双十二涉暴视频审核购买

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

# 加载预训练的模型
model = load_model('path_to_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 frames

def predict_video(frames):
    predictions = []
    for frame in frames:
        # 预处理帧数据
        processed_frame = preprocess_frame(frame)
        prediction = model.predict(processed_frame)
        predictions.append(prediction)
    return predictions

def preprocess_frame(frame):
    # 转换为灰度图并调整大小
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
    resized = cv2.resize(gray, (224, 224))
    normalized = resized / 255.0
    input_frame = np.expand_dims(normalized, axis=0)
    return input_frame

# 示例使用
video_path = 'path_to_video.mp4'
frames = preprocess_video(video_path)
predictions = predict_video(frames)

for pred in predictions:
    if pred[0][0] > 0.5:  # 假设阈值为0.5
        print("违规内容检测到")
    else:
        print("正常内容")