手写体文字识别促销活动

import tensorflow as tf
from tensorflow.keras.models import load_model
import numpy as np
from PIL import Image

# 加载预训练模型
model = load_model('handwriting_recognition_model.h5')

def preprocess_image(image_path):
    img = Image.open(image_path).convert('L')  # 转换为灰度图像
    img = img.resize((28, 28))  # 调整大小为28x28像素
    img_array = np.array(img) / 255.0  # 归一化处理
    img_array = np.expand_dims(img_array, axis=-1)  # 增加通道维度
    img_array = np.expand_dims(img_array, axis=0)  # 增加批次维度
    return img_array

def recognize_handwriting(image_path):
    processed_image = preprocess_image(image_path)
    prediction = model.predict(processed_image)
    predicted_label = np.argmax(prediction, axis=1)[0]
    return predicted_label

# 使用示例
result = recognize_handwriting('example_handwriting.png')
print(f"识别结果: {result}")