mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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52 lines
1.7 KiB
C++
52 lines
1.7 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/fastdeploy_model.h"
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#include "fastdeploy/vision/common/processors/transform.h"
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#include "fastdeploy/vision/common/result.h"
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namespace fastdeploy {
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namespace vision {
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namespace ppcls {
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class FASTDEPLOY_DECL Model : public FastDeployModel {
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public:
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Model(const std::string& model_file, const std::string& params_file,
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const std::string& config_file,
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const RuntimeOption& custom_option = RuntimeOption(),
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const Frontend& model_format = Frontend::PADDLE);
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std::string ModelName() const { return "ppclas-classify"; }
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// TODO(jiangjiajun) Batch is on the way
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virtual bool Predict(cv::Mat* im, ClassifyResult* result, int topk = 1);
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private:
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bool Initialize();
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bool BuildPreprocessPipelineFromConfig();
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bool Preprocess(Mat* mat, FDTensor* outputs);
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bool Postprocess(const FDTensor& infer_result, ClassifyResult* result,
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int topk = 1);
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std::vector<std::shared_ptr<Processor>> processors_;
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std::string config_file_;
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};
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} // namespace ppcls
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} // namespace vision
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} // namespace fastdeploy
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