<?xml version="1.0" encoding="GB2312"?>
<opencv_storage>
	<!--分类器-->
	<Classifier>
		<ModelPath>"../Resource/Models/Classifier/mnist-12.onnx"</ModelPath>
        <Scale>0.003922</Scale><!--缩放尺度-->
        <MeanValue1>0.0</MeanValue1><!--均值-->
        <MeanValue2>0.0</MeanValue2>
        <MeanValue3>0.0</MeanValue3>
        <SwapRB>0</SwapRB>
        <Crop>0</Crop>
		<UseInt8>0</UseInt8><!--是否使用int8,不支持-->
		<UseFP16>0</UseFP16><!--是否使用FP16-->
		<AddSoftmax>1</AddSoftmax><!--是否需要添加Softmax计算(如果onnx模型中包含了softmax，则设置为0)-->
	</Classifier>

	<!--超分辨率重建-->
	<Espcn>
		<ModelPath>"../Resource/Models/Super_Resolution/super.onnx"</ModelPath>
	</Espcn>

	<!--Unet-->
	<Unet>
		<ModelPath>"../Resource/Models/Segmentation/unet_13_256.onnx"</ModelPath>
	</Unet>
	
	<!--Bert-->
	<Bert>
		<ModelPath>"../Resource/Models/NLP/Bert/bertsquad-10.onnx"</ModelPath>
	</Bert>

	<!--GPT2-->
	<GPT2>
		<ModelPath>"../Resource/Models/NLP/GPT2/GPT2_shici.onnx"</ModelPath>
	</GPT2>

	<!--SSD检测器-->
	<DetectorSSD>
		<ModelPath>"../Resource/Models/Detector/SSD/yufacedetectnet-open-v2.onnx"</ModelPath>
        <Scale>1.0</Scale><!--缩放尺度-->
		<MeanValue1>0</MeanValue1><!--均值，顺序为bgr-->
		<MeanValue2>0</MeanValue2>
		<MeanValue3>0</MeanValue3>
		<SwapRB>0</SwapRB>
		<Crop>0</Crop>
		<UseInt8>0</UseInt8><!--是否使用int8,不支持-->
		<UseFP16>0</UseFP16><!--是否使用FP16-->

		<!--////////////////// SSD网络结构参数 ////////////////// -->
		<!--priorbox层的个数-->
		<PriorBoxLayerNumber>4</PriorBoxLayerNumber>

		<!--每个priorbox层的minisize和maxSize(需要与输出检测层顺序保持一致，下面涉及每个priorbox层参数的都需要保持顺序一致)-->
		<MinSize11>10</MinSize11>
		<MinSize12>16</MinSize12>
		<MinSize13>24</MinSize13>
		<MinSize21>32</MinSize21>
		<MinSize22>48</MinSize22>
		<MinSize31>64</MinSize31>
		<MinSize32>96</MinSize32>
		<MinSize41>128</MinSize41>
		<MinSize42>192</MinSize42>
		<MinSize43>256</MinSize43>

		<!--每个priorbox层的Flip和Clip(使用0,1表示)-->
		<Flip1>0</Flip1>
		<Flip2>0</Flip2>
		<Flip3>0</Flip3>
		<Flip4>0</Flip4>

		<Clip1>0</Clip1>
		<Clip2>0</Clip2>
		<Clip3>0</Clip3>
		<Clip4>0</Clip4>

		<!--每个priorbox层的宽高比(不包括1,且忽略flip,比如宽高比设置为0.3333和0.25且flip为true,则只需要写0.3333和0.25,如果宽高比只有1,则不用填写该项)-->
		<!-- <AspectRatio11>0.3333</AspectRatio11>
		<AspectRatio12>0.25</AspectRatio12>
		<AspectRatio21>0.3333</AspectRatio21>
		<AspectRatio22>0.25</AspectRatio22>
		<AspectRatio31>0.3333</AspectRatio31>
		<AspectRatio32>0.25</AspectRatio32>
		<AspectRatio41>0.3333</AspectRatio41>
		<AspectRatio42>0.25</AspectRatio42> -->

		<!--每个priorbox层的step-->
		<PriorBoxStepWidth1>8</PriorBoxStepWidth1><!--第一个priorbox层的step的width-->
		<PriorBoxStepWidth2>16</PriorBoxStepWidth2>
		<PriorBoxStepWidth3>32</PriorBoxStepWidth3>
		<PriorBoxStepWidth4>64</PriorBoxStepWidth4>

		<PriorBoxStepHeight1>8</PriorBoxStepHeight1><!--第一个priorbox层的step的height-->
		<PriorBoxStepHeight2>16</PriorBoxStepHeight2>
		<PriorBoxStepHeight3>32</PriorBoxStepHeight3>
		<PriorBoxStepHeight4>64</PriorBoxStepHeight4>

		<!--priorbox层中的offset-->
		<Offset>0.5</Offset>

		<!--DetectionOutput参数-->
		<ClassNumber>2</ClassNumber>
		<TopK>400</TopK>
		<KeepTopK>200</KeepTopK>
		<NMSThreshold>0.3</NMSThreshold>
		<ConfidenceThreshold>0.9</ConfidenceThreshold>
	</DetectorSSD>

	<!--RetinaFace检测器-->
	<DetectorRetinaFace>
		<ModelPath>"../Resource/Models/Detector/RetinaFace/mobilenet0.25_Final.onnx"</ModelPath>
        <Scale>1.0</Scale><!--缩放尺度-->
		<MeanValue1>104</MeanValue1><!--均值，顺序为bgr-->
		<MeanValue2>117</MeanValue2>
		<MeanValue3>123</MeanValue3>
		<SwapRB>0</SwapRB>
		<Crop>0</Crop>
		<UseInt8>0</UseInt8><!--是否使用int8,不支持-->
		<UseFP16>0</UseFP16><!--是否使用FP16-->

		<!--////////////////// RetinaFace检测器参数 ////////////////// -->
		<!--priorbox层的个数-->
		<PriorBoxLayerNumber>3</PriorBoxLayerNumber>

		<!--每个priorbox层的minisize和maxSize(需要与输出检测层顺序保持一致，下面涉及每个priorbox层参数的都需要保持顺序一致)-->
		<MinSize11>16</MinSize11>
		<MinSize12>32</MinSize12>
		<MinSize21>64</MinSize21>
		<MinSize22>128</MinSize22>
		<MinSize31>256</MinSize31>
		<MinSize32>512</MinSize32>

		<!--每个priorbox层的Flip和Clip(使用0,1表示)-->
		<Flip1>0</Flip1>
		<Flip2>0</Flip2>
		<Flip3>0</Flip3>

		<Clip1>0</Clip1>
		<Clip2>0</Clip2>
		<Clip3>0</Clip3>

		<!--每个priorbox层的宽高比(由于RetinaFace只包含宽高比为1的anchor，所以这里不需要设置宽高比)-->
		<!-- <AspectRatio11>0.3333</AspectRatio11>
		<AspectRatio12>0.25</AspectRatio12>
		<AspectRatio21>0.3333</AspectRatio21>
		<AspectRatio22>0.25</AspectRatio22>
		<AspectRatio31>0.3333</AspectRatio31>
		<AspectRatio32>0.25</AspectRatio32>
		<AspectRatio41>0.3333</AspectRatio41>
		<AspectRatio42>0.25</AspectRatio42> -->

		<!--每个priorbox层的step-->
		<PriorBoxStepWidth1>8</PriorBoxStepWidth1><!--第一个priorbox层的step的width-->
		<PriorBoxStepWidth2>16</PriorBoxStepWidth2>
		<PriorBoxStepWidth3>32</PriorBoxStepWidth3>

		<PriorBoxStepHeight1>8</PriorBoxStepHeight1><!--第一个priorbox层的step的height-->
		<PriorBoxStepHeight2>16</PriorBoxStepHeight2>
		<PriorBoxStepHeight3>32</PriorBoxStepHeight3>

		<!--priorbox层中的offset-->
		<Offset>0.5</Offset>

		<!--DetectionOutput参数-->
		<ClassNumber>2</ClassNumber>
		<TopK>400</TopK>
		<KeepTopK>200</KeepTopK>
		<NMSThreshold>0.3</NMSThreshold>
		<ConfidenceThreshold>0.9</ConfidenceThreshold>
	</DetectorRetinaFace>

	<!--YOLOV3检测器 -->
	<DetectorYOLOV3>
		<ModelPath>"../Resource/Models/Detector/YOLOV3/yolov3-tiny.onnx"</ModelPath>
		<ClassNameFile>"../Resource/Models/Detector/YOLOV3/coco.names"</ClassNameFile>
		<UseFP16>0</UseFP16><!--是否使用FP16-->
		<NumberOfClasses>80</NumberOfClasses><!--类别数(不包括背景类)，COCO:80,VOC:20-->
		<ConfidenceThreshold>0.2</ConfidenceThreshold>
		<NMSThreshold>0.4</NMSThreshold>
		<ObjectThreshold>0.4</ObjectThreshold>
	</DetectorYOLOV3>

	<!--YOLOV5检测器 -->
	<DetectorYOLOV5>
		<ModelPath>"../Resource/Models/Detector/YOLOV5/yolov5s.onnx"</ModelPath>
		<ClassNameFile>"../Resource/Models/Detector/YOLOV5/coco.names"</ClassNameFile>
		<UseFP16>0</UseFP16><!--是否使用FP16-->
		<NumberOfClasses>80</NumberOfClasses><!--类别数(不包括背景类)，COCO:80,VOC:20-->
		<ConfidenceThreshold>0.25</ConfidenceThreshold>
		<NMSThreshold>0.5</NMSThreshold>
		<ObjectThreshold>0.5</ObjectThreshold>
	</DetectorYOLOV5>

	<!--MTCNN检测器 -->
	<DetectorMTCNN>
		<PNet>
    		<ModelPath>"../Resource/Models/Detector/MTCNN/PNet.onnx"</ModelPath>
			<MaxHeight>512</MaxHeight>
			<MaxWidth>512</MaxWidth>
			<ConfidenceThreshold>0.90</ConfidenceThreshold>
	    	<UseFP16>0</UseFP16>
  		</PNet>
	</DetectorMTCNN>

	<!--YOLOV7检测器 -->
	<DetectorYOLOV7>
		<ModelPath>"../Resource/Models/Detector/YOLOV7/yolov7-tiny.onnx"</ModelPath>
		<ClassNameFile>"../Resource/Models/Detector/YOLOV7/coco.names"</ClassNameFile>
		<UseFP16>0</UseFP16><!--是否使用FP16-->
		<NumberOfClasses>80</NumberOfClasses><!--类别数(不包括背景类)，COCO:80,VOC:20-->
		<ConfidenceThreshold>0.25</ConfidenceThreshold>
		<NMSThreshold>0.5</NMSThreshold>
		<ObjectThreshold>0.5</ObjectThreshold>
	</DetectorYOLOV7>

	<!--CRNN动态文本识别 -->
	<CrnnDynamic>
		<ModelPath>"../Resource/Models/Ocr/CRNN/crnn_dynamic.onnx"</ModelPath>
	</CrnnDynamic>

	<!--PaddleOCR车牌检测 -->
	<OcrDB>
		<ModelPath>"../Resource/Models/PaddleOCR/VLPR/db.onnx"</ModelPath>
		<BinaryThreshold>0.3</BinaryThreshold>
		<BoxThreshold>0.5</BoxThreshold>
		<UnclipRatio>1.6</UnclipRatio>
		<LimitSideLen>2500</LimitSideLen>
		<ScoreMode>"fast"</ScoreMode>
	</OcrDB>

	<!--PaddleOCR车牌识别 -->
	<OcrSVTR>
		<ModelPath>"../Resource/Models/PaddleOCR/VLPR/svtr.onnx"</ModelPath>
		<DictPath>"../Resource/Models/PaddleOCR/VLPR/ppocr_keys_v1.txt"</DictPath>
	</OcrSVTR>
</opencv_storage>
