone Detection | Seatbelt Detection | **100% MediaPipe-Free!**")
|
||||
|
||||
# Auto-refresh
|
||||
time.sleep(0.033)
|
||||
|
||||
Loading…
Reference in New Issue
Block a user