敏感视频审核双11活动

import cv2
import numpy as np
from tensorflow.keras.models import load_model

# 加载预训练的深度学习模型
model = load_model('sensitive_content_detection_model.h5')

def preprocess_video(video_path):
    cap = cv2.VideoCapture(video_path)
    frames = []
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        frames.append(frame)
    cap.release()
    return np.array(frames)

def detect_sensitive_content(video_frames):
    predictions = model.predict(video_frames)
    return any(prediction > 0.5 for prediction in predictions)  # 假设阈值为0.5

# 使用示例
video_path = 'example_video.mp4'
frames = preprocess_video(video_path)
is_sensitive = detect_sensitive_content(frames)

if is_sensitive:
    print("该视频包含敏感内容，需要进行处理。")
else:
    print("视频内容正常，可以通过审核。")