Initial setup for CLion
This commit is contained in:
439
ANSLIB/ANSLIB.h
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439
ANSLIB/ANSLIB.h
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#ifndef ANSLIB_H
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#define ANSLIB_H
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#define ANSLIB_API __declspec(dllexport)
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#define CUSTOM_API __declspec(dllexport)
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#pragma once
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#include <windows.h>
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#include <opencv2/opencv.hpp>
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#include <opencv2/core/cuda.hpp>
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enum DetectionType {
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CLASSIFICATION = 0,
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DETECTION = 1,
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SEGMENTATION = 2,
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FACEDETECTOR = 3,
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FACERECOGNIZER = 4,
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LICENSEPLATE = 5,
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TEXTSCENSE = 6,
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KEYPOINT = 7,
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OBB = 8 // Oriented Bounding Box
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};
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enum ModelType {
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TENSORFLOW = 0,
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YOLOV4 = 1,
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YOLOV5 = 2,
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YOLOV8 = 3,
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TENSORRT = 4,
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OPENVINO = 5,
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FACEDETECT = 6,
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FACERECOGNIZE = 7,
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ALPR = 8,
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OCR = 9,
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ANOMALIB = 10,
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POSE = 11,
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SAM = 12,
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ODHUBMODEL = 13,
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YOLOV10RTOD = 14, // TensorRT Object Detection for Yolov10
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YOLOV10OVOD = 15, // OpenVINO Object Detection for Yolov10
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CUSTOMDETECTOR = 16, // Custom Detector
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YOLOV12 = 17, // YoloV12 standard for yolov12
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CUSTOMPY = 18, // Custom Python script model
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MOTIONDETECTOR = 19, // Motion Detector,
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ONNXCL = 20,
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ONNXPOSE = 21,
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RTPOSE = 22,
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ONNXSEG = 23,
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RTSEG = 24,
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ONNXOBB = 25,
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RTOBB = 26,
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MOVIENET = 27,
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ONNXSAM3 = 28,
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RTSAM3 = 29,
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ONNXYOLO = 30,
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RTYOLO = 31
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};
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enum TrackerType {
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BYTETRACK = 0,
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UCMC = 1,
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OCSORT = 2
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};
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namespace ANSCENTER {
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struct Point {
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int x, y;
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};
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struct ROIConfig {
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bool Rectangle;
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bool Polygon;
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bool Line;
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int MinItems;
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int MaxItems;
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std::string Name;
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std::string ROIMatch;
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};
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struct Parameter {
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std::string Name;
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std::string DataType;
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int NoOfDecimals;
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int MaxValue;
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int MinValue;
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std::string StartValue;
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std::vector<std::string> ListItems;
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std::string DefaultValue;
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std::string Value;
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};
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struct ROIValue {
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std::string ROIMatch;
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std::vector<Point> ROIPoints;
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std::string Option;
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std::string Name;
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int OriginalImageSize;
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};
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struct Params {
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std::vector<ROIConfig> ROI_Config;
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std::vector<std::string> ROI_Options;
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std::vector<Parameter> Parameters;
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std::vector<ROIValue> ROI_Values;
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};
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/* Example
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{
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"ROI_Config":[
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{
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"Rectangle":true,
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"Polygon":true,
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"Line":false,
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"MinItems":0,
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"MaxItems":3,
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"Name":"Traffic Light",
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"ROI-Match":"All Corners"
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},
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{
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"Rectangle":true,
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"Polygon":false,
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"Line":false,
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"MinItems":1,
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"MaxItems":1,
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"Name":"Car Zone",
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"ROI-Match":"All Corners"
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},
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{
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"Rectangle":false,
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"Polygon":false,
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"Line":true,
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"MinItems":1,
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"MaxItems":2,
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"Name":"Cross Line",
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"ROI-Match":"All Corners"
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}
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],
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"ROI_Options":[
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"Inside ROI",
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"Inside ROI",
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"Both Directions"
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],
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"Parameters":[
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{
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"Name":"Para1",
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"DataType":"Boolean",
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"NoOfdecimals":0,
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"MaxValue":0,
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"MinValue":0,
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"StartValue":"",
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"ListItems":[],
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"DefaultValue":"",
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"Value":"true"
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},
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{
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"Name":"Para2",
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"DataType":"Integer",
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"NoOfdecimals":0,
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"MaxValue":5,
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"MinValue":1,
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"StartValue":"2",
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"ListItems":[],
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"DefaultValue":"",
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"Value":"3"
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},
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{
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"Name":"Para3",
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"DataType":"List-Single",
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"NoOfdecimals":0,
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"MaxValue":0,
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"MinValue":0,
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"StartValue":"",
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"ListItems":["A","B","C"],
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"DefaultValue":"",
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"Value":"A"
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},
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{
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"Name":"Para4",
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"DataType":"Range",
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"NoOfdecimals":0,
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"MaxValue":100,
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"MinValue":50,
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"StartValue":">,60",
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"ListItems":[">","<"],
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"DefaultValue":"",
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"Value":">,52.000000"
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}
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],
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"ROI_Values":[
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[
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{"x":269,"y":134},
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{"x":777,"y":134},
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{"x":777,"y":457},
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{"x":269,"y":457}
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],
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"Option":"Inside ROI",
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"Name":"Car Zone 1",
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"OriginalImageSize":1920
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},
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[{"x":280,"y":613},{"x":1108,"y":280}],
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"Option":"Above",
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"Name":"Cross Line 1",
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"OriginalImageSize":1920
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},
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[{"x":1511,"y":383},{"x":1283,"y":754}],
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"Option":"Left side",
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"Name":"Cross Line 2",
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"OriginalImageSize":1920
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},
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[
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{"x":229,"y":161},
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{"x":964,"y":161},
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{"x":964,"y":628},
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{"x":229,"y":628}
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],
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"Option":"Left side",
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"Name":"Traffic Light 1",
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"OriginalImageSize":1920
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},
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[
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{"x":1115,"y":304},
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{"x":1730,"y":304},
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{"x":1730,"y":695},
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{"x":1115,"y":695}
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],
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"Option":"Left side",
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"Name":"Traffic Light 2",
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"OriginalImageSize":1920
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},
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{
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"ROI-Match":"Centre Point",
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"ROIPoints":[
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{"x":678,"y":683},
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{"x":1217,"y":683},
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{"x":1217,"y":1026},
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{"x":678,"y":1026}
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],
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"Option":"Left side",
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"Name":"Traffic Light 3",
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"OriginalImageSize":1920
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}
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]
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}
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*/
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struct Object
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{
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int classId{ 0 };
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int trackId{ 0 };
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std::string className{};
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float confidence{ 0.0 };
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cv::Rect box{};
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std::vector<cv::Point2f> polygon; // Polygon that contain x1,y1,x2,y2,x3,y3,x4,y4
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cv::Mat mask{}; // Face image in box (cropped) or mask image for segmentation
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cv::cuda::GpuMat gpuMask{}; // GPU-resident face crop (set by NV12 affine warp, avoids re-upload)
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std::vector<float> kps{}; // Pose exsimate 17 keypoints or oriented bouding box (xcenter, ycenter, width, height, angle)
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std::string extraInfo; // More information such as facial recognition
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std::string cameraId; // Use to check if this object belongs to any camera
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//std::string attributes; // Attributes such as keypoint string
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};
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class ANSLIB_API ANSLIB {
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public:
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ANSLIB();
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~ANSLIB() noexcept;
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[[nodiscard]] static ANSLIB* Create();
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static void Destroy(ANSLIB* instance);
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[[nodiscard]] int Initialize(const char* licenseKey,
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const char* modelFilePath,
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const char* modelFileZipPassword,
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float modelThreshold,
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float modelConfThreshold,
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float modelNMSThreshold,
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int modelType,
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int detectionType, int loadEngineOnCreation,std::string &labels);
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[[nodiscard]] int RunInference(cv::Mat cvImage, const char* cameraId, std::vector<ANSCENTER::Object>& detectionResult);
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[[nodiscard]] int RunInferenceWithOptions(cv::Mat cvImage, const char* cameraId, const char* activeROIMode, std::vector<ANSCENTER::Object>& detectionResult);
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[[nodiscard]] int OptimizeModel(const char* modelFilePath, const char* modelFileZipPassword, int modelType, int modelDetectionType,int fp16);
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[[nodiscard]] int Optimize(bool fp16); // Perform optimization on the loaded model on current model folder
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[[nodiscard]] int GetEngineType();
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[[nodiscard]] int LoadModelFromFolder(const char* licenseKey, const char* modelName, const char* className,
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float detectionScoreThreshold, float modelConfThreshold, float modelMNSThreshold,
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int autoDetectEngine, int modelType, int detectionType, int loadEngineOnCreation, const char* modelFolder, std::string& labelMap);
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[[nodiscard]] int DetectMovement(cv::Mat image, const char* cameraId, std::vector<Object>& results);
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[[nodiscard]] cv::Rect GetActiveWindow(cv::Mat cvImage);
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[[nodiscard]] int SetPrompt(const char* text);
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[[nodiscard]] int SetTracker(int trackerType, int enableTracker);
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[[nodiscard]] int SetTrackerParameters(const char* trackerParams);
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private:
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HMODULE dllHandle = nullptr;
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bool loaded = false;
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void* ANSHandle = nullptr;
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const char* CreateANSODHandle_CS(void** Handle,
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const char* licenseKey,
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const char* modelFilePath,
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const char* modelFileZipPassword,
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float modelThreshold,
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float modelConfThreshold,
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float modelNMSThreshold,
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int autoDetectEngine,
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int modelType,
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int detectionType,
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int loadEngineOnCreation);
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int RunInference_CPP(void** Handle, cv::Mat** cvImage, const char* cameraId, std::vector<ANSCENTER::Object>& detectionResult);
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int RunInferenceComplete_CPP(void** Handle, cv::Mat** cvImage, const char* cameraId, const char* activeROIMode,std::vector<ANSCENTER::Object>& detectionResult);
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const char* OptimizeModelStr_CS(const char* modelFilePath, const char* modelFileZipPassword, int modelType, int modelDetectionType,int fp16);
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int ReleaseANSODHandle(void** Handle);
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int GetActiveRect(cv::Mat cvImage, cv::Rect& activeWindow);
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int GetODParameters(ANSCENTER::Params& param);
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int UpdateDetectionMinScore(float scoreThreshold);
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[[nodiscard]] bool IsLoaded() const;
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typedef const char* (*CreateANSODHandle_CSFuncT)(void**, const char*, const char*, const char*, float, float, float, int, int, int, int);
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typedef const char* (*OptimizeModelStr_CSFuncT)(const char*, const char*, int, int, int);
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typedef int (*RunInference_CPPFuncT)(void**, cv::Mat**, const char*, std::vector<ANSCENTER::Object>& detectionResult);
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typedef int (*RunInferenceComplete_CPPFuncT)(void**, cv::Mat**, const char*, const char*, std::vector<ANSCENTER::Object>& detectionResult);
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typedef int (*ReleaseANSODHandleFuncT)(void**);
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typedef int(*GetEngineTypeFuncT)();
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typedef int(*LoadModelFromFolderFuncT)(void**, const char*, const char*, const char*, float, float, float, int, int, int,int, const char*,std::string&);
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typedef int(*GetActiveRectFuncT)(void**, cv::Mat, cv::Rect&);
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typedef int(*DetectMovementFuncT)(void**, cv::Mat, const char*, std::vector<ANSCENTER::Object>&);
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typedef int(*OptimizeFuncT)(void**, bool);
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typedef int(*GetODParametersFuncT)(void**, ANSCENTER::Params&);
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typedef int(*UpdateDetectionMinScoreFuncT)(void**, float); // Add 'Func' to match other typedefs
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typedef int(*SetPromptFuncT)(void**, const char*);
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typedef int(*SetTrackerFuncT)(void**, int, int);
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typedef int(*SetTrackerParametersFuncT)(void**, const char*);
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CreateANSODHandle_CSFuncT CreateANSODHandle_CSFunc = nullptr;
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OptimizeModelStr_CSFuncT OptimizeModelStr_CSFunc = nullptr;
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ReleaseANSODHandleFuncT ReleaseANSODHandleFunc = nullptr;
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RunInference_CPPFuncT RunInference_CPPFunc = nullptr;
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RunInferenceComplete_CPPFuncT RunInferenceComplete_CPPFunc = nullptr;
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GetEngineTypeFuncT GetEngineTypeFunc = nullptr;
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LoadModelFromFolderFuncT LoadModelFromFolderFunc = nullptr;
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GetActiveRectFuncT GetActiveRectFunc = nullptr;
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DetectMovementFuncT DetectMovementFunc = nullptr;
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OptimizeFuncT OptimizeFunc = nullptr;
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GetODParametersFuncT GetODParametersFunc = nullptr;
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UpdateDetectionMinScoreFuncT UpdateDetectionMinScoreFunc = nullptr;
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SetPromptFuncT SetPromptFunc = nullptr;
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SetTrackerFuncT SetTrackerFunc = nullptr;
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SetTrackerParametersFuncT SetTrackerParametersFunc = nullptr;
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};
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}
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struct CustomObject
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{
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int classId{ 0 };
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int trackId{ 0 };
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std::string className{};
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float confidence{ 0.0 };
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cv::Rect box{};
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std::vector<cv::Point2f> polygon; // Polygon that contain x1,y1,x2,y2,x3,y3,x4,y4
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cv::Mat mask{}; // Face image in box (cropped) or mask image for segmentation
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cv::cuda::GpuMat gpuMask{}; // GPU-resident face crop (set by NV12 affine warp, avoids re-upload)
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std::vector<float> kps{}; // Pose exsimate 17 keypoints or oriented bouding box (xcenter, ycenter, width, height, angle)
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std::string extraInfo; // More information such as facial recognition
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std::string cameraId; // Use to check if this object belongs to any camera
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//std::string attributes; // Attributes such as keypoint string
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};
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struct CustomPoint { int x, y; };
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struct CustomROIConfig {
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bool Rectangle;
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bool Polygon;
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bool Line;
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int MinItems;
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int MaxItems;
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std::string Name;
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std::string ROIMatch;
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};
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struct CustomParameter {
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std::string Name;
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std::string DataType;
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int NoOfDecimals;
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int MaxValue;
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int MinValue;
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std::string StartValue;
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std::vector<std::string> ListItems;
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std::string DefaultValue;
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std::string Value;
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};
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struct CustomROIValue {
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std::string ROIMatch;
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std::vector<CustomPoint> ROIPoints;
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std::string Option;
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std::string Name;
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int OriginalImageSize;
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};
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struct CustomParams {
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std::vector<CustomROIConfig> ROI_Config;
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std::vector<std::string> ROI_Options;
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std::vector<CustomParameter> Parameters;
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std::vector<CustomROIValue> ROI_Values;
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};
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class CUSTOM_API IANSCustomClass
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{
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protected:
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std::string _modelDirectory; // The directory where the model is located
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float _detectionScoreThreshold{ 0.5 };
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CustomParams _params; // Parameters for the model
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bool _loadEngineOnCreate{ false }; // Load engine on create
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public:
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virtual bool Initialize(const std::string& modelDirectory, float detectionScoreThreshold, std::string& labelMap) = 0;
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virtual bool OptimizeModel(bool fp16) = 0;
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virtual std::vector<CustomObject> RunInference(const cv::Mat& input) = 0;
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virtual std::vector<CustomObject> RunInference(const cv::Mat& input, const std::string& camera_id) = 0;
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virtual bool ConfigureParameters(CustomParams& param) = 0;
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virtual bool Destroy() = 0;
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bool SetParameters(const CustomParams& param) {
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try {
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this->_params.ROI_Config.clear();
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for (auto& cf : param.ROI_Config) {
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this->_params.ROI_Config.push_back(cf);
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}
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this->_params.ROI_Options.clear();
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for (auto& op : param.ROI_Options) {
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this->_params.ROI_Options.push_back(op);
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}
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this->_params.Parameters.clear();
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for (auto& par : param.Parameters) {
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this->_params.Parameters.push_back(par);
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}
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this->_params.ROI_Values.clear();
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for (auto& roi : param.ROI_Values) {
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this->_params.ROI_Values.push_back(roi);
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}
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return true;
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}
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catch (...) {
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return false;
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}
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};
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void SetLoadEngineOnCreate(bool loadEngineOnCreate) {
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this->_loadEngineOnCreate = loadEngineOnCreate;
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}
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};
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#endif
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Block a user