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85d519e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | # SPDX-License-Identifier: MIT
# Copyright (C) Intel Corporation
#
# Motion Detection: OpenCV sample.
# See README.md for prerequisites and inputs. Run: python3 opencv_sample.py
import cv2
import numpy as np
INPUT_VIDEO = "test_video.mp4"
MIN_AREA = 500 # ignore motion blobs smaller than this many pixels
cap = cv2.VideoCapture(INPUT_VIDEO)
fps = cap.get(cv2.CAP_PROP_FPS) or 30.0
width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH))
height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))
bg = cv2.createBackgroundSubtractorMOG2(
history=200, varThreshold=25, detectShadows=True)
writer = cv2.VideoWriter(
"output_opencv.mp4", cv2.VideoWriter_fourcc(*"mp4v"), fps, (width, height))
kernel = np.ones((3, 3), np.uint8)
frame_idx = 0
motion_frames = 0
while True:
ok, frame = cap.read()
if not ok:
break
frame_idx += 1
fg = bg.apply(frame)
# MOG2 marks shadows as 127; keep only strong foreground (255).
fg = cv2.threshold(fg, 200, 255, cv2.THRESH_BINARY)[1]
fg = cv2.morphologyEx(fg, cv2.MORPH_OPEN, kernel)
contours, _ = cv2.findContours(
fg, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
regions = [c for c in contours if cv2.contourArea(c) >= MIN_AREA]
if regions:
motion_frames += 1
for c in regions:
x, y, w, h = cv2.boundingRect(c)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 0, 255), 2)
status_text = "Motion Detected" if regions else "No Motion"
status_color = (0, 0, 255) if regions else (0, 255, 0)
cv2.putText(frame, status_text, (10, 30),
cv2.FONT_HERSHEY_SIMPLEX, 0.9, status_color, 2)
cv2.putText(frame, f"Motion regions: {len(regions)}", (10, 60),
cv2.FONT_HERSHEY_SIMPLEX, 0.8, (0, 0, 255), 2)
print(f"Frame {frame_idx}: motion regions={len(regions)}", flush=True)
writer.write(frame)
cap.release()
writer.release()
print(f"Motion detected in {motion_frames} frames", flush=True)
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