108 lines
4.3 KiB
C
108 lines
4.3 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 <stddef.h>
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#include <stdint.h>
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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 <openvino/op/region_yolo.hpp>
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#include <openvino/openvino.hpp>
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#include "models/detection_model.h"
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struct DetectedObject;
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struct InferenceResult;
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struct ResultBase;
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class ModelYolo : public DetectionModel {
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protected:
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class Region {
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public:
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int num = 0;
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size_t classes = 0;
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int coords = 0;
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std::vector<float> anchors;
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size_t outputWidth = 0;
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size_t outputHeight = 0;
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Region(const std::shared_ptr<ov::op::v0::RegionYolo>& regionYolo);
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Region(size_t classes,
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int coords,
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const std::vector<float>& anchors,
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const std::vector<int64_t>& masks,
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size_t outputWidth,
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size_t outputHeight);
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};
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public:
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enum YoloVersion { YOLO_V1V2, YOLO_V3, YOLO_V4, YOLO_V4_TINY, YOLOF };
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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 useAdvancedPostprocessing - if true, an advanced algorithm for filtering/postprocessing will be used
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/// (with better processing of multiple crossing objects). Otherwise, classic algorithm will be used.
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/// @param boxIOUThreshold - threshold to treat separate output regions as one object for filtering
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/// during postprocessing (only one of them should stay). The default value is 0.5
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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 anchors - vector of anchors coordinates. Required for YOLOv4, for other versions it may be omitted.
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/// @param masks - vector of masks values. Required for YOLOv4, for other versions it may be omitted.
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/// @param layout - model input layout
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ModelYolo(const std::string& modelFileName,
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float confidenceThreshold,
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bool useAutoResize,
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bool useAdvancedPostprocessing = true,
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float boxIOUThreshold = 0.5,
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const std::vector<std::string>& labels = std::vector<std::string>(),
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const std::vector<float>& anchors = std::vector<float>(),
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const std::vector<int64_t>& masks = std::vector<int64_t>(),
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const std::string& layout = "");
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std::unique_ptr<ResultBase> postprocess(InferenceResult& infResult) override;
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protected:
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void prepareInputsOutputs(std::shared_ptr<ov::Model>& model) override;
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void parseYOLOOutput(const std::string& output_name,
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const ov::Tensor& tensor,
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const unsigned long resized_im_h,
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const unsigned long resized_im_w,
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const unsigned long original_im_h,
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const unsigned long original_im_w,
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std::vector<DetectedObject>& objects);
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static int calculateEntryIndex(int entriesNum, int lcoords, size_t lclasses, int location, int entry);
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static double intersectionOverUnion(const DetectedObject& o1, const DetectedObject& o2);
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std::map<std::string, Region> regions;
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double boxIOUThreshold;
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bool useAdvancedPostprocessing;
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bool isObjConf = 1;
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YoloVersion yoloVersion;
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const std::vector<float> presetAnchors;
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const std::vector<int64_t> presetMasks;
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ov::Layout yoloRegionLayout = "NCHW";
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};
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