OpenCVForUnity.DnnModule.Dnn Class Reference

Static Public Member Functions
static Mat	blobFromImage (Mat image)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in Vec2d size)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in Vec2d size, in Vec4d mean)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in(double width, double height) size)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, Size size)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, Size size, Scalar mean)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImage (Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in Vec2d size)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in(double width, double height) size)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, Size size)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, Size size, Scalar mean)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImages (List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth)
	Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.
static Mat	blobFromImagesWithParams (List< Mat > images)
	Creates 4-dimensional blob from series of images with given params.
static Mat	blobFromImagesWithParams (List< Mat > images, Image2BlobParams param)
	Creates 4-dimensional blob from series of images with given params.
static void	blobFromImagesWithParams (List< Mat > images, Mat blob)
static void	blobFromImagesWithParams (List< Mat > images, Mat blob, Image2BlobParams param)
static Mat	blobFromImageWithParams (Mat image)
	Creates 4-dimensional blob from image with given params.
static Mat	blobFromImageWithParams (Mat image, Image2BlobParams param)
	Creates 4-dimensional blob from image with given params.
static void	blobFromImageWithParams (Mat image, Mat blob)
static void	blobFromImageWithParams (Mat image, Mat blob, Image2BlobParams param)
static List< int >	getAvailableTargets (int be)
static string	getInferenceEngineBackendType ()
	Returns Inference Engine internal backend API.
static string	getInferenceEngineCPUType ()
	Returns Inference Engine CPU type.
static string	getInferenceEngineVPUType ()
	Returns Inference Engine VPU type.
static void	imagesFromBlob (Mat blob_, List< Mat > images_)
	Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>).
static void	NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices)
	Performs non maximum suppression given boxes and corresponding scores.
static void	NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
	Performs non maximum suppression given boxes and corresponding scores.
static void	NMSBoxes (MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
	Performs non maximum suppression given boxes and corresponding scores.
static void	NMSBoxesBatched (MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices)
	Performs batched non maximum suppression on given boxes and corresponding scores across different classes.
static void	NMSBoxesBatched (MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
	Performs batched non maximum suppression on given boxes and corresponding scores across different classes.
static void	NMSBoxesBatched (MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
	Performs batched non maximum suppression on given boxes and corresponding scores across different classes.
static void	NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices)
static void	NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta)
static void	NMSBoxesRotated (MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k)
static Net	readNet (string framework, MatOfByte bufferModel)
	Read deep learning network represented in one of the supported formats.
static Net	readNet (string framework, MatOfByte bufferModel, MatOfByte bufferConfig)
	Read deep learning network represented in one of the supported formats.
static Net	readNet (string model)
	Read deep learning network represented in one of the supported formats.
static Net	readNet (string model, string config)
	Read deep learning network represented in one of the supported formats.
static Net	readNet (string model, string config, string framework)
	Read deep learning network represented in one of the supported formats.
static Net	readNetFromCaffe (MatOfByte bufferProto)
	Reads a network model stored in Caffe model in memory.
static Net	readNetFromCaffe (MatOfByte bufferProto, MatOfByte bufferModel)
	Reads a network model stored in Caffe model in memory.
static Net	readNetFromCaffe (string prototxt)
	Reads a network model stored in <a href="http://caffe.berkeleyvision.org">Caffe</a> framework's format.
static Net	readNetFromCaffe (string prototxt, string caffeModel)
	Reads a network model stored in <a href="http://caffe.berkeleyvision.org">Caffe</a> framework's format.
static Net	readNetFromDarknet (MatOfByte bufferCfg)
	Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.
static Net	readNetFromDarknet (MatOfByte bufferCfg, MatOfByte bufferModel)
	Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.
static Net	readNetFromDarknet (string cfgFile)
	Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.
static Net	readNetFromDarknet (string cfgFile, string darknetModel)
	Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.
static Net	readNetFromModelOptimizer (MatOfByte bufferModelConfig, MatOfByte bufferWeights)
	Load a network from Intel's Model Optimizer intermediate representation.
static Net	readNetFromModelOptimizer (string xml)
	Load a network from Intel's Model Optimizer intermediate representation.
static Net	readNetFromModelOptimizer (string xml, string bin)
	Load a network from Intel's Model Optimizer intermediate representation.
static Net	readNetFromONNX (MatOfByte buffer)
	Reads a network model from <a href="https://onnx.ai/">ONNX</a> in-memory buffer.
static Net	readNetFromONNX (string onnxFile)
	Reads a network model <a href="https://onnx.ai/">ONNX</a>.
static Net	readNetFromTensorflow (MatOfByte bufferModel)
	Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.
static Net	readNetFromTensorflow (MatOfByte bufferModel, MatOfByte bufferConfig)
	Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.
static Net	readNetFromTensorflow (string model)
	Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.
static Net	readNetFromTensorflow (string model, string config)
	Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.
static Net	readNetFromTFLite (MatOfByte bufferModel)
	Reads a network model stored in <a href="https://www.tensorflow.org/lite">TFLite</a> framework's format.
static Net	readNetFromTFLite (string model)
	Reads a network model stored in <a href="https://www.tensorflow.org/lite">TFLite</a> framework's format.
static Net	readNetFromTorch (string model)
	Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.
static Net	readNetFromTorch (string model, bool isBinary)
	Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.
static Net	readNetFromTorch (string model, bool isBinary, bool evaluate)
	Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.
static Mat	readTensorFromONNX (string path)
	Creates blob from .pb file.
static Mat	readTorchBlob (string filename)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework.
static Mat	readTorchBlob (string filename, bool isBinary)
	Loads blob which was serialized as torch.Tensor object of Torch7 framework.
static void	releaseHDDLPlugin ()
	Release a HDDL plugin.
static void	resetMyriadDevice ()
	Release a Myriad device (binded by OpenCV).
static string	setInferenceEngineBackendType (string newBackendType)
	Specify Inference Engine internal backend API.
static void	shrinkCaffeModel (string src, string dst)
	Convert all weights of Caffe network to half precision floating point.
static void	shrinkCaffeModel (string src, string dst, List< string > layersTypes)
	Convert all weights of Caffe network to half precision floating point.
static void	softNMSBoxes (MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices)
	Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.
static void	softNMSBoxes (MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices, long top_k)
	Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.
static void	softNMSBoxes (MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices, long top_k, float sigma)
	Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.
static void	writeTextGraph (string model, string output)
	Create a text representation for a binary network stored in protocol buffer format.

Static Public Attributes
const int	DNN_BACKEND_CANN = 0 + 8
const int	DNN_BACKEND_CUDA = 0 + 5
const int	DNN_BACKEND_DEFAULT = 0
const int	DNN_BACKEND_HALIDE = 0 + 1
const int	DNN_BACKEND_INFERENCE_ENGINE = 0 + 2
const int	DNN_BACKEND_OPENCV = 0 + 3
const int	DNN_BACKEND_TIMVX = 0 + 7
const int	DNN_BACKEND_VKCOM = 0 + 4
const int	DNN_BACKEND_WEBNN = 0 + 6
const int	DNN_LAYOUT_NCDHW = 3
const int	DNN_LAYOUT_NCHW = 2
const int	DNN_LAYOUT_ND = 1
const int	DNN_LAYOUT_NDHWC = 5
const int	DNN_LAYOUT_NHWC = 4
const int	DNN_LAYOUT_PLANAR = 6
const int	DNN_LAYOUT_UNKNOWN = 0
const int	DNN_PMODE_CROP_CENTER = 1
const int	DNN_PMODE_LETTERBOX = 2
const int	DNN_PMODE_NULL = 0
const int	DNN_TARGET_CPU = 0
const int	DNN_TARGET_CPU_FP16 = 0 + 10
const int	DNN_TARGET_CUDA = 0 + 6
const int	DNN_TARGET_CUDA_FP16 = 0 + 7
const int	DNN_TARGET_FPGA = 0 + 5
const int	DNN_TARGET_HDDL = 0 + 8
const int	DNN_TARGET_MYRIAD = 0 + 3
const int	DNN_TARGET_NPU = 0 + 9
const int	DNN_TARGET_OPENCL = 0 + 1
const int	DNN_TARGET_OPENCL_FP16 = 0 + 2
const int	DNN_TARGET_VULKAN = 0 + 4
const int	SoftNMSMethod_SOFTNMS_GAUSSIAN = 2
const int	SoftNMSMethod_SOFTNMS_LINEAR = 1

Member Function Documentation

blobFromImage() [1/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [2/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [3/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in Vec2d size )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [4/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in Vec2d size, in Vec4d mean )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [5/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [6/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [7/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [8/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in(double width, double height) size )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [9/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [10/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [11/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [12/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [13/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, Size size )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [14/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, Size size, Scalar mean )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [15/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, Size size, Scalar mean, bool swapRB )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [16/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImage() [17/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImage ( Mat image, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from image. Optionally resizes and crops image from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

image	input image (with 1-, 3- or 4-channels).
scalefactor	multiplier for images values.
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [1/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [2/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [3/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in Vec2d size )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [4/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [5/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [6/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [7/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in Vec2d size, in Vec4d mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [8/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in(double width, double height) size )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [9/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [10/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [11/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [12/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, in(double width, double height) size, in(double v0, double v1, double v2, double v3) mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [13/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, Size size )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [14/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, Size size, Scalar mean )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [15/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [16/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImages() [17/17]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImages ( List< Mat > images, double scalefactor, Size size, Scalar mean, bool swapRB, bool crop, int ddepth )

static

Creates 4-dimensional blob from series of images. Optionally resizes and crops images from center, subtract mean values, scales values by scalefactor, swap Blue and Red channels.

Parameters

images	input images (all with 1-, 3- or 4-channels).
size	spatial size for output image
mean	scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if image has BGR ordering and swapRB is true.
scalefactor	multiplier for images values.
swapRB	flag which indicates that swap first and last channels in 3-channel image is necessary.
crop	flag which indicates whether image will be cropped after resize or not
ddepth	Depth of output blob. Choose CV_32F or CV_8U.

if crop is true, input image is resized so one side after resize is equal to corresponding dimension in size and another one is equal or larger. Then, crop from the center is performed. If crop is false, direct resize without cropping and preserving aspect ratio is performed.

Returns

4-dimensional Mat with NCHW dimensions order.

Note

The order and usage of scalefactor and mean are (input - mean) * scalefactor.

blobFromImagesWithParams() [1/4]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImagesWithParams ( List< Mat > images )

static

Creates 4-dimensional blob from series of images with given params.

This function is an extension of blobFromImages to meet more image preprocess needs. Given input image and preprocessing parameters, and function outputs the blob.

Parameters

images	input image (all with 1-, 3- or 4-channels).
param	struct of Image2BlobParams, contains all parameters needed by processing of image to blob.

Returns

4-dimensional Mat.

blobFromImagesWithParams() [2/4]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImagesWithParams ( List< Mat > images, Image2BlobParams param )

static

Creates 4-dimensional blob from series of images with given params.

This function is an extension of blobFromImages to meet more image preprocess needs. Given input image and preprocessing parameters, and function outputs the blob.

Parameters

images	input image (all with 1-, 3- or 4-channels).
param	struct of Image2BlobParams, contains all parameters needed by processing of image to blob.

Returns

4-dimensional Mat.

blobFromImagesWithParams() [3/4]

static void OpenCVForUnity.DnnModule.Dnn.blobFromImagesWithParams ( List< Mat > images, Mat blob )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

blobFromImagesWithParams() [4/4]

static void OpenCVForUnity.DnnModule.Dnn.blobFromImagesWithParams ( List< Mat > images, Mat blob, Image2BlobParams param )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

blobFromImageWithParams() [1/4]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImageWithParams ( Mat image )

static

Creates 4-dimensional blob from image with given params.

This function is an extension of blobFromImage to meet more image preprocess needs. Given input image and preprocessing parameters, and function outputs the blob.

Parameters

image	input image (all with 1-, 3- or 4-channels).
param	struct of Image2BlobParams, contains all parameters needed by processing of image to blob.

Returns

4-dimensional Mat.

blobFromImageWithParams() [2/4]

static Mat OpenCVForUnity.DnnModule.Dnn.blobFromImageWithParams ( Mat image, Image2BlobParams param )

static

Creates 4-dimensional blob from image with given params.

This function is an extension of blobFromImage to meet more image preprocess needs. Given input image and preprocessing parameters, and function outputs the blob.

Parameters

image	input image (all with 1-, 3- or 4-channels).
param	struct of Image2BlobParams, contains all parameters needed by processing of image to blob.

Returns

4-dimensional Mat.

blobFromImageWithParams() [3/4]

static void OpenCVForUnity.DnnModule.Dnn.blobFromImageWithParams ( Mat image, Mat blob )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

blobFromImageWithParams() [4/4]

static void OpenCVForUnity.DnnModule.Dnn.blobFromImageWithParams ( Mat image, Mat blob, Image2BlobParams param )

static

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

getAvailableTargets()

static List< int > OpenCVForUnity.DnnModule.Dnn.getAvailableTargets ( int be )

static

getInferenceEngineBackendType()

static string OpenCVForUnity.DnnModule.Dnn.getInferenceEngineBackendType ( )

static

Returns Inference Engine internal backend API.

See values of CV_DNN_BACKEND_INFERENCE_ENGINE_* macros.

OPENCV_DNN_BACKEND_INFERENCE_ENGINE_TYPE runtime parameter (environment variable) is ignored since 4.6.0.

Deprecated

getInferenceEngineCPUType()

static string OpenCVForUnity.DnnModule.Dnn.getInferenceEngineCPUType ( )

static

Returns Inference Engine CPU type.

Specify OpenVINO plugin: CPU or ARM.

getInferenceEngineVPUType()

static string OpenCVForUnity.DnnModule.Dnn.getInferenceEngineVPUType ( )

static

Returns Inference Engine VPU type.

See values of CV_DNN_INFERENCE_ENGINE_VPU_TYPE_* macros.

imagesFromBlob()

static void OpenCVForUnity.DnnModule.Dnn.imagesFromBlob ( Mat blob_, List< Mat > images_ )

static

Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>).

NMSBoxes() [1/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxes ( MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices )

static

Performs non maximum suppression given boxes and corresponding scores.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxes() [2/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxes ( MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta )

static

Performs non maximum suppression given boxes and corresponding scores.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxes() [3/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxes ( MatOfRect2d bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k )

static

Performs non maximum suppression given boxes and corresponding scores.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxesBatched() [1/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesBatched ( MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices )

static

Performs batched non maximum suppression on given boxes and corresponding scores across different classes.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
class_ids	a set of corresponding class ids. Ids are integer and usually start from 0.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxesBatched() [2/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesBatched ( MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices, float eta )

static

Performs batched non maximum suppression on given boxes and corresponding scores across different classes.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
class_ids	a set of corresponding class ids. Ids are integer and usually start from 0.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxesBatched() [3/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesBatched ( MatOfRect2d bboxes, MatOfFloat scores, MatOfInt class_ids, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k )

static

Performs batched non maximum suppression on given boxes and corresponding scores across different classes.

Parameters

bboxes	a set of bounding boxes to apply NMS.
scores	a set of corresponding confidences.
class_ids	a set of corresponding class ids. Ids are integer and usually start from 0.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
eta	a coefficient in adaptive threshold formula: \(nms\_threshold_{i+1}=eta\cdot nms\_threshold_i\).
top_k	if >0, keep at most top_k picked indices.

NMSBoxesRotated() [1/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesRotated ( MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices )

static

NMSBoxesRotated() [2/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesRotated ( MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta )

static

NMSBoxesRotated() [3/3]

static void OpenCVForUnity.DnnModule.Dnn.NMSBoxesRotated ( MatOfRotatedRect bboxes, MatOfFloat scores, float score_threshold, float nms_threshold, MatOfInt indices, float eta, int top_k )

static

readNet() [1/5]

static Net OpenCVForUnity.DnnModule.Dnn.readNet ( string framework, MatOfByte bufferModel )

static

Read deep learning network represented in one of the supported formats.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Returns

Net object.

readNet() [2/5]

static Net OpenCVForUnity.DnnModule.Dnn.readNet ( string framework, MatOfByte bufferModel, MatOfByte bufferConfig )

static

Read deep learning network represented in one of the supported formats.

This is an overloaded member function, provided for convenience. It differs from the above function only in what argument(s) it accepts.

Returns

Net object.

readNet() [3/5]

static Net OpenCVForUnity.DnnModule.Dnn.readNet ( string model )

static

Read deep learning network represented in one of the supported formats.

Returns

Net object.

This function automatically detects an origin framework of trained model and calls an appropriate function such readNetFromCaffe, readNetFromTensorflow, readNetFromTorch or readNetFromDarknet. An order of model and config arguments does not matter.

readNet() [4/5]

static Net OpenCVForUnity.DnnModule.Dnn.readNet ( string model, string config )

static

Read deep learning network represented in one of the supported formats.

Returns

Net object.

This function automatically detects an origin framework of trained model and calls an appropriate function such readNetFromCaffe, readNetFromTensorflow, readNetFromTorch or readNetFromDarknet. An order of model and config arguments does not matter.

readNet() [5/5]

static Net OpenCVForUnity.DnnModule.Dnn.readNet ( string model, string config, string framework )

static

Read deep learning network represented in one of the supported formats.

Returns

Net object.

This function automatically detects an origin framework of trained model and calls an appropriate function such readNetFromCaffe, readNetFromTensorflow, readNetFromTorch or readNetFromDarknet. An order of model and config arguments does not matter.

readNetFromCaffe() [1/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromCaffe ( MatOfByte bufferProto )

static

Reads a network model stored in Caffe model in memory.

Parameters

bufferProto	buffer containing the content of the .prototxt file
bufferModel	buffer containing the content of the .caffemodel file

Returns

Net object.

readNetFromCaffe() [2/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromCaffe ( MatOfByte bufferProto, MatOfByte bufferModel )

static

Reads a network model stored in Caffe model in memory.

Parameters

bufferProto	buffer containing the content of the .prototxt file
bufferModel	buffer containing the content of the .caffemodel file

Returns

Net object.

readNetFromCaffe() [3/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromCaffe ( string prototxt )

static

Reads a network model stored in <a href="http://caffe.berkeleyvision.org">Caffe</a> framework's format.

Parameters

prototxt	path to the .prototxt file with text description of the network architecture.
caffeModel	path to the .caffemodel file with learned network.

Returns

Net object.

readNetFromCaffe() [4/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromCaffe ( string prototxt, string caffeModel )

static

Reads a network model stored in <a href="http://caffe.berkeleyvision.org">Caffe</a> framework's format.

Parameters

prototxt	path to the .prototxt file with text description of the network architecture.
caffeModel	path to the .caffemodel file with learned network.

Returns

Net object.

readNetFromDarknet() [1/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromDarknet ( MatOfByte bufferCfg )

static

Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.

Parameters

bufferCfg	A buffer contains a content of .cfg file with text description of the network architecture.
bufferModel	A buffer contains a content of .weights file with learned network.

Returns

Net object.

readNetFromDarknet() [2/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromDarknet ( MatOfByte bufferCfg, MatOfByte bufferModel )

static

Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.

Parameters

bufferCfg	A buffer contains a content of .cfg file with text description of the network architecture.
bufferModel	A buffer contains a content of .weights file with learned network.

Returns

Net object.

readNetFromDarknet() [3/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromDarknet ( string cfgFile )

static

Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.

Parameters

cfgFile	path to the .cfg file with text description of the network architecture.
darknetModel	path to the .weights file with learned network.

Returns

Network object that ready to do forward, throw an exception in failure cases.

readNetFromDarknet() [4/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromDarknet ( string cfgFile, string darknetModel )

static

Reads a network model stored in <a href="https://pjreddie.com/darknet/">Darknet</a> model files.

Parameters

cfgFile	path to the .cfg file with text description of the network architecture.
darknetModel	path to the .weights file with learned network.

Returns

Network object that ready to do forward, throw an exception in failure cases.

readNetFromModelOptimizer() [1/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromModelOptimizer ( MatOfByte bufferModelConfig, MatOfByte bufferWeights )

static

Load a network from Intel's Model Optimizer intermediate representation.

Returns

Net object. Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine backend.

readNetFromModelOptimizer() [2/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromModelOptimizer ( string xml )

static

Load a network from Intel's Model Optimizer intermediate representation.

Returns

Net object. Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine backend.

readNetFromModelOptimizer() [3/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromModelOptimizer ( string xml, string bin )

static

Load a network from Intel's Model Optimizer intermediate representation.

Returns

Net object. Networks imported from Intel's Model Optimizer are launched in Intel's Inference Engine backend.

readNetFromONNX() [1/2]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromONNX ( MatOfByte buffer )

static

Reads a network model from <a href="https://onnx.ai/">ONNX</a> in-memory buffer.

Parameters

buffer

in-memory buffer that stores the ONNX model bytes.

Returns

Network object that ready to do forward, throw an exception in failure cases.

readNetFromONNX() [2/2]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromONNX ( string onnxFile )

static

Reads a network model <a href="https://onnx.ai/">ONNX</a>.

Parameters

onnxFile

path to the .onnx file with text description of the network architecture.

Returns

Network object that ready to do forward, throw an exception in failure cases.

readNetFromTensorflow() [1/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTensorflow ( MatOfByte bufferModel )

static

Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.

Parameters

bufferModel	buffer containing the content of the pb file
bufferConfig	buffer containing the content of the pbtxt file

Returns

Net object.

readNetFromTensorflow() [2/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTensorflow ( MatOfByte bufferModel, MatOfByte bufferConfig )

static

Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.

Parameters

bufferModel	buffer containing the content of the pb file
bufferConfig	buffer containing the content of the pbtxt file

Returns

Net object.

readNetFromTensorflow() [3/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTensorflow ( string model )

static

Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.

Parameters

model	path to the .pb file with binary protobuf description of the network architecture
config	path to the .pbtxt file that contains text graph definition in protobuf format. Resulting Net object is built by text graph using weights from a binary one that let us make it more flexible.

Returns

Net object.

readNetFromTensorflow() [4/4]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTensorflow ( string model, string config )

static

Reads a network model stored in <a href="https://www.tensorflow.org/">TensorFlow</a> framework's format.

Parameters

model	path to the .pb file with binary protobuf description of the network architecture
config	path to the .pbtxt file that contains text graph definition in protobuf format. Resulting Net object is built by text graph using weights from a binary one that let us make it more flexible.

Returns

Net object.

readNetFromTFLite() [1/2]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTFLite ( MatOfByte bufferModel )

static

Reads a network model stored in <a href="https://www.tensorflow.org/lite">TFLite</a> framework's format.

Parameters

bufferModel

buffer containing the content of the tflite file

Returns

Net object.

readNetFromTFLite() [2/2]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTFLite ( string model )

static

Reads a network model stored in <a href="https://www.tensorflow.org/lite">TFLite</a> framework's format.

Parameters

model

path to the .tflite file with binary flatbuffers description of the network architecture

Returns

Net object.

readNetFromTorch() [1/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTorch ( string model )

static

Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.

Parameters

model	path to the file, dumped from Torch by using torch.save() function.
isBinary	specifies whether the network was serialized in ascii mode or binary.
evaluate	specifies testing phase of network. If true, it's similar to evaluate() method in Torch.

Returns

Net object.

Note

Ascii mode of Torch serializer is more preferable, because binary mode extensively use long type of C language, which has various bit-length on different systems.

The loading file must contain serialized <a href="https://github.com/torch/nn/blob/master/doc/module.md">nn.Module</a> object with importing network. Try to eliminate a custom objects from serialazing data to avoid importing errors.

List of supported layers (i.e. object instances derived from Torch nn.Module class):

• nn.Sequential
• nn.Parallel
• nn.Concat
• nn.Linear
• nn.SpatialConvolution
• nn.SpatialMaxPooling, nn.SpatialAveragePooling
• nn.ReLU, nn.TanH, nn.Sigmoid
• nn.Reshape
• nn.SoftMax, nn.LogSoftMax

Also some equivalents of these classes from cunn, cudnn, and fbcunn may be successfully imported.

readNetFromTorch() [2/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTorch ( string model, bool isBinary )

static

Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.

Parameters

model	path to the file, dumped from Torch by using torch.save() function.
isBinary	specifies whether the network was serialized in ascii mode or binary.
evaluate	specifies testing phase of network. If true, it's similar to evaluate() method in Torch.

Returns

Net object.

Note

Ascii mode of Torch serializer is more preferable, because binary mode extensively use long type of C language, which has various bit-length on different systems.

The loading file must contain serialized <a href="https://github.com/torch/nn/blob/master/doc/module.md">nn.Module</a> object with importing network. Try to eliminate a custom objects from serialazing data to avoid importing errors.

List of supported layers (i.e. object instances derived from Torch nn.Module class):

• nn.Sequential
• nn.Parallel
• nn.Concat
• nn.Linear
• nn.SpatialConvolution
• nn.SpatialMaxPooling, nn.SpatialAveragePooling
• nn.ReLU, nn.TanH, nn.Sigmoid
• nn.Reshape
• nn.SoftMax, nn.LogSoftMax

Also some equivalents of these classes from cunn, cudnn, and fbcunn may be successfully imported.

readNetFromTorch() [3/3]

static Net OpenCVForUnity.DnnModule.Dnn.readNetFromTorch ( string model, bool isBinary, bool evaluate )

static

Reads a network model stored in <a href="http://torch.ch">Torch7</a> framework's format.

Parameters

model	path to the file, dumped from Torch by using torch.save() function.
isBinary	specifies whether the network was serialized in ascii mode or binary.
evaluate	specifies testing phase of network. If true, it's similar to evaluate() method in Torch.

Returns

Net object.

Note

Ascii mode of Torch serializer is more preferable, because binary mode extensively use long type of C language, which has various bit-length on different systems.

The loading file must contain serialized <a href="https://github.com/torch/nn/blob/master/doc/module.md">nn.Module</a> object with importing network. Try to eliminate a custom objects from serialazing data to avoid importing errors.

List of supported layers (i.e. object instances derived from Torch nn.Module class):

• nn.Sequential
• nn.Parallel
• nn.Concat
• nn.Linear
• nn.SpatialConvolution
• nn.SpatialMaxPooling, nn.SpatialAveragePooling
• nn.ReLU, nn.TanH, nn.Sigmoid
• nn.Reshape
• nn.SoftMax, nn.LogSoftMax

Also some equivalents of these classes from cunn, cudnn, and fbcunn may be successfully imported.

readTensorFromONNX()

static Mat OpenCVForUnity.DnnModule.Dnn.readTensorFromONNX ( string path )

static

Creates blob from .pb file.

Parameters

path	to the .pb file with input tensor.

Returns

Mat.

readTorchBlob() [1/2]

static Mat OpenCVForUnity.DnnModule.Dnn.readTorchBlob ( string filename )

static

Loads blob which was serialized as torch.Tensor object of Torch7 framework.

Warning

This function has the same limitations as readNetFromTorch().

readTorchBlob() [2/2]

static Mat OpenCVForUnity.DnnModule.Dnn.readTorchBlob ( string filename, bool isBinary )

static

Loads blob which was serialized as torch.Tensor object of Torch7 framework.

Warning

This function has the same limitations as readNetFromTorch().

releaseHDDLPlugin()

static void OpenCVForUnity.DnnModule.Dnn.releaseHDDLPlugin ( )

static

Release a HDDL plugin.

resetMyriadDevice()

static void OpenCVForUnity.DnnModule.Dnn.resetMyriadDevice ( )

static

Release a Myriad device (binded by OpenCV).

Single Myriad device cannot be shared across multiple processes which uses Inference Engine's Myriad plugin.

setInferenceEngineBackendType()

static string OpenCVForUnity.DnnModule.Dnn.setInferenceEngineBackendType ( string newBackendType )

static

Specify Inference Engine internal backend API.

See values of CV_DNN_BACKEND_INFERENCE_ENGINE_* macros.

Returns

previous value of internal backend API

Deprecated

shrinkCaffeModel() [1/2]

static void OpenCVForUnity.DnnModule.Dnn.shrinkCaffeModel ( string src, string dst )

static

Convert all weights of Caffe network to half precision floating point.

Parameters

src	Path to origin model from Caffe framework contains single precision floating point weights (usually has .caffemodel extension).
dst	Path to destination model with updated weights.
layersTypes	Set of layers types which parameters will be converted. By default, converts only Convolutional and Fully-Connected layers' weights.

Note

Shrinked model has no origin float32 weights so it can't be used in origin Caffe framework anymore. However the structure of data is taken from NVidia's Caffe fork: https://github.com/NVIDIA/caffe. So the resulting model may be used there.

shrinkCaffeModel() [2/2]

static void OpenCVForUnity.DnnModule.Dnn.shrinkCaffeModel ( string src, string dst, List< string > layersTypes )

static

Convert all weights of Caffe network to half precision floating point.

Parameters

src	Path to origin model from Caffe framework contains single precision floating point weights (usually has .caffemodel extension).
dst	Path to destination model with updated weights.
layersTypes	Set of layers types which parameters will be converted. By default, converts only Convolutional and Fully-Connected layers' weights.

Note

Shrinked model has no origin float32 weights so it can't be used in origin Caffe framework anymore. However the structure of data is taken from NVidia's Caffe fork: https://github.com/NVIDIA/caffe. So the resulting model may be used there.

softNMSBoxes() [1/3]

static void OpenCVForUnity.DnnModule.Dnn.softNMSBoxes ( MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices )

static

Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.

Parameters

bboxes	a set of bounding boxes to apply Soft NMS.
scores	a set of corresponding confidences.
updated_scores	a set of corresponding updated confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
top_k	keep at most top_k picked indices.
sigma	parameter of Gaussian weighting.
method	Gaussian or linear.

SoftNMSMethod

softNMSBoxes() [2/3]

static void OpenCVForUnity.DnnModule.Dnn.softNMSBoxes ( MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices, long top_k )

static

Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.

Parameters

bboxes	a set of bounding boxes to apply Soft NMS.
scores	a set of corresponding confidences.
updated_scores	a set of corresponding updated confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
top_k	keep at most top_k picked indices.
sigma	parameter of Gaussian weighting.
method	Gaussian or linear.

SoftNMSMethod

softNMSBoxes() [3/3]

static void OpenCVForUnity.DnnModule.Dnn.softNMSBoxes ( MatOfRect bboxes, MatOfFloat scores, MatOfFloat updated_scores, float score_threshold, float nms_threshold, MatOfInt indices, long top_k, float sigma )

static

Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503.

Parameters

bboxes	a set of bounding boxes to apply Soft NMS.
scores	a set of corresponding confidences.
updated_scores	a set of corresponding updated confidences.
score_threshold	a threshold used to filter boxes by score.
nms_threshold	a threshold used in non maximum suppression.
indices	the kept indices of bboxes after NMS.
top_k	keep at most top_k picked indices.
sigma	parameter of Gaussian weighting.
method	Gaussian or linear.

SoftNMSMethod

writeTextGraph()

static void OpenCVForUnity.DnnModule.Dnn.writeTextGraph ( string model, string output )

static

Create a text representation for a binary network stored in protocol buffer format.

Note

To reduce output file size, trained weights are not included.

Member Data Documentation

DNN_BACKEND_CANN

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_CANN = 0 + 8

static

DNN_BACKEND_CUDA

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_CUDA = 0 + 5

static

DNN_BACKEND_DEFAULT

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_DEFAULT = 0

static

DNN_BACKEND_HALIDE

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_HALIDE = 0 + 1

static

DNN_BACKEND_INFERENCE_ENGINE

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_INFERENCE_ENGINE = 0 + 2

static

DNN_BACKEND_OPENCV

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_OPENCV = 0 + 3

static

DNN_BACKEND_TIMVX

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_TIMVX = 0 + 7

static

DNN_BACKEND_VKCOM

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_VKCOM = 0 + 4

static

DNN_BACKEND_WEBNN

const int OpenCVForUnity.DnnModule.Dnn.DNN_BACKEND_WEBNN = 0 + 6

static

DNN_LAYOUT_NCDHW

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_NCDHW = 3

static

DNN_LAYOUT_NCHW

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_NCHW = 2

static

DNN_LAYOUT_ND

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_ND = 1

static

DNN_LAYOUT_NDHWC

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_NDHWC = 5

static

DNN_LAYOUT_NHWC

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_NHWC = 4

static

DNN_LAYOUT_PLANAR

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_PLANAR = 6

static

DNN_LAYOUT_UNKNOWN

const int OpenCVForUnity.DnnModule.Dnn.DNN_LAYOUT_UNKNOWN = 0

static

DNN_PMODE_CROP_CENTER

const int OpenCVForUnity.DnnModule.Dnn.DNN_PMODE_CROP_CENTER = 1

static

DNN_PMODE_LETTERBOX

const int OpenCVForUnity.DnnModule.Dnn.DNN_PMODE_LETTERBOX = 2

static

DNN_PMODE_NULL

const int OpenCVForUnity.DnnModule.Dnn.DNN_PMODE_NULL = 0

static

DNN_TARGET_CPU

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_CPU = 0

static

DNN_TARGET_CPU_FP16

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_CPU_FP16 = 0 + 10

static

DNN_TARGET_CUDA

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_CUDA = 0 + 6

static

DNN_TARGET_CUDA_FP16

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_CUDA_FP16 = 0 + 7

static

DNN_TARGET_FPGA

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_FPGA = 0 + 5

static

DNN_TARGET_HDDL

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_HDDL = 0 + 8

static

DNN_TARGET_MYRIAD

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_MYRIAD = 0 + 3

static

DNN_TARGET_NPU

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_NPU = 0 + 9

static

DNN_TARGET_OPENCL

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_OPENCL = 0 + 1

static

DNN_TARGET_OPENCL_FP16

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_OPENCL_FP16 = 0 + 2

static

DNN_TARGET_VULKAN

const int OpenCVForUnity.DnnModule.Dnn.DNN_TARGET_VULKAN = 0 + 4

static

SoftNMSMethod_SOFTNMS_GAUSSIAN

const int OpenCVForUnity.DnnModule.Dnn.SoftNMSMethod_SOFTNMS_GAUSSIAN = 2

static

SoftNMSMethod_SOFTNMS_LINEAR

const int OpenCVForUnity.DnnModule.Dnn.SoftNMSMethod_SOFTNMS_LINEAR = 1

static

---

The documentation for this class was generated from the following files:

• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Dnn.cs
• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Dnn_Struct.cs
• OpenCVForUnity/Assets/OpenCVForUnity/org/opencv/dnn/Dnn_ValueTuple.cs