mirror of
https://github.com/PaddlePaddle/FastDeploy.git
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57 lines
1.9 KiB
C++
57 lines
1.9 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 faceid {
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class FASTDEPLOY_DECL InsightFaceRecognitionModel : public FastDeployModel {
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public:
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InsightFaceRecognitionModel(
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const std::string& model_file, const std::string& params_file = "",
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const RuntimeOption& custom_option = RuntimeOption(),
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const ModelFormat& model_format = ModelFormat::ONNX);
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virtual std::string ModelName() const { return "deepinsight/insightface"; }
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// tuple of (width, height), default (112, 112)
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std::vector<int> size;
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std::vector<float> alpha;
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std::vector<float> beta;
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// whether to swap the B and R channel, such as BGR->RGB, default true.
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bool swap_rb;
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// whether to apply l2 normalize to embedding values, default;
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bool l2_normalize;
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virtual bool Predict(cv::Mat* im, FaceRecognitionResult* result);
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virtual bool Initialize();
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virtual bool Preprocess(Mat* mat, FDTensor* output);
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virtual bool Postprocess(std::vector<FDTensor>& infer_result,
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FaceRecognitionResult* result);
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};
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} // namespace faceid
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} // namespace vision
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} // namespace fastdeploy
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