视频智能拆条新年活动

import cv2
import tensorflow as tf

# 加载预训练模型
model = tf.keras.models.load_model('video_split_model.h5')

def detect_scenes(video_path):
    cap = cv2.VideoCapture(video_path)
    scenes = []
    prev_frame = None
    
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        
        if prev_frame is not None:
            # 将帧转换为模型输入格式
            input_frame = cv2.resize(frame, (224, 224))
            input_frame = tf.keras.applications.mobilenet_v2.preprocess_input(input_frame)
            input_frame = tf.expand_dims(input_frame, 0)
            
            # 预测场景变化
            prediction = model.predict(input_frame)
            if prediction[0][0] > 0.5:  # 假设阈值为0.5
                scenes.append(cap.get(cv2.CAP_PROP_POS_FRAMES))
        
        prev_frame = frame
    
    cap.release()
    return scenes

# 示例使用
video_path = 'path_to_your_video.mp4'
scenes = detect_scenes(video_path)
print("Detected scenes at frames:", scenes)