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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.
- import numpy as np
- from ..base import BaseComponent
- class DocTrPostProcess(BaseComponent):
- """normalize image such as substract mean, divide std"""
- INPUT_KEYS = ["pred"]
- OUTPUT_KEYS = ["doctr_img"]
- DEAULT_INPUTS = {"pred": "pred"}
- DEAULT_OUTPUTS = {"doctr_img": "doctr_img"}
- def __init__(self, scale=None, **kwargs):
- super().__init__()
- if isinstance(scale, str):
- scale = np.float32(scale)
- self.scale = np.float32(scale if scale is not None else 255.0)
- def apply(self, pred):
- im = pred[0]
- assert isinstance(im, np.ndarray), "invalid input 'im' in DocTrPostProcess"
- im = im.squeeze()
- im = im.transpose(1, 2, 0)
- im *= self.scale
- im = im[:, :, ::-1]
- im = im.astype("uint8", copy=False)
- result = {"doctr_img": im}
- return result
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