Class CvDnn

cv::dnn functions

Inheritance
System.Object
CvDnn
Inherited Members
System.Object.Equals(System.Object)
System.Object.Equals(System.Object, System.Object)
System.Object.GetHashCode()
System.Object.GetType()
System.Object.MemberwiseClone()
System.Object.ReferenceEquals(System.Object, System.Object)
System.Object.ToString()
Namespace: OpenCvSharp.Dnn
Assembly: OpenCvSharp.dll
Syntax
public static class CvDnn

Methods

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BlobFromImage(Mat, Double, Size, Scalar, Boolean, Boolean)

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

Declaration
public static Mat BlobFromImage(Mat image, double scaleFactor = 1, Size size = default(Size), Scalar mean = default(Scalar), bool swapRB = true, bool crop = true)
Parameters
Type Name Description
Mat image

input image (with 1- or 3-channels).
System.Double scaleFactor

multiplier for @p image values.
OpenCvSharp.Size size

spatial size for output image
OpenCvSharp.Scalar mean

scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if @p image has BGR ordering and @p swapRB is true.
System.Boolean swapRB

flag which indicates that swap first and last channels in 3-channel image is necessary.
System.Boolean crop

flag which indicates whether image will be cropped after resize or not
Returns
Type Description
Mat

4-dimansional Mat with NCHW dimensions order.
Remarks

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

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BlobFromImages(IEnumerable<Mat>, Double, Size, Scalar, Boolean, Boolean)

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

Declaration
public static Mat BlobFromImages(IEnumerable<Mat> images, double scaleFactor, Size size = default(Size), Scalar mean = default(Scalar), bool swapRB = true, bool crop = true)
Parameters
Type Name Description
IEnumerable<Mat> images

input images (all with 1- or 3-channels).
System.Double scaleFactor

multiplier for @p image values.
OpenCvSharp.Size size

spatial size for output image
OpenCvSharp.Scalar mean

scalar with mean values which are subtracted from channels. Values are intended to be in (mean-R, mean-G, mean-B) order if @p image has BGR ordering and @p swapRB is true.
System.Boolean swapRB

flag which indicates that swap first and last channels in 3-channel image is necessary.
System.Boolean crop

flag which indicates whether image will be cropped after resize or not
Returns
Type Description
Mat

4-dimansional Mat with NCHW dimensions order.
Remarks

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

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NMSBoxes(IEnumerable<Rect>, IEnumerable<Single>, Single, Single, out Int32[], Single, Int32)

Performs non maximum suppression given boxes and corresponding scores.

Declaration
public static void NMSBoxes(IEnumerable<Rect> bboxes, IEnumerable<float> scores, float scoreThreshold, float nmsThreshold, out int[] indices, float eta = 1F, int topK = 0)
Parameters
Type Name Description
IEnumerable<OpenCvSharp.Rect> bboxes

a set of bounding boxes to apply NMS.
IEnumerable<System.Single> scores

a set of corresponding confidences.
System.Single scoreThreshold

a threshold used to filter boxes by score.
System.Single nmsThreshold

a threshold used in non maximum suppression.
System.Int32[] indices

the kept indices of bboxes after NMS.
System.Single eta

a coefficient in adaptive threshold formula
System.Int32 topK

if >0, keep at most @p top_k picked indices.
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NMSBoxes(IEnumerable<Rect2d>, IEnumerable<Single>, Single, Single, out Int32[], Single, Int32)

Performs non maximum suppression given boxes and corresponding scores.

Declaration
public static void NMSBoxes(IEnumerable<Rect2d> bboxes, IEnumerable<float> scores, float scoreThreshold, float nmsThreshold, out int[] indices, float eta = 1F, int topK = 0)
Parameters
Type Name Description
IEnumerable<OpenCvSharp.Rect2d> bboxes

a set of bounding boxes to apply NMS.
IEnumerable<System.Single> scores

a set of corresponding confidences.
System.Single scoreThreshold

a threshold used to filter boxes by score.
System.Single nmsThreshold

a threshold used in non maximum suppression.
System.Int32[] indices

the kept indices of bboxes after NMS.
System.Single eta

a coefficient in adaptive threshold formula
System.Int32 topK

if >0, keep at most @p top_k picked indices.
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NMSBoxes(IEnumerable<RotatedRect>, IEnumerable<Single>, Single, Single, out Int32[], Single, Int32)

Performs non maximum suppression given boxes and corresponding scores.

Declaration
public static void NMSBoxes(IEnumerable<RotatedRect> bboxes, IEnumerable<float> scores, float scoreThreshold, float nmsThreshold, out int[] indices, float eta = 1F, int topK = 0)
Parameters
Type Name Description
IEnumerable<OpenCvSharp.RotatedRect> bboxes

a set of bounding boxes to apply NMS.
IEnumerable<System.Single> scores

a set of corresponding confidences.
System.Single scoreThreshold

a threshold used to filter boxes by score.
System.Single nmsThreshold

a threshold used in non maximum suppression.
System.Int32[] indices

the kept indices of bboxes after NMS.
System.Single eta

a coefficient in adaptive threshold formula
System.Int32 topK

if >0, keep at most @p top_k picked indices.
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ReadNet(String, String, String)

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

This function automatically detects an origin framework of trained model and calls an appropriate function such @ref readNetFromCaffe, @ref readNetFromTensorflow,

Declaration
public static Net ReadNet(string model, string config = "", string framework = "")
Parameters
Type Name Description
System.String model

Binary file contains trained weights. The following file

  •              extensions are expected for models from different frameworks:

  •              * `*.caffemodel` (Caffe, http://caffe.berkeleyvision.org/)

  •              * `*.pb` (TensorFlow, https://www.tensorflow.org/)

  •              * `*.t7` | `*.net` (Torch, http://torch.ch/)

  •              * `*.weights` (Darknet, https://pjreddie.com/darknet/)

  •              * `*.bin` (DLDT, https://software.intel.com/openvino-toolkit)
System.String config

Text file contains network configuration. It could be a

  •               file with the following extensions:

  •              * `*.prototxt` (Caffe, http://caffe.berkeleyvision.org/)

  •              * `*.pbtxt` (TensorFlow, https://www.tensorflow.org/)

  •              * `*.cfg` (Darknet, https://pjreddie.com/darknet/)

  •              * `*.xml` (DLDT, https://software.intel.com/openvino-toolkit)
System.String framework

Explicit framework name tag to determine a format.
Returns
Type Description
Net
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ReadNetFromCaffe(ReadOnlySpan<Byte>, ReadOnlySpan<Byte>)

Reads a network model stored in Caffe model files from memory.

Declaration
public static Net ReadNetFromCaffe(ReadOnlySpan<byte> bufferProto, ReadOnlySpan<byte> bufferModel = null)
Parameters
Type Name Description
ReadOnlySpan<System.Byte> bufferProto

buffer containing the content of the .prototxt file
ReadOnlySpan<System.Byte> bufferModel

buffer containing the content of the .caffemodel file
Returns
Type Description
Net
Remarks

This is shortcut consisting from createCaffeImporter and Net::populateNet calls.

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ReadNetFromCaffe(Stream, Nullable<Stream>)

Reads a network model stored in Caffe model files from Stream.

Declaration
public static Net ReadNetFromCaffe(Stream bufferProto, Stream? bufferModel = null)
Parameters
Type Name Description
Stream bufferProto

buffer containing the content of the .prototxt file
System.Nullable<Stream> bufferModel

buffer containing the content of the .caffemodel file
Returns
Type Description
Net
Remarks

This is shortcut consisting from createCaffeImporter and Net::populateNet calls.

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ReadNetFromCaffe(Byte[], Byte[])

Reads a network model stored in Caffe model files from memory.

Declaration
public static Net ReadNetFromCaffe(byte[] bufferProto, byte[] bufferModel = null)
Parameters
Type Name Description
System.Byte[] bufferProto

buffer containing the content of the .prototxt file
System.Byte[] bufferModel

buffer containing the content of the .caffemodel file
Returns
Type Description
Net
Remarks

This is shortcut consisting from createCaffeImporter and Net::populateNet calls.

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ReadNetFromCaffe(String, String)

Reads a network model stored in Caffe model files.

Declaration
public static Net ReadNetFromCaffe(string prototxt, string caffeModel = null)
Parameters
Type Name Description
System.String prototxt

path to the .prototxt file with text description of the network architecture.
System.String caffeModel

path to the .caffemodel file with learned network.
Returns
Type Description
Net
Remarks

This is shortcut consisting from createCaffeImporter and Net::populateNet calls.

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ReadNetFromDarknet(Stream, Nullable<Stream>)

Reads a network model stored in Darknet (https://pjreddie.com/darknet/) model files from stream.

Declaration
public static Net ReadNetFromDarknet(Stream bufferCfg, Stream? bufferModel = null)
Parameters
Type Name Description
Stream bufferCfg

A buffer contains a content of .cfg file with text description of the network architecture.
System.Nullable<Stream> bufferModel

A buffer contains a content of .weights file with learned network.
Returns
Type Description
Net
Remarks

This is shortcut consisting from DarknetImporter and Net::populateNet calls.

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ReadNetFromDarknet(Byte[], Byte[])

Reads a network model stored in Darknet (https://pjreddie.com/darknet/) model files from memory.

Declaration
public static Net ReadNetFromDarknet(byte[] bufferCfg, byte[] bufferModel = null)
Parameters
Type Name Description
System.Byte[] bufferCfg

A buffer contains a content of .cfg file with text description of the network architecture.
System.Byte[] bufferModel

A buffer contains a content of .weights file with learned network.
Returns
Type Description
Net
Remarks

This is shortcut consisting from DarknetImporter and Net::populateNet calls.

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ReadNetFromDarknet(String, String)

Reads a network model stored in Darknet (https://pjreddie.com/darknet/) model files.

Declaration
public static Net ReadNetFromDarknet(string cfgFile, string darknetModel = null)
Parameters
Type Name Description
System.String cfgFile

path to the .cfg file with text description of the network architecture.
System.String darknetModel

path to the .weights file with learned network.
Returns
Type Description
Net

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

This is shortcut consisting from DarknetImporter and Net::populateNet calls.

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ReadNetFromOnnx(ReadOnlySpan<Byte>)

Reads a network model ONNX https://onnx.ai/ from memory

Declaration
public static Net ReadNetFromOnnx(ReadOnlySpan<byte> onnxFileData)
Parameters
Type Name Description
ReadOnlySpan<System.Byte> onnxFileData

memory of the first byte of the buffer.
Returns
Type Description
Net
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ReadNetFromOnnx(Stream)

Reads a network model ONNX https://onnx.ai/ from stream.

Declaration
public static Net ReadNetFromOnnx(Stream onnxFileStream)
Parameters
Type Name Description
Stream onnxFileStream

memory of the first byte of the buffer.
Returns
Type Description
Net
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ReadNetFromOnnx(Byte[])

Reads a network model ONNX https://onnx.ai/ from memory

Declaration
public static Net ReadNetFromOnnx(byte[] onnxFileData)
Parameters
Type Name Description
System.Byte[] onnxFileData

memory of the first byte of the buffer.
Returns
Type Description
Net
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ReadNetFromOnnx(String)

Reads a network model ONNX https://onnx.ai/ from memory

Declaration
public static Net ReadNetFromOnnx(string onnxFile)
Parameters
Type Name Description
System.String onnxFile
Returns
Type Description
Net
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ReadNetFromTensorflow(Stream, Nullable<Stream>)

Reads a network model stored in Tensorflow model file from stream.

Declaration
public static Net ReadNetFromTensorflow(Stream bufferModel, Stream? bufferConfig = null)
Parameters
Type Name Description
Stream bufferModel

buffer containing the content of the pb file
System.Nullable<Stream> bufferConfig

buffer containing the content of the pbtxt file (optional)
Returns
Type Description
Net
Remarks

This is shortcut consisting from createTensorflowImporter and Net::populateNet calls.

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ReadNetFromTensorflow(Byte[], Byte[])

Reads a network model stored in Tensorflow model file from memory.

Declaration
public static Net ReadNetFromTensorflow(byte[] bufferModel, byte[] bufferConfig = null)
Parameters
Type Name Description
System.Byte[] bufferModel

buffer containing the content of the pb file
System.Byte[] bufferConfig

buffer containing the content of the pbtxt file (optional)
Returns
Type Description
Net
Remarks

This is shortcut consisting from createTensorflowImporter and Net::populateNet calls.

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ReadNetFromTensorflow(String, String)

Reads a network model stored in Tensorflow model file.

Declaration
public static Net ReadNetFromTensorflow(string model, string config = null)
Parameters
Type Name Description
System.String model

path to the .pb file with binary protobuf description of the network architecture
System.String config

path to the .pbtxt file that contains text graph definition in protobuf format.
Returns
Type Description
Net

Resulting Net object is built by text graph using weights from a binary one that let us make it more flexible.
Remarks

This is shortcut consisting from createTensorflowImporter and Net::populateNet calls.

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ReadNetFromTorch(String, Boolean)

Reads a network model stored in Torch model file.

Declaration
public static Net ReadNetFromTorch(string model, bool isBinary = true)
Parameters
Type Name Description
System.String model
System.Boolean isBinary
Returns
Type Description
Net
Remarks

This is shortcut consisting from createTorchImporter and Net::populateNet calls.

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ReadTensorFromONNX(String)

Creates blob from .pb file.

Declaration
public static Mat ReadTensorFromONNX(string path)
Parameters
Type Name Description
System.String path

path to the .pb file with input tensor.
Returns
Type Description
Mat
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ReadTorchBlob(String, Boolean)

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

Declaration
public static Mat ReadTorchBlob(string fileName, bool isBinary = true)
Parameters
Type Name Description
System.String fileName
System.Boolean isBinary
Returns
Type Description
Mat
Remarks

This function has the same limitations as createTorchImporter().

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ResetMyriadDevice()

Release a Myriad device is binded by OpenCV.

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

Declaration
public static void ResetMyriadDevice()
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ShrinkCaffeModel(String, String, Nullable<IEnumerable<String>>)

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

Declaration
public static void ShrinkCaffeModel(string src, string dst, IEnumerable<string>? layersTypes = null)
Parameters
Type Name Description
System.String src

Path to origin model from Caffe framework contains single precision floating point weights(usually has .caffemodel extension).
System.String dst

Path to destination model with updated weights.
System.Nullable<IEnumerable<System.String>> layersTypes

Set of layers types which parameters will be converted. By default, converts only Convolutional and Fully-Connected layers' weights.
Remarks

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.

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WriteTextGraph(String, String)

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

Declaration
public static void WriteTextGraph(string model, string output)
Parameters
Type Name Description
System.String model

A path to binary network.
System.String output

A path to output text file to be created.