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ANSCORE/engines/OpenVINOEngine/include/models/detection_model_ssd.h

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