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import cv2
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import numpy as np
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def extract_frames(video_path, resize=(640, 480)):
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cap = cv2.VideoCapture(video_path)
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frames = []
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while cap.isOpened():
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ret, frame = cap.read()
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if not ret:
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break
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if resize:
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frame = cv2.resize(frame, resize)
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frames.append(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY))
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cap.release()
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return frames
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def detect_camera_movement(frames, threshold=15):
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orb = cv2.ORB_create()
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movement_indices = []
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for i in range(len(frames) - 1):
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kp1, des1 = orb.detectAndCompute(frames[i], None)
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kp2, des2 = orb.detectAndCompute(frames[i+1], None)
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if des1 is None or des2 is None:
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continue
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bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
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matches = bf.match(des1, des2)
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if len(matches) < 10:
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continue
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src_pts = np.float32([kp1[m.queryIdx].pt for m in matches]).reshape(-1, 1, 2)
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dst_pts = np.float32([kp2[m.trainIdx].pt for m in matches]).reshape(-1, 1, 2)
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H, mask = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
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if H is not None:
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dx = H[0, 2]
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dy = H[1, 2]
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movement_magnitude = np.sqrt(dx**2 + dy**2)
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if movement_magnitude > threshold:
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movement_indices.append(i+1)
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return movement_indices
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