双十一商品智能识别购买

import tensorflow as tf
from tensorflow.keras.applications.resnet50 import ResNet50, preprocess_input, decode_predictions
from PIL import Image
import numpy as np

# 加载预训练模型
model = ResNet50(weights='imagenet')

def recognize_image(image_path):
    img = Image.open(image_path)
    img = img.resize((224, 224))  # 调整图像大小以适应模型输入
    x = np.array(img)
    x = np.expand_dims(x, axis=0)
    x = preprocess_input(x)

    preds = model.predict(x)
    decoded_preds = decode_predictions(preds, top=3)[0]  # 获取前三个最可能的预测结果
    return decoded_preds

def recommend_products(image_path):
    recognized_items = recognize_image(image_path)
    # 这里可以加入更复杂的推荐逻辑，如根据识别结果查询数据库获取相似商品等
    recommended_products = [item[1] for item in recognized_items]  # 提取商品名称
    return recommended_products

# 示例调用
image_path = './excels/双十一商品图片.jpg'
print("识别的商品及相似推荐：", recommend_products(image_path))