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- # copyright (c) 2024 PaddlePaddle Authors. All Rights Reserve.
- #
- # Licensed under the Apache License, Version 2.0 (the "License");
- # you may not use this file except in compliance with the License.
- # You may obtain a copy of the License at
- #
- # http://www.apache.org/licenses/LICENSE-2.0
- #
- # Unless required by applicable law or agreed to in writing, software
- # distributed under the License is distributed on an "AS IS" BASIS,
- # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- # See the License for the specific language governing permissions and
- # limitations under the License.
- from .base import BasePipeline
- from ..predictors import create_predictor
- from ..components import CropByPolys
- from ..results import OCRResult
- class OCRPipeline(BasePipeline):
- """OCR Pipeline"""
- entities = "ocr"
- def __init__(self, det_model, rec_model, det_batch_size, rec_batch_size, **kwargs):
- self._det_predict = create_predictor(det_model, batch_size=det_batch_size)
- self._rec_predict = create_predictor(rec_model, batch_size=rec_batch_size)
- # TODO: foo
- self._crop_by_polys = CropByPolys(det_box_type="foo")
- def predict(self, x):
- batch_ocr_res = []
- for batch_det_res in self._det_predict(x):
- for det_res in batch_det_res:
- single_img_res = det_res["result"]
- single_img_res["rec_text"] = []
- single_img_res["rec_score"] = []
- all_subs_of_img = list(self._crop_by_polys(single_img_res))
- for batch_rec_res in self._rec_predict(all_subs_of_img):
- for rec_res in batch_rec_res:
- single_img_res["rec_text"].append(rec_res["result"]["rec_text"])
- single_img_res["rec_score"].append(
- rec_res["result"]["rec_score"]
- )
- # TODO(gaotingquan): using "ocr_res" or new a component or dict only?
- batch_ocr_res.append({"ocr_res": OCRResult(single_img_res)})
- # batch_ocr_res.append(OCRResult(single_img_res))
- yield batch_ocr_res
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