智能单据识别怎么创建

import tensorflow as tf
from tensorflow.keras import layers

# 假设你已经有了标注好的数据集
# 数据预处理和模型构建
model = tf.keras.Sequential([
    layers.Conv2D(32, (3, 3), activation='relu', input_shape=(128, 128, 3)),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3, 3), activation='relu'),
    layers.MaxPooling2D((2, 2)),
    layers.Conv2D(64, (3, 3), activation='relu'),
    layers.Flatten(),
    layers.Dense(64, activation='relu'),
    layers.Dense(10)  # 假设有10类单据
])

model.compile(optimizer='adam',
              loss=tf.keras.losses.SparseCategoricalCrossentropy(from_logits=True),
              metrics=['accuracy'])

# 训练模型
model.fit(train_images, train_labels, epochs=10)

import pytesseract
from PIL import Image

# 打开图像文件
image = Image.open('example.png')

# 使用Tesseract进行OCR识别
text = pytesseract.image_to_string(image)
print(text)

import re

# 假设识别出的文本包含发票信息
invoice_text = """
Invoice Number: INV12345
Date: 2023-04-15
Amount: $123.45
"""

# 使用正则表达式提取关键信息
invoice_number = re.search(r"Invoice Number: (\w+)", invoice_text).group(1)
date = re.search(r"Date: (\d{4}-\d{2}-\d{2})", invoice_text).group(1)
amount = re.search(r"Amount: \$(\d+\.\d+)", invoice_text).group(1)

print(f"Invoice Number: {invoice_number}")
print(f"Date: {date}")
print(f"Amount: ${amount}")