1121 lines
46 KiB
C#
Executable File
1121 lines
46 KiB
C#
Executable File
#if !UNITY_WSA_10_0
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using OpenCVForUnity.CoreModule;
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using OpenCVForUnity.UtilsModule;
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using System;
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using System.Collections.Generic;
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using System.Runtime.InteropServices;
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namespace OpenCVForUnity.DnnModule
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{
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// C++: class Dnn
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//javadoc: Dnn
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public class Dnn
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{
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// C++: enum Backend
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public const int DNN_BACKEND_DEFAULT = 0;
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public const int DNN_BACKEND_HALIDE = 1;
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public const int DNN_BACKEND_INFERENCE_ENGINE = 2;
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public const int DNN_BACKEND_OPENCV = 3;
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public const int DNN_BACKEND_VKCOM = 4;
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// C++: enum Target
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public const int DNN_TARGET_CPU = 0;
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public const int DNN_TARGET_OPENCL = 1;
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public const int DNN_TARGET_OPENCL_FP16 = 2;
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public const int DNN_TARGET_MYRIAD = 3;
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public const int DNN_TARGET_VULKAN = 4;
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//
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// C++: Mat cv::dnn::blobFromImage(Mat image, double scalefactor = 1.0, Size size = Size(), Scalar mean = Scalar(), bool swapRB = false, bool crop = false, int ddepth = CV_32F)
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//
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//javadoc: blobFromImage(image, scalefactor, size, mean, swapRB, crop, ddepth)
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public static Mat blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_10 (image.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB, crop, ddepth));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image, scalefactor, size, mean, swapRB, crop)
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public static Mat blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_11 (image.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB, crop));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image, scalefactor, size, mean, swapRB)
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public static Mat blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_12 (image.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image, scalefactor, size, mean)
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public static Mat blobFromImage (Mat image, double scalefactor, Size size, Scalar mean)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_13 (image.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3]));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image, scalefactor, size)
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public static Mat blobFromImage (Mat image, double scalefactor, Size size)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_14 (image.nativeObj, scalefactor, size.width, size.height));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image, scalefactor)
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public static Mat blobFromImage (Mat image, double scalefactor)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_15 (image.nativeObj, scalefactor));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImage(image)
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public static Mat blobFromImage (Mat image)
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{
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if (image != null)
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image.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_blobFromImage_16 (image.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Mat cv::dnn::blobFromImages(vector_Mat images, double scalefactor = 1.0, Size size = Size(), Scalar mean = Scalar(), bool swapRB = false, bool crop = false, int ddepth = CV_32F)
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//
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//javadoc: blobFromImages(images, scalefactor, size, mean, swapRB, crop, ddepth)
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public static Mat blobFromImages (List<Mat> images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_10 (images_mat.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB, crop, ddepth));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images, scalefactor, size, mean, swapRB, crop)
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public static Mat blobFromImages (List<Mat> images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_11 (images_mat.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB, crop));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images, scalefactor, size, mean, swapRB)
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public static Mat blobFromImages (List<Mat> images, double scalefactor, Size size, Scalar mean, bool swapRB)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_12 (images_mat.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3], swapRB));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images, scalefactor, size, mean)
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public static Mat blobFromImages (List<Mat> images, double scalefactor, Size size, Scalar mean)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_13 (images_mat.nativeObj, scalefactor, size.width, size.height, mean.val [0], mean.val [1], mean.val [2], mean.val [3]));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images, scalefactor, size)
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public static Mat blobFromImages (List<Mat> images, double scalefactor, Size size)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_14 (images_mat.nativeObj, scalefactor, size.width, size.height));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images, scalefactor)
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public static Mat blobFromImages (List<Mat> images, double scalefactor)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_15 (images_mat.nativeObj, scalefactor));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: blobFromImages(images)
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public static Mat blobFromImages (List<Mat> images)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat images_mat = Converters.vector_Mat_to_Mat (images);
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Mat retVal = new Mat (dnn_Dnn_blobFromImages_16 (images_mat.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Mat cv::dnn::readTensorFromONNX(String path)
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//
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//javadoc: readTensorFromONNX(path)
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public static Mat readTensorFromONNX (string path)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_readTensorFromONNX_10 (path));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Mat cv::dnn::readTorchBlob(String filename, bool isBinary = true)
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//
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//javadoc: readTorchBlob(filename, isBinary)
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public static Mat readTorchBlob (string filename, bool isBinary)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_readTorchBlob_10 (filename, isBinary));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readTorchBlob(filename)
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public static Mat readTorchBlob (string filename)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat retVal = new Mat (dnn_Dnn_readTorchBlob_11 (filename));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Net cv::dnn::readNet(String framework, vector_uchar bufferModel, vector_uchar bufferConfig = std::vector<uchar>())
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//
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//javadoc: readNet(framework, bufferModel, bufferConfig)
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public static Net readNet (string framework, MatOfByte bufferModel, MatOfByte bufferConfig)
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{
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if (bufferModel != null)
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bufferModel.ThrowIfDisposed ();
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if (bufferConfig != null)
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bufferConfig.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat bufferModel_mat = bufferModel;
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Mat bufferConfig_mat = bufferConfig;
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Net retVal = new Net (dnn_Dnn_readNet_10 (framework, bufferModel_mat.nativeObj, bufferConfig_mat.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNet(framework, bufferModel)
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public static Net readNet (string framework, MatOfByte bufferModel)
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{
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if (bufferModel != null)
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bufferModel.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat bufferModel_mat = bufferModel;
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Net retVal = new Net (dnn_Dnn_readNet_11 (framework, bufferModel_mat.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Net cv::dnn::readNet(String model, String config = "", String framework = "")
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//
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//javadoc: readNet(model, config, framework)
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public static Net readNet (string model, string config, string framework)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNet_12 (model, config, framework));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNet(model, config)
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public static Net readNet (string model, string config)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNet_13 (model, config));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNet(model)
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public static Net readNet (string model)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNet_14 (model));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Net cv::dnn::readNetFromCaffe(String prototxt, String caffeModel = String())
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//
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//javadoc: readNetFromCaffe(prototxt, caffeModel)
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public static Net readNetFromCaffe (string prototxt, string caffeModel)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNetFromCaffe_10 (prototxt, caffeModel));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNetFromCaffe(prototxt)
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public static Net readNetFromCaffe (string prototxt)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNetFromCaffe_11 (prototxt));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Net cv::dnn::readNetFromCaffe(vector_uchar bufferProto, vector_uchar bufferModel = std::vector<uchar>())
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//
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//javadoc: readNetFromCaffe(bufferProto, bufferModel)
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public static Net readNetFromCaffe (MatOfByte bufferProto, MatOfByte bufferModel)
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{
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if (bufferProto != null)
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bufferProto.ThrowIfDisposed ();
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if (bufferModel != null)
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bufferModel.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat bufferProto_mat = bufferProto;
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Mat bufferModel_mat = bufferModel;
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Net retVal = new Net (dnn_Dnn_readNetFromCaffe_12 (bufferProto_mat.nativeObj, bufferModel_mat.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNetFromCaffe(bufferProto)
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public static Net readNetFromCaffe (MatOfByte bufferProto)
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{
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if (bufferProto != null)
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bufferProto.ThrowIfDisposed ();
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Mat bufferProto_mat = bufferProto;
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Net retVal = new Net (dnn_Dnn_readNetFromCaffe_13 (bufferProto_mat.nativeObj));
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return retVal;
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#else
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return null;
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#endif
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}
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//
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// C++: Net cv::dnn::readNetFromDarknet(String cfgFile, String darknetModel = String())
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//
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//javadoc: readNetFromDarknet(cfgFile, darknetModel)
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public static Net readNetFromDarknet (string cfgFile, string darknetModel)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNetFromDarknet_10 (cfgFile, darknetModel));
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return retVal;
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#else
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return null;
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#endif
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}
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//javadoc: readNetFromDarknet(cfgFile)
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public static Net readNetFromDarknet (string cfgFile)
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{
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#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
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Net retVal = new Net (dnn_Dnn_readNetFromDarknet_11 (cfgFile));
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|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromDarknet(vector_uchar bufferCfg, vector_uchar bufferModel = std::vector<uchar>())
|
|
//
|
|
|
|
//javadoc: readNetFromDarknet(bufferCfg, bufferModel)
|
|
public static Net readNetFromDarknet (MatOfByte bufferCfg, MatOfByte bufferModel)
|
|
{
|
|
if (bufferCfg != null)
|
|
bufferCfg.ThrowIfDisposed ();
|
|
if (bufferModel != null)
|
|
bufferModel.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bufferCfg_mat = bufferCfg;
|
|
Mat bufferModel_mat = bufferModel;
|
|
Net retVal = new Net (dnn_Dnn_readNetFromDarknet_12 (bufferCfg_mat.nativeObj, bufferModel_mat.nativeObj));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: readNetFromDarknet(bufferCfg)
|
|
public static Net readNetFromDarknet (MatOfByte bufferCfg)
|
|
{
|
|
if (bufferCfg != null)
|
|
bufferCfg.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bufferCfg_mat = bufferCfg;
|
|
Net retVal = new Net (dnn_Dnn_readNetFromDarknet_13 (bufferCfg_mat.nativeObj));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromModelOptimizer(String xml, String bin)
|
|
//
|
|
|
|
//javadoc: readNetFromModelOptimizer(xml, bin)
|
|
public static Net readNetFromModelOptimizer (string xml, string bin)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromModelOptimizer_10 (xml, bin));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromONNX(String onnxFile)
|
|
//
|
|
|
|
//javadoc: readNetFromONNX(onnxFile)
|
|
public static Net readNetFromONNX (string onnxFile)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromONNX_10 (onnxFile));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromTensorflow(String model, String config = String())
|
|
//
|
|
|
|
//javadoc: readNetFromTensorflow(model, config)
|
|
public static Net readNetFromTensorflow (string model, string config)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTensorflow_10 (model, config));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: readNetFromTensorflow(model)
|
|
public static Net readNetFromTensorflow (string model)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTensorflow_11 (model));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromTensorflow(vector_uchar bufferModel, vector_uchar bufferConfig = std::vector<uchar>())
|
|
//
|
|
|
|
//javadoc: readNetFromTensorflow(bufferModel, bufferConfig)
|
|
public static Net readNetFromTensorflow (MatOfByte bufferModel, MatOfByte bufferConfig)
|
|
{
|
|
if (bufferModel != null)
|
|
bufferModel.ThrowIfDisposed ();
|
|
if (bufferConfig != null)
|
|
bufferConfig.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bufferModel_mat = bufferModel;
|
|
Mat bufferConfig_mat = bufferConfig;
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTensorflow_12 (bufferModel_mat.nativeObj, bufferConfig_mat.nativeObj));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: readNetFromTensorflow(bufferModel)
|
|
public static Net readNetFromTensorflow (MatOfByte bufferModel)
|
|
{
|
|
if (bufferModel != null)
|
|
bufferModel.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bufferModel_mat = bufferModel;
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTensorflow_13 (bufferModel_mat.nativeObj));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: Net cv::dnn::readNetFromTorch(String model, bool isBinary = true)
|
|
//
|
|
|
|
//javadoc: readNetFromTorch(model, isBinary)
|
|
public static Net readNetFromTorch (string model, bool isBinary)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTorch_10 (model, isBinary));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: readNetFromTorch(model)
|
|
public static Net readNetFromTorch (string model)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
Net retVal = new Net (dnn_Dnn_readNetFromTorch_11 (model));
|
|
|
|
return retVal;
|
|
#else
|
|
return null;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::NMSBoxes(vector_Rect bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
|
|
//
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices, eta, top_k)
|
|
public static void NMSBoxes (MatOfRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_10 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta, top_k);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices, eta)
|
|
public static void NMSBoxes (MatOfRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_11 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices)
|
|
public static void NMSBoxes (MatOfRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_12 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::NMSBoxes(vector_Rect2d bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
|
|
//
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices, eta, top_k)
|
|
public static void NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_13 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta, top_k);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices, eta)
|
|
public static void NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_14 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxes(bboxes, scores, score_threshold, nms_threshold, indices)
|
|
public static void NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxes_15 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::NMSBoxes(vector_RotatedRect bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
|
|
//
|
|
|
|
//javadoc: NMSBoxesRotated(bboxes, scores, score_threshold, nms_threshold, indices, eta, top_k)
|
|
public static void NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxesRotated_10 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta, top_k);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxesRotated(bboxes, scores, score_threshold, nms_threshold, indices, eta)
|
|
public static void NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxesRotated_11 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj, eta);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: NMSBoxesRotated(bboxes, scores, score_threshold, nms_threshold, indices)
|
|
public static void NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices)
|
|
{
|
|
if (bboxes != null)
|
|
bboxes.ThrowIfDisposed ();
|
|
if (scores != null)
|
|
scores.ThrowIfDisposed ();
|
|
if (indices != null)
|
|
indices.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat bboxes_mat = bboxes;
|
|
Mat scores_mat = scores;
|
|
Mat indices_mat = indices;
|
|
dnn_Dnn_NMSBoxesRotated_12 (bboxes_mat.nativeObj, scores_mat.nativeObj, score_threshold, nms_threshold, indices_mat.nativeObj);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::imagesFromBlob(Mat blob_, vector_Mat& images_)
|
|
//
|
|
|
|
//javadoc: imagesFromBlob(blob_, images_)
|
|
public static void imagesFromBlob (Mat blob_, List<Mat> images_)
|
|
{
|
|
if (blob_ != null)
|
|
blob_.ThrowIfDisposed ();
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat images__mat = new Mat ();
|
|
dnn_Dnn_imagesFromBlob_10 (blob_.nativeObj, images__mat.nativeObj);
|
|
Converters.Mat_to_vector_Mat (images__mat, images_);
|
|
images__mat.release ();
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::resetMyriadDevice()
|
|
//
|
|
|
|
//javadoc: resetMyriadDevice()
|
|
public static void resetMyriadDevice ()
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
dnn_Dnn_resetMyriadDevice_10 ();
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::shrinkCaffeModel(String src, String dst, vector_String layersTypes = std::vector<String>())
|
|
//
|
|
|
|
//javadoc: shrinkCaffeModel(src, dst, layersTypes)
|
|
public static void shrinkCaffeModel (string src, string dst, List<string> layersTypes)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
Mat layersTypes_mat = Converters.vector_String_to_Mat (layersTypes);
|
|
dnn_Dnn_shrinkCaffeModel_10 (src, dst, layersTypes_mat.nativeObj);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
//javadoc: shrinkCaffeModel(src, dst)
|
|
public static void shrinkCaffeModel (string src, string dst)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
dnn_Dnn_shrinkCaffeModel_11 (src, dst);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
|
|
//
|
|
// C++: void cv::dnn::writeTextGraph(String model, String output)
|
|
//
|
|
|
|
//javadoc: writeTextGraph(model, output)
|
|
public static void writeTextGraph (string model, string output)
|
|
{
|
|
#if ((UNITY_ANDROID || UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR) || UNITY_5 || UNITY_5_3_OR_NEWER
|
|
|
|
dnn_Dnn_writeTextGraph_10 (model, output);
|
|
|
|
return;
|
|
#else
|
|
return;
|
|
#endif
|
|
}
|
|
|
|
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#if (UNITY_IOS || UNITY_WEBGL) && !UNITY_EDITOR
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const string LIBNAME = "__Internal";
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#else
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const string LIBNAME = "opencvforunity";
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#endif
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// C++: Mat cv::dnn::blobFromImage(Mat image, double scalefactor = 1.0, Size size = Size(), Scalar mean = Scalar(), bool swapRB = false, bool crop = false, int ddepth = CV_32F)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_10 (IntPtr image_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB, bool crop, int ddepth);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_11 (IntPtr image_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB, bool crop);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_12 (IntPtr image_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_13 (IntPtr image_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_14 (IntPtr image_nativeObj, double scalefactor, double size_width, double size_height);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_15 (IntPtr image_nativeObj, double scalefactor);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImage_16 (IntPtr image_nativeObj);
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// C++: Mat cv::dnn::blobFromImages(vector_Mat images, double scalefactor = 1.0, Size size = Size(), Scalar mean = Scalar(), bool swapRB = false, bool crop = false, int ddepth = CV_32F)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_10 (IntPtr images_mat_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB, bool crop, int ddepth);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_11 (IntPtr images_mat_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB, bool crop);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_12 (IntPtr images_mat_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3, bool swapRB);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_13 (IntPtr images_mat_nativeObj, double scalefactor, double size_width, double size_height, double mean_val0, double mean_val1, double mean_val2, double mean_val3);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_14 (IntPtr images_mat_nativeObj, double scalefactor, double size_width, double size_height);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_15 (IntPtr images_mat_nativeObj, double scalefactor);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_blobFromImages_16 (IntPtr images_mat_nativeObj);
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// C++: Mat cv::dnn::readTensorFromONNX(String path)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readTensorFromONNX_10 (string path);
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// C++: Mat cv::dnn::readTorchBlob(String filename, bool isBinary = true)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readTorchBlob_10 (string filename, bool isBinary);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readTorchBlob_11 (string filename);
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// C++: Net cv::dnn::readNet(String framework, vector_uchar bufferModel, vector_uchar bufferConfig = std::vector<uchar>())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNet_10 (string framework, IntPtr bufferModel_mat_nativeObj, IntPtr bufferConfig_mat_nativeObj);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNet_11 (string framework, IntPtr bufferModel_mat_nativeObj);
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// C++: Net cv::dnn::readNet(String model, String config = "", String framework = "")
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNet_12 (string model, string config, string framework);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNet_13 (string model, string config);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNet_14 (string model);
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// C++: Net cv::dnn::readNetFromCaffe(String prototxt, String caffeModel = String())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromCaffe_10 (string prototxt, string caffeModel);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromCaffe_11 (string prototxt);
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// C++: Net cv::dnn::readNetFromCaffe(vector_uchar bufferProto, vector_uchar bufferModel = std::vector<uchar>())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromCaffe_12 (IntPtr bufferProto_mat_nativeObj, IntPtr bufferModel_mat_nativeObj);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromCaffe_13 (IntPtr bufferProto_mat_nativeObj);
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// C++: Net cv::dnn::readNetFromDarknet(String cfgFile, String darknetModel = String())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromDarknet_10 (string cfgFile, string darknetModel);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromDarknet_11 (string cfgFile);
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// C++: Net cv::dnn::readNetFromDarknet(vector_uchar bufferCfg, vector_uchar bufferModel = std::vector<uchar>())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromDarknet_12 (IntPtr bufferCfg_mat_nativeObj, IntPtr bufferModel_mat_nativeObj);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromDarknet_13 (IntPtr bufferCfg_mat_nativeObj);
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// C++: Net cv::dnn::readNetFromModelOptimizer(String xml, String bin)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromModelOptimizer_10 (string xml, string bin);
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// C++: Net cv::dnn::readNetFromONNX(String onnxFile)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromONNX_10 (string onnxFile);
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// C++: Net cv::dnn::readNetFromTensorflow(String model, String config = String())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTensorflow_10 (string model, string config);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTensorflow_11 (string model);
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// C++: Net cv::dnn::readNetFromTensorflow(vector_uchar bufferModel, vector_uchar bufferConfig = std::vector<uchar>())
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTensorflow_12 (IntPtr bufferModel_mat_nativeObj, IntPtr bufferConfig_mat_nativeObj);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTensorflow_13 (IntPtr bufferModel_mat_nativeObj);
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// C++: Net cv::dnn::readNetFromTorch(String model, bool isBinary = true)
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTorch_10 (string model, bool isBinary);
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[DllImport (LIBNAME)]
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private static extern IntPtr dnn_Dnn_readNetFromTorch_11 (string model);
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// C++: void cv::dnn::NMSBoxes(vector_Rect bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_10 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta, int top_k);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_11 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_12 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj);
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// C++: void cv::dnn::NMSBoxes(vector_Rect2d bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_13 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta, int top_k);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_14 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxes_15 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj);
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// C++: void cv::dnn::NMSBoxes(vector_RotatedRect bboxes, vector_float scores, float score_threshold, float nms_threshold, vector_int& indices, float eta = 1.f, int top_k = 0)
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxesRotated_10 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta, int top_k);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxesRotated_11 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj, float eta);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_NMSBoxesRotated_12 (IntPtr bboxes_mat_nativeObj, IntPtr scores_mat_nativeObj, float score_threshold, float nms_threshold, IntPtr indices_mat_nativeObj);
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// C++: void cv::dnn::imagesFromBlob(Mat blob_, vector_Mat& images_)
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_imagesFromBlob_10 (IntPtr blob__nativeObj, IntPtr images__mat_nativeObj);
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// C++: void cv::dnn::resetMyriadDevice()
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_resetMyriadDevice_10 ();
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// C++: void cv::dnn::shrinkCaffeModel(String src, String dst, vector_String layersTypes = std::vector<String>())
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_shrinkCaffeModel_10 (string src, string dst, IntPtr layersTypes_mat_nativeObj);
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_shrinkCaffeModel_11 (string src, string dst);
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// C++: void cv::dnn::writeTextGraph(String model, String output)
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[DllImport (LIBNAME)]
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private static extern void dnn_Dnn_writeTextGraph_10 (string model, string output);
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}
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}
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#endif |