双12智能识图推荐

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

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

def predict_image(image_url):
    # 下载并预处理图片
    response = requests.get(image_url)
    img = Image.open(BytesIO(response.content))
    img = img.resize((224, 224))
    img_array = np.array(img)
    img_array = np.expand_dims(img_array, axis=0)
    img_array = preprocess_input(img_array)

    # 进行预测
    predictions = model.predict(img_array)
    decoded_predictions = decode_predictions(predictions, top=3)[0]
    
    return decoded_predictions

# 示例使用
image_url = 'https://example.com/image.jpg'
predictions = predict_image(image_url)
for pred in predictions:
    print(f"Label: {pred[1]}, Confidence: {pred[2]*100:.2f}%")