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* add style transfer model * add examples for generation model * add unit test * add speed comparison * add speed comparison * add variable for constant * add preprocessor and postprocessor * add preprocessor and postprocessor * fix * fix according to review Co-authored-by: DefTruth <31974251+DefTruth@users.noreply.github.com>
43 lines
1.5 KiB
C++
43 lines
1.5 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include "fastdeploy/vision/common/processors/transform.h"
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#include "fastdeploy/function/functions.h"
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namespace fastdeploy {
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namespace vision {
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namespace generation {
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/*! @brief Preprocessor object for AnimeGAN serials model.
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*/
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class FASTDEPLOY_DECL AnimeGANPreprocessor {
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public:
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/** \brief Create a preprocessor instance for AnimeGAN serials model
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*/
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AnimeGANPreprocessor() {}
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/** \brief Process the input image and prepare input tensors for runtime
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*
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* \param[in] images The input image data list, all the elements are returned wrapped by FDMat.
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* \param[in] output The output tensors which will feed in runtime
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* \return true if the preprocess successed, otherwise false
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*/
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bool Run(std::vector<Mat>& images, std::vector<FDTensor>* output);
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};
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} // namespace generation
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} // namespace vision
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} // namespace fastdeploy
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