hr-ocr-cet/core/ocr.py

import time
from dataclasses import dataclass
from typing import Any

from core.line_parser import LineParser
from core.parser import *
from core.direction import *
import numpy as np
from paddleocr import PaddleOCR

# <- 传入pic pic_type
# 1. 旋转pic  (to 正向)
# 2. 重写识别pic  (get res)
# 3. 行处理res  (get res)
# 4. 对res字段逻辑识别  (get dict)
# -> dict
# 身份证OCR
@dataclass
class CetOcr:
    ocr: PaddleOCR
    # 角度探测器
    angle_detector: AngleDetector

    # 检测
    # <- 传入pic pic_type
    # -> dict
    def predict(self, image: np.ndarray) -> ():

        # 旋转后img angle result(生ocr)
        image, angle, result, image_type = self._pre_process(image)
        print(f'---------- detect angle: {angle} 角度 --------')
        if angle != 0:
            _, _, result = self._ocr(image)

        return self._post_process(result, angle, image_type)

    # 预处理(旋转图片)
    # <- img(cv2) img_type
    # -> 正向的img(旋转后) 源img角度 result(ocr生)
    def _pre_process(self, image) -> (np.ndarray, int, Any):
        # pic角度 result(ocr生)
        angle, result, image_type = self.angle_detector.detect_angle(image)

        if angle == 1:
            image = cv2.rotate(image, cv2.ROTATE_90_COUNTERCLOCKWISE)
        if angle == 2:
            image = cv2.rotate(image, cv2.ROTATE_180)
        if angle == 3:
            image = cv2.rotate(image, cv2.ROTATE_90_CLOCKWISE)
        return image, angle, result, image_type

    # 获取模型检测结果
    def _ocr(self, image):
        result = self.ocr.ocr(image, cls=True)
        # print("------------------")
        # print(result)
        if not result:
            raise Exception('无法识别')
        confs = [line[1][1] for line in result]

        # 将检测到的文字放到一个列表中
        txts = [line[1][0] for line in result]
        # print("......................................")
        # print(txts)
        # print("......................................")
        return txts, confs, result

    # <- result(正向img_生ocr) angle img_type
    # == 对 正向img_res 进行[行处理]
    # -> 最后要返回的结果 dict
    def _post_process(self, result, angle: int, image_type):
        filters = [lambda x: x.is_slope, lambda x: x.txt.replace(' ', '').encode('utf-8').isalpha()]
        line_parser = LineParser(result, filters)
        line_result = line_parser.parse()
        print('-------------')
        print(line_result)
        print('-------------')
        conf = line_parser.confidence

        if int(image_type) == 0:
            parser = CETParser(line_result)
        elif int(image_type) == 1:
            parser = TEMParser(line_result)
        else:
            raise Exception('无法识别')

        # 字段逻辑处理后对res(dict)
        ocr_res = parser.parse()

        res = {
            "confidence": conf,
            "orientation": angle,  # 原angle是逆时针，转成顺时针
            **ocr_res
        }
        print(res)
        return res

    # def _get_type(self, image) -> int: