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