table_recognition.py 3.2 KB

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  1. # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
  2. #
  3. # Licensed under the Apache License, Version 2.0 (the "License");
  4. # you may not use this file except in compliance with the License.
  5. # You may obtain a copy of the License at
  6. #
  7. # http://www.apache.org/licenses/LICENSE-2.0
  8. #
  9. # Unless required by applicable law or agreed to in writing, software
  10. # distributed under the License is distributed on an "AS IS" BASIS,
  11. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  12. # See the License for the specific language governing permissions and
  13. # limitations under the License.
  14. import numpy as np
  15. from ...utils.func_register import FuncRegister
  16. from ...modules.table_recognition.model_list import MODELS
  17. from ..components import *
  18. from ..results import TableRecResult
  19. from .base import BasicPredictor
  20. from ..utils.process_hook import batchable_method
  21. class TablePredictor(BasicPredictor):
  22. """table recognition predictor"""
  23. entities = MODELS
  24. _FUNC_MAP = {}
  25. register = FuncRegister(_FUNC_MAP)
  26. def _build_components(self):
  27. ops = {}
  28. for cfg in self.config["PreProcess"]["transform_ops"]:
  29. tf_key = list(cfg.keys())[0]
  30. func = self._FUNC_MAP.get(tf_key)
  31. args = cfg.get(tf_key, {})
  32. op = func(self, **args) if args else func(self)
  33. if op:
  34. ops[tf_key] = op
  35. predictor = ImagePredictor(
  36. model_dir=self.model_dir,
  37. model_prefix=self.MODEL_FILE_PREFIX,
  38. option=self.pp_option,
  39. )
  40. ops["predictor"] = predictor
  41. key, op = self.build_postprocess(**self.config["PostProcess"])
  42. ops[key] = op
  43. return ops
  44. def build_postprocess(self, **kwargs):
  45. if kwargs.get("name") == "TableLabelDecode":
  46. return "TableLabelDecode", TableLabelDecode(
  47. merge_no_span_structure=kwargs.get("merge_no_span_structure"),
  48. dict_character=kwargs.get("character_dict"),
  49. )
  50. else:
  51. raise Exception()
  52. @register("DecodeImage")
  53. def build_readimg(self, *args, **kwargs):
  54. return ReadImage(batch_size=self.kwargs.get("batch_size", 1))
  55. @register("TableLabelEncode")
  56. def foo(self, *args, **kwargs):
  57. return None
  58. @register("TableBoxEncode")
  59. def foo(self, *args, **kwargs):
  60. return None
  61. @register("ResizeTableImage")
  62. def build_resize_table(self, max_len=488):
  63. return ResizeByLong(target_long_edge=max_len)
  64. @register("NormalizeImage")
  65. def build_normalize(
  66. self,
  67. mean=[0.485, 0.456, 0.406],
  68. std=[0.229, 0.224, 0.225],
  69. scale=1 / 255,
  70. order="hwc",
  71. ):
  72. return Normalize(mean=mean, std=std)
  73. @register("PaddingTableImage")
  74. def build_padding(self, size=[488, 448], pad_value=0):
  75. return Pad(target_size=size[0], val=pad_value)
  76. @register("ToCHWImage")
  77. def build_to_chw(self):
  78. return ToCHWImage()
  79. @register("KeepKeys")
  80. def foo(self, *args, **kwargs):
  81. return None
  82. def _pack_res(self, single):
  83. keys = ["img_path", "bbox", "structure"]
  84. return TableRecResult({key: single[key] for key in keys})