| import base64 |
| import requests |
| import numpy as np |
| import cv2 |
| from typing import Union, List, Tuple |
| from collections import OrderedDict |
|
|
| from utils.textblock import TextBlock |
| from utils.proj_imgtrans import ProjImgTrans |
|
|
| from utils.registry import Registry |
| TEXTDETECTORS = Registry('textdetectors') |
| register_textdetectors = TEXTDETECTORS.register_module |
|
|
| from ..base import BaseModule, DEFAULT_DEVICE, DEVICE_SELECTOR |
|
|
| class TextDetectorBase(BaseModule): |
|
|
| _postprocess_hooks = OrderedDict() |
| _preprocess_hooks = OrderedDict() |
|
|
| def __init__(self, **params) -> None: |
| super().__init__(**params) |
| self.name = '' |
| for key in TEXTDETECTORS.module_dict: |
| if TEXTDETECTORS.module_dict[key] == self.__class__: |
| self.name = key |
| break |
|
|
| def _detect(self, img: np.ndarray, proj: ProjImgTrans) -> Tuple[np.ndarray, List[TextBlock]]: |
| ''' |
| The proj context can be accessed via ```proj``` |
| ''' |
| raise NotImplementedError |
|
|
| def setup_detector(self): |
| raise NotImplementedError |
|
|
| def detect(self, img: np.ndarray, proj: ProjImgTrans = None) -> Tuple[np.ndarray, List[TextBlock]]: |
| |
| if not self.all_model_loaded(): |
| self.load_model() |
| mask, blk_list = self._detect(img, proj) |
| for blk in blk_list: |
| blk.det_model = self.name |
| return mask, blk_list |
|
|
