🎊 视频转场检测：帧差法与直方图方法应用

目录

帧差法可以判断转场

直方图方法：

帧差法可以判断转场

import cv2

# 读取视频文件

cap = cv2.VideoCapture('your_video_file.mp4')

# 读取第一帧

ret, frame1 = cap.read()

prev_gray = cv2.cvtColor(frame1, cv2.COLOR_BGR2GRAY)

while True:

# 读取下一帧

ret, frame2 = cap.read()

if not ret:

break

# 将当前帧转换为灰度图像

gray = cv2.cvtColor(frame2, cv2.COLOR_BGR2GRAY)

# 计算当前帧与上一帧的差异

frame_diff = cv2.absdiff(prev_gray, gray)

# 设定一个阈值来判断变化

threshold = 30

ret, thresh = cv2.threshold(frame_diff, threshold, 255, cv2.THRESH_BINARY)

# 展示结果

cv2.imshow('Frame Difference', thresh)

# 更新上一帧

prev_gray = gray

if cv2.waitKey(1) & 0xFF == ord('q'):

break

# 释放资源

cap.release()

cv2.destroyAllWindows()

直方图方法：

import cv2

import numpy as np

# 读取视频文件

cap = cv2.VideoCapture('your_video_file.mp4')

# 读取第一帧

ret, frame1 = cap.read()

prev_hist = cv2.calcHist([frame1], [0, 1, 2], None, [256, 256, 256], [0, 256, 0, 256, 0, 256])

while True:

# 读取下一帧

ret, frame2 = cap.read()

if not ret:

break

# 计算当前帧的直方图

current_hist = cv2.calcHist([frame2], [0, 1, 2], None, [256, 256, 256], [0, 256, 0, 256, 0, 256])

# 比较当前帧和上一帧的直方图差异

hist_diff = cv2.compareHist(prev_hist, current_hist, cv2.HISTCMP_CORREL) # 可以尝试不同的比较方法

# 设定阈值判断转场

threshold = 0.8 # 设置阈值，根据实际情况调整

if hist_diff < threshold:

print("转场可能发生！")

# 更新上一帧的直方图

prev_hist = current_hist

# 释放资源

cap.release()

cv2.destroyAllWindows()