涉暴视频审核如何搭建

import cv2
import tensorflow as tf

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

def detect_violence(video_path):
    cap = cv2.VideoCapture(video_path)
    while cap.isOpened():
        ret, frame = cap.read()
        if not ret:
            break
        # 预处理帧
        processed_frame = preprocess_frame(frame)
        # 进行预测
        prediction = model.predict(processed_frame)
        if prediction[0][0] > 0.5:  # 假设阈值为0.5
            print("Violent content detected!")
        else:
            print("Safe content.")
    cap.release()

def preprocess_frame(frame):
    # 转换为灰度图并进行缩放
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    resized = cv2.resize(gray, (224, 224))  # 假设模型输入尺寸为224x224
    normalized = resized / 255.0
    input_frame = tf.expand_dims(normalized, axis=0)
    return input_frame

# 测试视频路径
video_path = 'test_video.mp4'
detect_violence(video_path)