11.11图像识别购买

import tensorflow as tf
import numpy as np
from PIL import Image

# 加载预训练模型
model = tf.keras.applications.MobileNetV2(weights='imagenet')

# 加载并预处理图像
def load_image(image_path):
    img = Image.open(image_path).resize((224, 224))
    img_array = np.array(img) / 255.0
    img_array = np.expand_dims(img_array, axis=0)
    return img_array

# 进行预测
def predict_image(image_path):
    img_array = load_image(image_path)
    predictions = model.predict(img_array)
    decoded_predictions = tf.keras.applications.mobilenet_v2.decode_predictions(predictions, top=3)[0]
    return decoded_predictions

# 示例使用
image_path = 'path_to_your_image.jpg'
results = predict_image(image_path)
for result in results:
    print(f"Label: {result[1]}, Confidence: {result[2]*100:.2f}%")