在tf.keras中使用预训练模型进行预测

import tensorflow as tf
from tensorflow.keras.applications import 模型名称
from tensorflow.keras.preprocessing import image
from tensorflow.keras.applications.模型名称 import preprocess_input, decode_predictions

model = 模型名称(weights='imagenet')

img_path = '图片路径'
img = image.load_img(img_path, target_size=(输入尺寸))
x = image.img_to_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]
for class_id, class_name, probability in decoded_preds:
    print(f'{class_name}: {probability * 100}%')