商品智能识别双十一活动

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

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

def preprocess_image(image):
    # 图像预处理：缩放、灰度化、归一化等
    image = cv2.resize(image, (224, 224))
    image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    image = image / 255.0
    return np.expand_dims(image, axis=-1)

def recognize_product(image_path):
    # 读取图像文件
    image = cv2.imread(image_path)
    if image is None:
        return "Error: Unable to load image."
    
    # 预处理图像
    processed_image = preprocess_image(image)
    
    # 使用模型进行预测
    predictions = model.predict(np.expand_dims(processed_image, axis=0))
    predicted_class = np.argmax(predictions[0])
    
    # 返回识别结果
    return f"Recognized Product: {predicted_class}"

# 示例调用
result = recognize_product('sample_product.jpg')
print(result)