双11音视频内容结构化分析购买

import cv2
import tensorflow as tf

# 加载预训练的商品识别模型
model = tf.keras.models.load_model('path_to_model.h5')

# 打开视频文件
video_path = 'path_to_video.mp4'
cap = cv2.VideoCapture(video_path)

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        break
    
    # 预处理帧图像
    resized_frame = cv2.resize(frame, (224, 224))  # 调整大小以匹配模型输入
    normalized_frame = resized_frame / 255.0  # 归一化像素值
    input_frame = tf.expand_dims(normalized_frame, axis=0)  # 增加批次维度
    
    # 进行预测
    predictions = model.predict(input_frame)
    predicted_class = tf.argmax(predictions[0]).numpy()
    
    # 显示结果
    label = f'Class: {predicted_class}'
    cv2.putText(frame, label, (10, 30), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 255, 0), 2)
    cv2.imshow('Video Analysis', frame)
    
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()