123 lines
3.5 KiB
C
123 lines
3.5 KiB
C
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/*
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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 <map>
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#include <memory>
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#include <string>
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#include <vector>
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#include <opencv2/core.hpp>
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#include <openvino/openvino.hpp>
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#include "internal_model_data.h"
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struct MetaData;
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struct ResultBase {
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ResultBase(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: frameId(frameId),
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metaData(metaData) {}
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virtual ~ResultBase() {}
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int64_t frameId;
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std::shared_ptr<MetaData> metaData;
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bool IsEmpty() {
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return frameId < 0;
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}
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template <class T>
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T& asRef() {
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return dynamic_cast<T&>(*this);
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}
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template <class T>
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const T& asRef() const {
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return dynamic_cast<const T&>(*this);
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}
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};
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struct InferenceResult : public ResultBase {
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std::shared_ptr<InternalModelData> internalModelData;
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std::map<std::string, ov::Tensor> outputsData;
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/// Returns the first output tensor
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/// This function is a useful addition to direct access to outputs list as many models have only one output
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/// @returns first output tensor
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ov::Tensor getFirstOutputTensor() {
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if (outputsData.empty()) {
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throw std::out_of_range("Outputs map is empty.");
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}
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return outputsData.begin()->second;
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}
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/// Returns true if object contains no valid data
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/// @returns true if object contains no valid data
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bool IsEmpty() {
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return outputsData.empty();
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}
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};
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struct ClassificationResult : public ResultBase {
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ClassificationResult(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: ResultBase(frameId, metaData) {}
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struct Classification {
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unsigned int id;
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std::string label;
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float score;
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Classification(unsigned int id, const std::string& label, float score) : id(id), label(label), score(score) {}
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};
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std::vector<Classification> topLabels;
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};
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struct DetectedObject : public cv::Rect2f {
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size_t labelID;
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std::string label;
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float confidence;
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};
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struct DetectionResult : public ResultBase {
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DetectionResult(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: ResultBase(frameId, metaData) {}
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std::vector<DetectedObject> objects;
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};
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struct RetinaFaceDetectionResult : public DetectionResult {
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RetinaFaceDetectionResult(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: DetectionResult(frameId, metaData) {}
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std::vector<cv::Point2f> landmarks;
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};
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struct ImageResult : public ResultBase {
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ImageResult(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: ResultBase(frameId, metaData) {}
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cv::Mat resultImage;
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};
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struct HumanPose {
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std::vector<cv::Point2f> keypoints;
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float score;
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};
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struct HumanPoseResult : public ResultBase {
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HumanPoseResult(int64_t frameId = -1, const std::shared_ptr<MetaData>& metaData = nullptr)
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: ResultBase(frameId, metaData) {}
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std::vector<HumanPose> poses;
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};
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