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//
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// Created by tunm on 2023/1/25.
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//
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#ifndef ZEPHYRLPR_HYPER_LPR_CONTEXT_H
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#define ZEPHYRLPR_HYPER_LPR_CONTEXT_H
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#include <iostream>
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#include <opencv2/opencv.hpp>
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#include "nn_implementation_module/all.h"
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#include "buffer_module/all.h"
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#include "hyper_lpr_common.h"
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namespace hyper {
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enum {
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hRetOk = InferenceHelper::kRetOk, ///< 成功
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hRetErr = InferenceHelper::kRetErr, ///< 失败
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};
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class HyperLPRContext {
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public:
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HyperLPRContext(const HyperLPRContext &) = delete;
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HyperLPRContext &operator=(const HyperLPRContext &) = delete;
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explicit HyperLPRContext();
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void operator()(CameraBuffer &buffer);
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/**
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* 手动初始化并实例化内部模型对象
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* @param models_folder_path 存放模型文件夹的路径地址
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* @param max_num 最大识别车牌数量
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* @param detect_level 检测器等级 low速度快，high速度慢检出率略高于low
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* @param threads 推理线程数量 (暂时无效)
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* @param use_half 是否开启半精度推理 (暂时无效)
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* @param box_conf_threshold 检测框置信度阈值
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* @param nms_threshold 非极大值抑制阈值
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* @param rec_confidence_threshold 车牌字符识别置信度阈值
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* @return 初始化状态
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*/
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int32_t Initialize(const std::string& models_folder_path, int max_num = 1, DetectLevel detect_level = DETECT_LEVEL_LOW, int threads = 1, bool use_half = false, float box_conf_threshold = 0.3f,
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float nms_threshold = 0.5f,
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float rec_confidence_threshold = 0.75f);
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PlateResultList &getMObjectResults();
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static PlateType PreGetPlateType(std::string& code);
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int32_t getMInitStatus() const;
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private:
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std::shared_ptr<DetArch> m_plate_detector_;
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std::shared_ptr<ClassificationEngine> m_plate_classification_;
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std::shared_ptr<RecognitionEngine> m_plate_recognition_;
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int m_pre_image_size_ = 320;
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PlateResultList m_object_results_;
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int m_rec_max_num_ = 1;
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int32_t m_init_status_ = hRetErr;
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};
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} // namespace
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#endif //ZEPHYRLPR_HYPER_LPR_CONTEXT_H
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