A Python-based segmental motion detection system that uses OpenCV to identify and highlight movement within a video feed. The program divides the video frame into segments and detects movement based on statistical changes in pixel values.
- Segmental Analysis: The video frame is divided into segments for detailed motion analysis.
- Motion Detection: Detects and highlights movement in the video feed based on changes in pixel values.
- Configurable Settings: Adjust the number of segments, detection threshold, and recording delay time using trackbars.
- Recording Status: Displays 'RECORDING' or 'IDLE' status based on detected movement.
__init__(self, segments=20, threshold=10, delay_seconds=3)
: Initializes the class with the number of segments, threshold, and delay time.segment_calculation(self, frame)
: Calculates the average and standard deviation of pixel values in each segment.detect_movement(self, previous_stats, current_stats)
: Compares the average and standard deviation of pixel values in each segment to detect movement.run(self)
: Runs the motion detection demonstration.update_threshold(self, threshold_value)
: Updates the threshold value.update_segments(self, segments_value)
: Updates the number of segments.update_delay(self, delay_value)
: Updates the delay time.
- Initializes and runs the
SegmentalMotionDetection
demonstration.
This project is licensed under the MIT License.
James Bebarski