12.12内容识别购买

import cv2
import tensorflow as tf

# 加载预训练的模型
model = tf.keras.models.load_model('path_to_model.h5')

def recognize_product(image_path):
    # 读取图像
    image = cv2.imread(image_path)
    image = cv2.resize(image, (224, 224))  # 调整图像大小以适应模型输入
    image = image / 255.0  # 归一化处理
    image = tf.expand_dims(image, 0)  # 增加批次维度

    # 进行预测
    predictions = model.predict(image)
    predicted_class = tf.argmax(predictions, axis=1).numpy()[0]

    # 根据预测结果返回商品信息
    product_info = get_product_info(predicted_class)
    return product_info

def get_product_info(class_id):
    # 这里可以根据class_id查询数据库或调用API获取商品信息
    product_info = {
        'id': class_id,
        'name': 'Sample Product',
        'price': 19.99,
        'url': 'https://example.com/product/123'
    }
    return product_info

# 示例调用
image_path = 'path_to_image.jpg'
product_info = recognize_product(image_path)
print(product_info)