74 lines
2.8 KiB
C++
74 lines
2.8 KiB
C++
/*
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// Copyright (C) 2020-2024 Intel Corporation
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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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*/
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#pragma once
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#include <stddef.h>
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#include <memory>
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#include <string>
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#include <vector>
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#include "models/detection_model.h"
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namespace ov {
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class InferRequest;
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class Model;
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} // namespace ov
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struct InferenceResult;
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struct InputData;
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struct InternalModelData;
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struct ResultBase;
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class ModelSSD : public DetectionModel {
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public:
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ModelSSD();
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/// Constructor
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/// @param modelFileName name of model to load
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/// @param confidenceThreshold - threshold to eliminate low-confidence detections.
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/// Any detected object with confidence lower than this threshold will be ignored.
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/// @param useAutoResize - if true, image will be resized by openvino.
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/// Otherwise, image will be preprocessed and resized using OpenCV routines.
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/// @param labels - array of labels for every class. If this array is empty or contains less elements
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/// than actual classes number, default "Label #N" will be shown for missing items.
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/// @param layout - model input layout
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ModelSSD(const std::string& modelFileName,
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float confidenceThreshold,
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bool useAutoResize,
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const std::vector<std::string>& labels = std::vector<std::string>(),
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const std::string& layout = "");
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void Initialise(const std::string& modelFileName,
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float _confidenceThreshold,
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bool useAutoResize,
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const std::vector<std::string>& _labels = std::vector<std::string>(),
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const std::string& layout = "")
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{
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ImageModel::Initalise(modelFileName, useAutoResize, layout),
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confidenceThreshold = confidenceThreshold;
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labels = _labels;
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}
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std::shared_ptr<InternalModelData> preprocess(const InputData& inputData, ov::InferRequest& request) override;
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std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
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protected:
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std::unique_ptr<ResultBase> postprocessSingleOutput(InferenceResult& infResult);
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std::unique_ptr<ResultBase> postprocessMultipleOutputs(InferenceResult& infResult);
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void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;
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void prepareSingleOutput(std::shared_ptr<ov::Model>& model);
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void prepareMultipleOutputs(std::shared_ptr<ov::Model>& model);
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size_t objectSize = 0;
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size_t detectionsNumId = 0;
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};
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