fix ‘安徽省’多个‘安’的识别和地址里以数字打头的问题

This commit is contained in:
weiweiw 2024-08-14 16:24:11 +08:00
parent 213bb69f73
commit 75f8a71768
5 changed files with 44 additions and 125 deletions

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@ -9,6 +9,7 @@ BASE64_DATA_INCOMPLETE = 20003
NO_TEXT_RECOGNIZED = 20004
OCR_RECOGNIZE_OTHER_EXCEPTION = 20005
RECOGNITION_INFO_PARSE_OTHER_EXCEPTION = 20006
NO_DEFINED_FUNCTION_ERROR = 20007
error_codes = {
@ -19,6 +20,7 @@ error_codes = {
NO_TEXT_RECOGNIZED: "识别本地图片路径存在,但没有识别出文字",
OCR_RECOGNIZE_OTHER_EXCEPTION: "OCR识别身份证其他异常",
RECOGNITION_INFO_PARSE_OTHER_EXCEPTION: "身份证信息解析其他异常",
NO_DEFINED_FUNCTION_ERROR:"没有实现的功能"
}
# 是否显示详细日志
log_verbose = True

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@ -98,6 +98,10 @@ class IdentityCardExtractor(Extractor):
else:
pattern = r"\d{18,}$" # 匹配1位以上的数字结尾
data["address"] = re.sub(pattern, "", data["address"])
if data["address"].startswith("安安徽省"):
data["address"] ="安徽省" + data["address"][len("安安徽省"):]
if re.match(r'^[\d_-]+', data["address"]):
data["address"] = re.sub(r'^[\d_-]+', '', data["address"])
# 提取身份证号码
id_number = re.search(r"([123456]\d{17}|[123456]\d{16}[Xx])", text, re.DOTALL)
if id_number:
@ -248,25 +252,19 @@ class IdentityCardExtractor(Extractor):
# 公民身份号码
# 513401197807087411
# """
text = """中华人民共和国
居民身份证
签发机关
木里县公安局
有效期限
2020.03.16-2025.03.16
蒋子古
民族彝
出生
2005年1月4日
住址
四川省木里藏族自治县耗
牛坪乡泥珠村5组29号
公民身份号码
513422200501044415
"""
# text = """中华人民共和国
# 居民身份证
# 签发机关东至县公安局
# 有效期限2021.07.02-2031.07.02
# 姓名程文友
# 性别男民族汉
# 出生2002年2月7日
# 住址安
# 安徽省东至县胜利镇湖滨
# 村张四组12号
# 公民身份号码
# 342921200202074436
# """
#
# text = """姓名苏龙格德·胡尔查巴特尔
# 性别男民族蒙古
@ -351,9 +349,6 @@ text = """中华人民共和国
# 村峡山口村民组156号
# 公民身份号码
# 43038119831124301X"""
# extractor = IdentityCardExtractor()
# jsonstring = extractor.extract_textbyPaddle(text)
# print(jsonstring)
@ -380,3 +375,22 @@ text = """中华人民共和国
# else:
# print("未找到性别信息")
# text = """姓名热西提·伊明
# 性别
# 民族维吾尔
# 出生
# 1971年6月6日
# 住址
# 19995-6
# 新疆新和县无鲁都斯巴格镇
# 它乾城社区6组19号
# 公民身份号码
# 652925197106062519
# 中华人民共和国
# 居民身份证
# 有效期限
# 2021.07.16-长期
# """
# extractor = IdentityCardExtractor()
# jsonstring = extractor.extract_textbyPaddle(text)
# print(jsonstring)

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@ -29,14 +29,13 @@ class OCRRecognition:
@staticmethod
def extractIdCardInfoByPath(filePath1: str = "", filePath2: str = "") -> str:
logger.info(f"ocr加载开始计时")
# logger.info(f"ocr加载开始计时")
start_time = time.time() # 记录结束时间
ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
text = ""
finalResult = {
"code": LOCAL_PATH_NOT_EXIST,
"msg": error_codes[LOCAL_PATH_NOT_EXIST],
}
try:
if len(filePath1) > 0:
@ -73,7 +72,7 @@ class OCRRecognition:
jsonString = json.dumps(tempdict, ensure_ascii=False)
end_time = time.time() # 记录结束时间
execution_time = end_time - start_time # 计算执行时间
logger.info(f"extractIdCardInfoByPath 耗时{execution_time}")
# logger.info(f"extractIdCardInfoByPath 耗时{execution_time}秒")
return jsonString
else:
finalResult["code"] = NO_TEXT_RECOGNIZED
@ -87,7 +86,7 @@ class OCRRecognition:
"code": BASE64_DATA_INCOMPLETE,
"msg": error_codes[BASE64_DATA_INCOMPLETE],
}
logger.info(f"extractIdCardInfoByBase64Data")
# logger.info(f"extractIdCardInfoByBase64Data")
start_time = time.time() # 记录结束时间
jsonString = ""
try:
@ -118,5 +117,5 @@ class OCRRecognition:
end_time = time.time() # 记录结束时间
execution_time = end_time - start_time # 计算执行时间
logger.info(f"extractIdCardInfoByBase64Data 耗时{execution_time}")
# logger.info(f"extractIdCardInfoByBase64Data 耗时{execution_time}秒")
return jsonString

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@ -1,102 +1,8 @@
# -*- coding: utf-8 -*-
import sys
import io
import os
from paddleocr import PaddleOCR
import time
from configs.basic_config import logger
from extractor.identitycard_extractor import IdentityCardExtractor
import base64
import json
sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
def extractIdCardInfo(type:int, filePath1: str, filePath2: str)->str:
if (0 == type):
return extractIdCardInfoByPath(filePath1, filePath2)
elif (1 == type):
return extractIdCardInfoByBase64Data(filePath1,filePath2)
else:
pass
from util import ocr_recognition
def extractIdCardInfoByPath(filePath1: str, filePath2: str)->str:
ocr = PaddleOCR(use_angle_cls=True, lang="ch") # need to run only once to download and load model into memory
text = ""
start_time = time.time() # 记录结束时间
jsonString = ""
try:
if os.path.exists(filePath1):
result = ocr.ocr(filePath1, cls=False)
for idx in range(len(result)):
res = result[idx]
for line in res:
text += (line[1][0] + '\n')
if os.path.exists(filePath2):
result = ocr.ocr(filePath2, cls=False)
for idx in range(len(result)):
res = result[idx]
for line in res:
text += (line[1][0] + '\n')
except Exception as e:
logger.error(e)
print(e)
if 0 != len(text):
logger.info(f"text:{text}")
extractor = IdentityCardExtractor()
tempdict = extractor.extract_textbyPaddle(text)
jsonString = json.dumps(tempdict, ensure_ascii=False)
end_time = time.time() # 记录结束时间
execution_time = end_time - start_time # 计算执行时间
logger.info(f"extractIdCardInfoByBase64Data 耗时{execution_time}")
return jsonString
def extractIdCardInfoByBase64Data(base64data1:str, base64Data2: str)->str:
logger.info(f"extractIdCardInfoByBase64Data")
start_time = time.time() # 记录结束时间
jsonString = ""
try:
if 0!=len(base64data1):
logger.info(f"not base64data1.empty()")
image_data1 = base64.b64decode(base64data1)
with open("file1.png", "wb") as file:
file.write(image_data1)
if 0!=len(base64Data2):
logger.info(f"not base64Data2.empty()")
image_data2 = base64.b64decode(base64Data2)
with open("file2.png", "wb") as file:
file.write(image_data2)
if os.path.exists("file1.png") and os.path.exists("file2.png"):
logger.info(f"file1.png and file2.png exist")
jsonString = extractIdCardInfoByPath("file1.png","file2.png")
os.remove("file1.png")
os.remove("file2.png")
elif os.path.exists("file1.png"):
logger.info(f"file1.png exist")
jsonString = extractIdCardInfoByPath("file1.png","")
os.remove("file1.png")
elif os.path.exists("file2.png"):
logger.info(f"file2.png exist")
jsonString = extractIdCardInfoByPath("file2.png","")
os.remove("file2.png")
except Exception as e:
logger.error(e)
end_time = time.time() # 记录结束时间
execution_time = end_time - start_time # 计算执行时间
logger.info(f"extractIdCardInfoByBase64Data 耗时{execution_time}")
return jsonString
# with open('/Users/wangvivi/Desktop/Code/ocrtest/images/id_card.JPG', 'rb') as image_file:
# base64_image_string = base64.b64encode(image_file.read()).decode('utf-8')
#
# jsonString = extractIdCardInfoByBase64Data(base64_image_string,"")
# jsonString = extractIdCardInfoByBase64Data("/Users/wangvivi/Desktop/Code/ocrtest/images/2.jpg","/Users/wangvivi/Desktop/Code/ocrtest/images/1.jpg")
# print(jsonString)
# #
jsonString = extractIdCardInfoByPath("./images/han.jpg","")
jsonString = ocr_recognition.OCRRecognition.extractIdCardInfoByPath("./images/han.jpg","")
print(jsonString)
# jsonString = extractIdCardInfoByPath("/Users/wangvivi/Desktop/Code/ocrtest/images/2.jpg","/Users/wangvivi/Desktop/Code/ocrtest/images/1.jpg")
# print(jsonString)

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@ -1,7 +1,6 @@
from fastapi import FastAPI
from pydantic import BaseModel
from util import ocr_recognition
from configs.basic_config import *
app = FastAPI()
@ -12,7 +11,6 @@ class IdentifyRecognitionParams(BaseModel):
@app.post("/recognition")
async def recognition(params: IdentifyRecognitionParams):
# logger.info(f"python recognition里的参数{params.type}, {params.recognitionFrontData}, {params.recognitionBackData}")
returnStr = ocr_recognition.OCRRecognition.extractIdCardInfo(params.type, params.recognitionFrontData, params.recognitionBackData)
return returnStr