- Implemented live overlays to indicate alerting groups and their details.
- Updated person box annotations to reflect alert status with color coding.
- Improved saving of annotated alerts by including group-specific information and unique filenames.
- Added visual indicators for alert groups, including group size and duration.
- Added debug print statements for camera IP configuration at load time.
- Modified CAMERA_IPS initialization to correctly reference environment variables.
- Adjusted YOLO_CONF value for improved detection sensitivity.
- Refactored alert logic to accumulate pending alerts before saving, allowing for better management of alert metadata and image saving.
- Implemented saving of annotated alerts with unique filenames to prevent collisions.
- Introduced comprehensive documentation outlining the features, project structure, requirements, setup instructions, and environment variables for the surveillance dashboard application.
- Included details on person detection, group gathering alerts, and GPU requirements for optimal performance.
- Refactored camera handling to support multiple cameras via environment variables.
- Added API endpoints for camera selection and retrieval of available cameras.
- Updated stream processing to dynamically switch between selected cameras.
- Integrated device selection for YOLO inference to utilize CUDA if available.
- Introduced a dropdown for selecting cameras in the dashboard.
- Implemented functions to load available cameras and handle camera selection.
- Updated polling logic to reflect the currently selected camera.
- Enhanced styling for the camera selection dropdown.
- Created a new dashboard.html file for the surveillance dashboard interface.
- Implemented responsive layout with CSS grid for KPI display and video panel.
- Added styling for header, sidebar, alert banner, and various UI components.
- Included responsive design adjustments for mobile view.
- Implemented a new camera_stream.py file for real-time video processing.
- Integrated YOLO model for detecting people in the video stream.
- Added functionality for grouping detected individuals based on proximity.
- Implemented alert system for detecting groups over a specified duration.
- Included state management for stream status and alerts.
- Utilized Flask for serving video stream and alert information.
- Configured environment variables for RTSP stream access.
bahawal.baloch