{"id":1066006,"date":"2024-12-31T16:22:28","date_gmt":"2024-12-31T08:22:28","guid":{"rendered":"https:\/\/docs.pingcode.com\/ask\/ask-ask\/1066006.html"},"modified":"2024-12-31T16:22:31","modified_gmt":"2024-12-31T08:22:31","slug":"%e5%a6%82%e4%bd%95%e7%94%a8python%e6%8f%90%e5%8f%96%e8%ba%ab%e4%bb%bd%e8%af%81%e4%bf%a1%e6%81%af","status":"publish","type":"post","link":"https:\/\/docs.pingcode.com\/ask\/1066006.html","title":{"rendered":"\u5982\u4f55\u7528python\u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f"},"content":{"rendered":"

\"\u5982\u4f55\u7528python\u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f\"<\/p>\n

\u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f\u7684\u5173\u952e\u6b65\u9aa4\u6709\uff1a\u4f7f\u7528OCR\u6280\u672f\u8bc6\u522b\u8eab\u4efd\u8bc1\u56fe\u7247\u3001\u89e3\u6790\u8eab\u4efd\u8bc1\u53f7\u7801\u53ca\u5176\u4ed6\u4fe1\u606f\u3001\u8fdb\u884c\u6570\u636e\u6821\u9a8c\u548c\u5904\u7406\u3002<\/strong>\u5176\u4e2d\uff0c\u4f7f\u7528OCR\u6280\u672f\u8bc6\u522b\u8eab\u4efd\u8bc1\u56fe\u7247\u662f\u6700\u4e3a\u57fa\u7840\u548c\u5173\u952e\u7684\u4e00\u6b65\uff0c\u672c\u6587\u5c06\u8be6\u7ec6\u4ecb\u7ecd\u5982\u4f55\u4f7f\u7528Python\u6765\u5b9e\u73b0\u8fd9\u4e9b\u6b65\u9aa4\u3002<\/p>\n<\/p>\n

\u4e00\u3001OCR\u6280\u672f\u8bc6\u522b\u8eab\u4efd\u8bc1\u56fe\u7247<\/p>\n

\u4f7f\u7528OCR\uff08Optical Character Recognition\uff0c\u5149\u5b66\u5b57\u7b26\u8bc6\u522b\uff09\u6280\u672f\u53ef\u4ee5\u5c06\u8eab\u4efd\u8bc1\u56fe\u7247\u4e2d\u7684\u6587\u5b57\u4fe1\u606f\u8f6c\u6362\u4e3a\u53ef\u7f16\u8f91\u7684\u6587\u672c\u3002\u5728Python\u4e2d\uff0c\u53ef\u4ee5\u4f7f\u7528Tesseract OCR\u6765\u5b9e\u73b0\u8fd9\u4e00\u529f\u80fd\u3002Tesseract\u662f\u4e00\u4e2a\u5f00\u6e90\u7684OCR\u5f15\u64ce\uff0c\u652f\u6301\u591a\u79cd\u8bed\u8a00\u7684\u6587\u672c\u8bc6\u522b\u3002<\/p>\n<\/p>\n

\u9996\u5148\uff0c\u6211\u4eec\u9700\u8981\u5b89\u88c5Tesseract\u548c\u76f8\u5173\u7684Python\u5e93\uff1a<\/p>\n<\/p>\n

pip install pytesseract<\/p>\n
pip install pillow<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u7136\u540e\uff0c\u7f16\u5199\u4ee3\u7801\u6765\u8bfb\u53d6\u8eab\u4efd\u8bc1\u56fe\u7247\u5e76\u63d0\u53d6\u6587\u672c\u4fe1\u606f\uff1a<\/p>\n<\/p>\n
from PIL import Image<\/p>\n
import pytesseract<\/p>\n
\u8bbe\u7f6eTesseract\u7684\u8def\u5f84<\/strong><\/h2>\n
pytesseract.pytesseract.tesseract_cmd = r'C:\\Program Files\\Tesseract-OCR\\tesseract.exe'<\/p>\n
\u6253\u5f00\u8eab\u4efd\u8bc1\u56fe\u7247<\/strong><\/h2>\n
image = Image.open('path_to_id_card_image.jpg')<\/p>\n
\u4f7f\u7528Tesseract OCR\u63d0\u53d6\u6587\u672c<\/strong><\/h2>\n
text = pytesseract.image_to_string(image, lang='chi_sim')<\/p>\n
print(text)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e8c\u3001\u89e3\u6790\u8eab\u4efd\u8bc1\u53f7\u7801\u53ca\u5176\u4ed6\u4fe1\u606f<\/p>\n
\u63d0\u53d6\u5230\u8eab\u4efd\u8bc1\u7684\u6587\u672c\u4fe1\u606f\u540e\uff0c\u6211\u4eec\u9700\u8981\u4ece\u4e2d\u89e3\u6790\u51fa\u8eab\u4efd\u8bc1\u53f7\u7801\u53ca\u5176\u4ed6\u5173\u952e\u4fe1\u606f\uff08\u5982\u59d3\u540d\u3001\u6027\u522b\u3001\u51fa\u751f\u65e5\u671f\u7b49\uff09\u3002\u53ef\u4ee5\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u6765\u5339\u914d\u548c\u63d0\u53d6\u8fd9\u4e9b\u4fe1\u606f\u3002<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u7528\u4e8e\u4eceOCR\u63d0\u53d6\u7684\u6587\u672c\u4e2d\u89e3\u6790\u8eab\u4efd\u8bc1\u53f7\u7801\uff1a<\/p>\n<\/p>\n
import re<\/p>\n
\u5047\u8bbe\u4eceOCR\u63d0\u53d6\u7684\u6587\u672c<\/strong><\/h2>\n
text = """<\/p>\n
\u59d3\u540d\uff1a\u5f20\u4e09<\/p>\n
\u6027\u522b\uff1a\u7537<\/p>\n
\u6c11\u65cf\uff1a\u6c49<\/p>\n
\u51fa\u751f\uff1a1990\u5e7401\u670801\u65e5<\/p>\n
\u4f4f\u5740\uff1a\u5317\u4eac\u5e02\u4e1c\u57ce\u533a\u4e1c\u534e\u95e8\u5927\u8857<\/p>\n
\u516c\u6c11\u8eab\u4efd\u53f7\u7801\uff1a110101199001011234<\/p>\n
"""<\/p>\n
\u6b63\u5219\u8868\u8fbe\u5f0f\u5339\u914d\u8eab\u4efd\u8bc1\u53f7\u7801<\/strong><\/h2>\n
id_number_pattern = r'\\d{17}[\\dXx]'<\/p>\n
id_number = re.search(id_number_pattern, text).group()<\/p>\n
print("\u8eab\u4efd\u8bc1\u53f7\u7801:", id_number)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e09\u3001\u6570\u636e\u6821\u9a8c\u548c\u5904\u7406<\/p>\n
\u89e3\u6790\u51fa\u8eab\u4efd\u8bc1\u53f7\u7801\u540e\uff0c\u6211\u4eec\u53ef\u4ee5\u8fdb\u884c\u6821\u9a8c\uff0c\u786e\u4fdd\u6570\u636e\u7684\u6b63\u786e\u6027\u3002\u8eab\u4efd\u8bc1\u53f7\u7801\u753118\u4f4d\u6570\u5b57\u7ec4\u6210\uff0c\u5176\u4e2d\u524d17\u4f4d\u662f\u987a\u5e8f\u7801\uff0c\u7b2c18\u4f4d\u662f\u6821\u9a8c\u7801\u3002\u6821\u9a8c\u7801\u53ef\u4ee5\u901a\u8fc7\u524d17\u4f4d\u6570\u5b57\u8ba1\u7b97\u5f97\u51fa\u3002<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u6821\u9a8c\u8eab\u4efd\u8bc1\u53f7\u7801\u7684\u793a\u4f8b\u4ee3\u7801\uff1a<\/p>\n<\/p>\n
def validate_id_number(id_number):<\/p>\n
    # \u8eab\u4efd\u8bc1\u53f7\u7684\u6743\u91cd\u56e0\u5b50<\/p>\n
    weights = [7, 9, 10, 5, 8, 4, 2, 1, 6, 3, 7, 9, 10, 5, 8, 4, 2]<\/p>\n
    # \u8eab\u4efd\u8bc1\u53f7\u7684\u6821\u9a8c\u7801<\/p>\n
    check_digits = '10X98765432'<\/p>\n
    if len(id_number) != 18:<\/p>\n
        return False<\/p>\n
    # \u8ba1\u7b97\u6821\u9a8c\u7801<\/p>\n
    checksum = sum(int(id_number[i]) * weights[i] for i in range(17)) % 11<\/p>\n
    return check_digits[checksum] == id_number[-1]<\/p>\n
id_number = "110101199001011234"<\/p>\n
is_valid = validate_id_number(id_number)<\/p>\n
print("\u8eab\u4efd\u8bc1\u53f7\u7801\u6709\u6548:", is_valid)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u56db\u3001\u4f7f\u7528Python\u5e93\u8fdb\u4e00\u6b65\u5904\u7406\u548c\u5b58\u50a8\u4fe1\u606f<\/p>\n
\u5728\u63d0\u53d6\u548c\u9a8c\u8bc1\u8eab\u4efd\u8bc1\u4fe1\u606f\u540e\uff0c\u60a8\u53ef\u80fd\u5e0c\u671b\u8fdb\u4e00\u6b65\u5904\u7406\u548c\u5b58\u50a8\u8fd9\u4e9b\u4fe1\u606f\u3002\u53ef\u4ee5\u4f7f\u7528Python\u7684\u5404\u79cd\u5e93\u6765\u5b9e\u73b0\u8fd9\u4e00\u70b9\u3002\u4f8b\u5982\uff0c\u60a8\u53ef\u4ee5\u4f7f\u7528Pandas\u5e93\u5c06\u6570\u636e\u4fdd\u5b58\u5230Excel\u6216CSV\u6587\u4ef6\u4e2d\uff0c\u6216\u8005\u4f7f\u7528SQLite\u6570\u636e\u5e93\u8fdb\u884c\u5b58\u50a8\u3002<\/p>\n<\/p>\n
\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u4f7f\u7528Pandas\u5c06\u8eab\u4efd\u8bc1\u4fe1\u606f\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
import pandas as pd<\/p>\n
\u521b\u5efa\u8eab\u4efd\u8bc1\u4fe1\u606f\u7684\u5b57\u5178<\/strong><\/h2>\n
id_info = {<\/p>\n
    "\u59d3\u540d": ["\u5f20\u4e09"],<\/p>\n
    "\u6027\u522b": ["\u7537"],<\/p>\n
    "\u6c11\u65cf": ["\u6c49"],<\/p>\n
    "\u51fa\u751f\u65e5\u671f": ["1990\u5e7401\u670801\u65e5"],<\/p>\n
    "\u4f4f\u5740": ["\u5317\u4eac\u5e02\u4e1c\u57ce\u533a\u4e1c\u534e\u95e8\u5927\u8857"],<\/p>\n
    "\u8eab\u4efd\u8bc1\u53f7\u7801": ["110101199001011234"]<\/p>\n
}<\/p>\n
\u5c06\u5b57\u5178\u8f6c\u6362\u4e3aDataFrame<\/strong><\/h2>\n
df = pd.DataFrame(id_info)<\/p>\n
\u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
df.to_csv('id_info.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u4e94\u3001\u5904\u7406\u5927\u6279\u91cf\u7684\u8eab\u4efd\u8bc1\u56fe\u7247<\/p>\n
\u5982\u679c\u9700\u8981\u5904\u7406\u5927\u6279\u91cf\u7684\u8eab\u4efd\u8bc1\u56fe\u7247\uff0c\u53ef\u4ee5\u7f16\u5199\u4e00\u4e2a\u6279\u5904\u7406\u811a\u672c\u6765\u81ea\u52a8\u5316\u6574\u4e2a\u8fc7\u7a0b\u3002\u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u6279\u91cf\u5904\u7406\u591a\u4e2a\u8eab\u4efd\u8bc1\u56fe\u7247\uff0c\u5e76\u5c06\u63d0\u53d6\u7684\u4fe1\u606f\u4fdd\u5b58\u5230CSV\u6587\u4ef6\u4e2d\uff1a<\/p>\n<\/p>\n
import os<\/p>\n
from PIL import Image<\/p>\n
\u5b58\u50a8\u8eab\u4efd\u8bc1\u4fe1\u606f\u7684\u5217\u8868<\/strong><\/h2>\n
id_info_list = []<\/p>\n
\u904d\u5386\u8eab\u4efd\u8bc1\u56fe\u7247\u76ee\u5f55<\/strong><\/h2>\n
for filename in os.listdir('path_to_id_card_images'):<\/p>\n
    if filename.endswith('.jpg') or filename.endswith('.png'):<\/p>\n
        image_path = os.path.join('path_to_id_card_images', filename)<\/p>\n
        image = Image.open(image_path)<\/p>\n
        text = pytesseract.image_to_string(image, lang='chi_sim')<\/p>\n
        # \u89e3\u6790\u8eab\u4efd\u8bc1\u4fe1\u606f<\/p>\n
        id_number = re.search(id_number_pattern, text).group()<\/p>\n
        name = re.search(r'\u59d3\u540d\uff1a(\\S+)', text).group(1)<\/p>\n
        gender = re.search(r'\u6027\u522b\uff1a(\\S+)', text).group(1)<\/p>\n
        birth_date = re.search(r'\u51fa\u751f\uff1a(\\d{4}\u5e74\\d{2}\u6708\\d{2}\u65e5)', text).group(1)<\/p>\n
        address = re.search(r'\u4f4f\u5740\uff1a(\\S+)', text).group(1)<\/p>\n
        # \u6dfb\u52a0\u5230\u8eab\u4efd\u8bc1\u4fe1\u606f\u5217\u8868<\/p>\n
        id_info_list.append({<\/p>\n
            "\u59d3\u540d": name,<\/p>\n
            "\u6027\u522b": gender,<\/p>\n
            "\u51fa\u751f\u65e5\u671f": birth_date,<\/p>\n
            "\u4f4f\u5740": address,<\/p>\n
            "\u8eab\u4efd\u8bc1\u53f7\u7801": id_number<\/p>\n
        })<\/p>\n
\u5c06\u8eab\u4efd\u8bc1\u4fe1\u606f\u5217\u8868\u8f6c\u6362\u4e3aDataFrame<\/strong><\/h2>\n
df = pd.DataFrame(id_info_list)<\/p>\n
\u4fdd\u5b58\u5230CSV\u6587\u4ef6<\/strong><\/h2>\n
df.to_csv('batch_id_info.csv', index=False)<\/p>\n
<\/code><\/pre>\n<\/p>\n
\u516d\u3001\u63d0\u9ad8OCR\u8bc6\u522b\u51c6\u786e\u6027<\/p>\n
\u5728\u5b9e\u9645\u5e94\u7528\u4e2d\uff0cOCR\u8bc6\u522b\u53ef\u80fd\u4f1a\u53d7\u5230\u56fe\u7247\u8d28\u91cf\u3001\u6587\u5b57\u5b57\u4f53\u7b49\u56e0\u7d20\u7684\u5f71\u54cd\uff0c\u5bfc\u81f4\u8bc6\u522b\u7ed3\u679c\u4e0d\u51c6\u786e\u3002\u4e3a\u4e86\u63d0\u9ad8OCR\u8bc6\u522b\u7684\u51c6\u786e\u6027\uff0c\u53ef\u4ee5\u91c7\u53d6\u4ee5\u4e0b\u63aa\u65bd\uff1a<\/p>\n<\/p>\n
    \n
  1. \u9884\u5904\u7406\u56fe\u50cf<\/strong>\uff1a\u5728\u8fdb\u884cOCR\u8bc6\u522b\u4e4b\u524d\uff0c\u5bf9\u56fe\u50cf\u8fdb\u884c\u9884\u5904\u7406\uff0c\u5982\u7070\u5ea6\u5316\u3001\u4e8c\u503c\u5316\u3001\u53bb\u566a\u7b49\uff0c\u53ef\u4ee5\u63d0\u9ad8\u8bc6\u522b\u51c6\u786e\u6027\u3002<\/li>\n
  2. \u4f7f\u7528\u9ad8\u8d28\u91cf\u7684\u56fe\u50cf<\/strong>\uff1a\u4f7f\u7528\u9ad8\u5206\u8fa8\u7387\u7684\u8eab\u4efd\u8bc1\u626b\u63cf\u56fe\u50cf\uff0c\u907f\u514d\u6a21\u7cca\u3001\u5931\u7126\u7b49\u95ee\u9898\u3002<\/li>\n
  3. \u9009\u62e9\u5408\u9002\u7684OCR\u5f15\u64ce<\/strong>\uff1a\u6839\u636e\u5177\u4f53\u60c5\u51b5\u9009\u62e9\u9002\u5408\u7684OCR\u5f15\u64ce\uff0c\u5982Tesseract\u3001EasyOCR\u7b49\uff0c\u4e0d\u540c\u5f15\u64ce\u5728\u4e0d\u540c\u5e94\u7528\u573a\u666f\u4e0b\u8868\u73b0\u4e0d\u540c\u3002<\/li>\n
  4. \u8bad\u7ec3\u81ea\u5b9a\u4e49OCR\u6a21\u578b<\/strong>\uff1a\u5982\u679c\u6709\u5927\u91cf\u7684\u8eab\u4efd\u8bc1\u56fe\u50cf\u6570\u636e\uff0c\u53ef\u4ee5\u8003\u8651\u8bad\u7ec3\u81ea\u5b9a\u4e49\u7684OCR\u6a21\u578b\uff0c\u4ee5\u63d0\u9ad8\u7279\u5b9a\u573a\u666f\u4e0b\u7684\u8bc6\u522b\u51c6\u786e\u6027\u3002<\/li>\n<\/ol>\n
    \u4ee5\u4e0b\u662f\u4e00\u4e2a\u793a\u4f8b\u4ee3\u7801\uff0c\u5c55\u793a\u5982\u4f55\u5bf9\u56fe\u50cf\u8fdb\u884c\u9884\u5904\u7406\u5e76\u4f7f\u7528Tesseract\u8fdb\u884cOCR\u8bc6\u522b\uff1a<\/p>\n<\/p>\n
    import cv2<\/p>\n
    import numpy as np<\/p>\n
    \u8bfb\u53d6\u8eab\u4efd\u8bc1\u56fe\u7247<\/strong><\/h2>\n
    image = cv2.imread('path_to_id_card_image.jpg')<\/p>\n
    \u8f6c\u6362\u4e3a\u7070\u5ea6\u56fe\u50cf<\/strong><\/h2>\n
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)<\/p>\n
    \u4e8c\u503c\u5316\u5904\u7406<\/strong><\/h2>\n
    _, binary = cv2.threshold(gray, 128, 255, cv2.THRESH_BINARY)<\/p>\n
    \u53bb\u566a\u5904\u7406<\/strong><\/h2>\n
    denoised = cv2.fastNlMeansDenoising(binary, h=30)<\/p>\n
    \u4fdd\u5b58\u9884\u5904\u7406\u540e\u7684\u56fe\u50cf<\/strong><\/h2>\n
    cv2.imwrite('preprocessed_image.jpg', denoised)<\/p>\n
    \u4f7f\u7528Tesseract OCR\u63d0\u53d6\u6587\u672c<\/strong><\/h2>\n
    text = pytesseract.image_to_string(denoised, lang='chi_sim')<\/p>\n
    print(text)<\/p>\n
    <\/code><\/pre>\n<\/p>\n
    \u901a\u8fc7\u4ee5\u4e0a\u6b65\u9aa4\uff0c\u53ef\u4ee5\u4f7f\u7528Python\u5b9e\u73b0\u8eab\u4efd\u8bc1\u4fe1\u606f\u7684\u63d0\u53d6\u3001\u89e3\u6790\u3001\u6821\u9a8c\u548c\u5b58\u50a8\u3002\u672c\u6587\u4ecb\u7ecd\u4e86\u4eceOCR\u8bc6\u522b\u5230\u6570\u636e\u5904\u7406\u7684\u5b8c\u6574\u6d41\u7a0b\uff0c\u5e76\u63d0\u4f9b\u4e86\u793a\u4f8b\u4ee3\u7801\u4ee5\u4f9b\u53c2\u8003\u3002\u5e0c\u671b\u8fd9\u4e9b\u5185\u5bb9\u5bf9\u60a8\u6709\u6240\u5e2e\u52a9\u3002\u5982\u679c\u6709\u4efb\u4f55\u95ee\u9898\u6216\u9700\u8981\u8fdb\u4e00\u6b65\u7684\u5e2e\u52a9\uff0c\u8bf7\u968f\u65f6\u8054\u7cfb\u3002<\/p>\n<\/p>\n
    \u76f8\u5173\u95ee\u7b54FAQs\uff1a<\/strong><\/h2>\n
     \u5982\u4f55\u4f7f\u7528Python\u4ece\u8eab\u4efd\u8bc1\u56fe\u50cf\u4e2d\u63d0\u53d6\u4fe1\u606f\uff1f<\/strong>
    \u8981\u4ece\u8eab\u4efd\u8bc1\u56fe\u50cf\u4e2d\u63d0\u53d6\u4fe1\u606f\uff0c\u53ef\u4ee5\u4f7f\u7528OCR\uff08\u5149\u5b66\u5b57\u7b26\u8bc6\u522b\uff09\u6280\u672f\u3002\u5e38\u7528\u7684Python\u5e93\u5305\u62ecPytesseract\u548cOpenCV\u3002\u60a8\u53ef\u4ee5\u5148\u5c06\u8eab\u4efd\u8bc1\u56fe\u50cf\u9884\u5904\u7406\uff0c\u4f8b\u5982\u8c03\u6574\u56fe\u50cf\u5927\u5c0f\u548c\u5bf9\u6bd4\u5ea6\uff0c\u7136\u540e\u4f7f\u7528Pytesseract\u63d0\u53d6\u6587\u672c\u3002\u786e\u4fdd\u5b89\u88c5\u597dTesseract OCR\u5f15\u64ce\uff0c\u5e76\u5728\u4ee3\u7801\u4e2d\u8bbe\u7f6e\u6b63\u786e\u7684\u8def\u5f84\u3002<\/p>\n
    \u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f\u9700\u8981\u54ea\u4e9bPython\u5e93\uff1f<\/strong>
    \u901a\u5e38\uff0c\u60a8\u9700\u8981\u4f7f\u7528Pytesseract\u8fdb\u884cOCR\u8bc6\u522b\uff0c\u540c\u65f6\u7ed3\u5408OpenCV\u8fdb\u884c\u56fe\u50cf\u5904\u7406\u3002\u6b64\u5916\uff0cPillow\u4e5f\u662f\u4e00\u4e2a\u6709\u7528\u7684\u5e93\uff0c\u53ef\u7528\u4e8e\u56fe\u50cf\u6253\u5f00\u548c\u64cd\u4f5c\u3002\u786e\u4fdd\u5728\u60a8\u7684Python\u73af\u5883\u4e2d\u5b89\u88c5\u8fd9\u4e9b\u5e93\uff0c\u53ef\u4ee5\u4f7f\u7528pip\u547d\u4ee4\u6765\u5b8c\u6210\u5b89\u88c5\u3002<\/p>\n
    \u5982\u4f55\u5904\u7406\u63d0\u53d6\u8fc7\u7a0b\u4e2d\u9047\u5230\u7684\u8bc6\u522b\u9519\u8bef\uff1f<\/strong>
    \u5728\u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f\u65f6\uff0c\u8bc6\u522b\u9519\u8bef\u662f\u5e38\u89c1\u95ee\u9898\u3002\u53ef\u4ee5\u5c1d\u8bd5\u591a\u79cd\u65b9\u6cd5\u6765\u63d0\u9ad8\u51c6\u786e\u6027\uff0c\u4f8b\u5982\u5bf9\u56fe\u50cf\u8fdb\u884c\u53bb\u566a\u3001\u4e8c\u503c\u5316\u6216\u8c03\u6574\u4eae\u5ea6\u548c\u5bf9\u6bd4\u5ea6\u3002\u6b64\u5916\uff0c\u60a8\u8fd8\u53ef\u4ee5\u4f7f\u7528\u6b63\u5219\u8868\u8fbe\u5f0f\u6765\u9a8c\u8bc1\u63d0\u53d6\u7ed3\u679c\u7684\u683c\u5f0f\uff0c\u4ee5\u786e\u4fdd\u4fe1\u606f\u7684\u51c6\u786e\u6027\u548c\u5b8c\u6574\u6027\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"\u63d0\u53d6\u8eab\u4efd\u8bc1\u4fe1\u606f\u7684\u5173\u952e\u6b65\u9aa4\u6709\uff1a\u4f7f\u7528OCR\u6280\u672f\u8bc6\u522b\u8eab\u4efd\u8bc1\u56fe\u7247\u3001\u89e3\u6790\u8eab\u4efd\u8bc1\u53f7\u7801\u53ca\u5176\u4ed6\u4fe1\u606f\u3001\u8fdb\u884c\u6570\u636e\u6821\u9a8c\u548c\u5904\u7406\u3002\u5176\u4e2d\uff0c […]","protected":false},"author":3,"featured_media":1066016,"comment_status":"closed","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[37],"tags":[],"acf":[],"_links":{"self":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1066006"}],"collection":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/comments?post=1066006"}],"version-history":[{"count":"1","href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1066006\/revisions"}],"predecessor-version":[{"id":1066020,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/posts\/1066006\/revisions\/1066020"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media\/1066016"}],"wp:attachment":[{"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/media?parent=1066006"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/categories?post=1066006"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/docs.pingcode.com\/wp-json\/wp\/v2\/tags?post=1066006"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}