视频智能分类特惠活动

import cv2
import tensorflow as tf

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

def classify_video(video_path):
    cap = cv2.VideoCapture(video_path)
    frames = []
    
    while True:
        ret, frame = cap.read()
        if not ret:
            break
        frames.append(frame)
    
    cap.release()
    
    # 对每一帧进行预测
    predictions = []
    for frame in frames:
        processed_frame = preprocess_frame(frame)  # 预处理帧数据
        prediction = model.predict(processed_frame)
        predictions.append(prediction)
    
    # 综合预测结果
    final_prediction = aggregate_predictions(predictions)
    return final_prediction

def preprocess_frame(frame):
    # 这里可以添加具体的预处理步骤，如缩放、归一化等
    return frame

def aggregate_predictions(predictions):
    # 这里可以添加具体的预测结果综合逻辑
    return max(set(predictions), key=predictions.count)

# 使用示例
result = classify_video('example_video.mp4')
print("视频分类结果:", result)