OpenCV
4.5.5
Open Source Computer Vision
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Namespaces | |
details | |
Classes | |
struct | _Range |
class | AbsLayer |
class | AccumLayer |
class | AcoshLayer |
class | AcosLayer |
class | ActivationLayer |
class | ActivationLayerInt8 |
class | ArgLayer |
ArgMax/ArgMin layer. More... | |
class | AsinhLayer |
class | AsinLayer |
class | AtanhLayer |
class | AtanLayer |
class | BackendNode |
Derivatives of this class encapsulates functions of certain backends. More... | |
class | BackendWrapper |
Derivatives of this class wraps cv::Mat for different backends and targets. More... | |
class | BaseConvolutionLayer |
class | BatchNormLayer |
class | BatchNormLayerInt8 |
class | BlankLayer |
class | BNLLLayer |
class | CeilLayer |
class | CeluLayer |
class | ChannelsPReLULayer |
class | ClassificationModel |
This class represents high-level API for classification models. More... | |
class | CompareLayer |
class | ConcatLayer |
class | ConstLayer |
class | ConvolutionLayer |
class | ConvolutionLayerInt8 |
class | CorrelationLayer |
class | CoshLayer |
class | CosLayer |
class | CropAndResizeLayer |
class | CropLayer |
class | CumSumLayer |
class | DataAugmentationLayer |
class | DeconvolutionLayer |
class | DequantizeLayer |
class | DetectionModel |
This class represents high-level API for object detection networks. More... | |
class | DetectionOutputLayer |
Detection output layer. More... | |
class | Dict |
This class implements name-value dictionary, values are instances of DictValue. More... | |
struct | DictValue |
This struct stores the scalar value (or array) of one of the following type: double, cv::String or int64. More... | |
class | EltwiseLayer |
Element wise operation on inputs. More... | |
class | EltwiseLayerInt8 |
class | ELULayer |
class | ErfLayer |
class | ExpLayer |
class | FlattenLayer |
class | FloorLayer |
class | FlowWarpLayer |
class | GRULayer |
GRU recurrent one-layer. More... | |
class | HardSigmoidLayer |
class | HardSwishLayer |
class | InnerProductLayer |
class | InnerProductLayerInt8 |
class | InterpLayer |
Bilinear resize layer from https://github.com/cdmh/deeplab-public-ver2. More... | |
class | KeypointsModel |
This class represents high-level API for keypoints models. More... | |
class | Layer |
This interface class allows to build new Layers - are building blocks of networks. More... | |
class | LayerFactory |
Layer factory allows to create instances of registered layers. More... | |
class | LayerParams |
This class provides all data needed to initialize layer. More... | |
class | LogLayer |
class | LRNLayer |
class | LSTMLayer |
LSTM recurrent layer. More... | |
class | MaxUnpoolLayer |
class | MishLayer |
class | Model |
This class is presented high-level API for neural networks. More... | |
class | MVNLayer |
class | Net |
This class allows to create and manipulate comprehensive artificial neural networks. More... | |
class | NormalizeBBoxLayer |
\( L_p \) - normalization layer. More... | |
class | NotLayer |
class | PaddingLayer |
Adds extra values for specific axes. More... | |
class | PermuteLayer |
class | PoolingLayer |
class | PoolingLayerInt8 |
class | PowerLayer |
class | PriorBoxLayer |
class | ProposalLayer |
class | QuantizeLayer |
class | RegionLayer |
class | ReLU6Layer |
class | ReLULayer |
class | ReorgLayer |
class | RequantizeLayer |
class | ReshapeLayer |
class | ResizeLayer |
Resize input 4-dimensional blob by nearest neighbor or bilinear strategy. More... | |
class | RNNLayer |
Classical recurrent layer. More... | |
class | RoundLayer |
class | ScaleLayer |
class | ScaleLayerInt8 |
class | SegmentationModel |
This class represents high-level API for segmentation models. More... | |
class | SeluLayer |
class | ShiftLayer |
class | ShiftLayerInt8 |
class | ShuffleChannelLayer |
class | SigmoidLayer |
class | SinhLayer |
class | SinLayer |
class | SliceLayer |
class | SoftmaxLayer |
class | SoftmaxLayerInt8 |
class | SoftplusLayer |
class | SoftsignLayer |
class | SplitLayer |
class | SqrtLayer |
class | SwishLayer |
class | TanHLayer |
class | TanLayer |
class | TextDetectionModel |
Base class for text detection networks. More... | |
class | TextDetectionModel_DB |
This class represents high-level API for text detection DL networks compatible with DB model. More... | |
class | TextDetectionModel_EAST |
This class represents high-level API for text detection DL networks compatible with EAST model. More... | |
class | TextRecognitionModel |
This class represents high-level API for text recognition networks. More... | |
class | ThresholdedReluLayer |
Typedefs | |
typedef std::map< std::string, std::vector< LayerFactory::Constructor > > | LayerFactory_Impl |
typedef std::vector< int > | MatShape |
Enumerations | |
enum | Backend { DNN_BACKEND_DEFAULT = 0, DNN_BACKEND_HALIDE, DNN_BACKEND_INFERENCE_ENGINE, DNN_BACKEND_OPENCV, DNN_BACKEND_VKCOM, DNN_BACKEND_CUDA, DNN_BACKEND_WEBNN } |
Enum of computation backends supported by layers. More... | |
enum | SoftNMSMethod { SoftNMSMethod::SOFTNMS_LINEAR = 1, SoftNMSMethod::SOFTNMS_GAUSSIAN = 2 } |
Enum of Soft NMS methods. More... | |
enum | Target { DNN_TARGET_CPU = 0, DNN_TARGET_OPENCL, DNN_TARGET_OPENCL_FP16, DNN_TARGET_MYRIAD, DNN_TARGET_VULKAN, DNN_TARGET_FPGA, DNN_TARGET_CUDA, DNN_TARGET_CUDA_FP16, DNN_TARGET_HDDL } |
Enum of target devices for computations. More... | |
Functions | |
Mat | blobFromImage (InputArray image, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F) |
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. More... | |
void | blobFromImage (InputArray image, OutputArray blob, double scalefactor=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F) |
Creates 4-dimensional blob from image. More... | |
Mat | blobFromImages (InputArrayOfArrays images, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F) |
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. More... | |
void | blobFromImages (InputArrayOfArrays images, OutputArray blob, double scalefactor=1.0, Size size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false, int ddepth=CV_32F) |
Creates 4-dimensional blob from series of images. More... | |
static MatShape | concat (const MatShape &a, const MatShape &b) |
void | enableModelDiagnostics (bool isDiagnosticsMode) |
Enables detailed logging of the DNN model loading with CV DNN API. More... | |
std::vector< std::pair< Backend, Target > > | getAvailableBackends () |
std::vector< Target > | getAvailableTargets (dnn::Backend be) |
cv::String | getInferenceEngineBackendType () |
Returns Inference Engine internal backend API. More... | |
cv::String | getInferenceEngineCPUType () |
Returns Inference Engine CPU type. More... | |
cv::String | getInferenceEngineVPUType () |
Returns Inference Engine VPU type. More... | |
LayerFactory_Impl & | getLayerFactoryImpl () |
Mutex & | getLayerFactoryMutex () |
Get the mutex guarding LayerFactory_Impl, see getLayerFactoryImpl() function. More... | |
static Mat | getPlane (const Mat &m, int n, int cn) |
void | imagesFromBlob (const cv::Mat &blob_, OutputArrayOfArrays images_) |
Parse a 4D blob and output the images it contains as 2D arrays through a simpler data structure (std::vector<cv::Mat>). More... | |
static bool | isAllOnes (const MatShape &inputShape, int startPos, int endPos) |
void | NMSBoxes (const std::vector< Rect > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0) |
Performs non maximum suppression given boxes and corresponding scores. More... | |
void | NMSBoxes (const std::vector< Rect2d > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0) |
void | NMSBoxes (const std::vector< RotatedRect > &bboxes, const std::vector< float > &scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, const float eta=1.f, const int top_k=0) |
static int | normalize_axis (int axis, int dims) |
Converts axis from [-dims; dims) (similar to Python's slice notation) to [0; dims) range. More... | |
static int | normalize_axis (int axis, const MatShape &shape) |
static Range | normalize_axis_range (const Range &r, int axisSize) |
static std::ostream & | operator<< (std::ostream &out, const MatShape &shape) |
static void | print (const MatShape &shape, const String &name="") |
Net | readNet (const String &model, const String &config="", const String &framework="") |
Read deep learning network represented in one of the supported formats. More... | |
Net | readNet (const String &framework, const std::vector< uchar > &bufferModel, const std::vector< uchar > &bufferConfig=std::vector< uchar >()) |
Read deep learning network represented in one of the supported formats. More... | |
Net | readNetFromCaffe (const String &prototxt, const String &caffeModel=String()) |
Reads a network model stored in Caffe framework's format. More... | |
Net | readNetFromCaffe (const std::vector< uchar > &bufferProto, const std::vector< uchar > &bufferModel=std::vector< uchar >()) |
Reads a network model stored in Caffe model in memory. More... | |
Net | readNetFromCaffe (const char *bufferProto, size_t lenProto, const char *bufferModel=NULL, size_t lenModel=0) |
Reads a network model stored in Caffe model in memory. More... | |
Net | readNetFromDarknet (const String &cfgFile, const String &darknetModel=String()) |
Reads a network model stored in Darknet model files. More... | |
Net | readNetFromDarknet (const std::vector< uchar > &bufferCfg, const std::vector< uchar > &bufferModel=std::vector< uchar >()) |
Reads a network model stored in Darknet model files. More... | |
Net | readNetFromDarknet (const char *bufferCfg, size_t lenCfg, const char *bufferModel=NULL, size_t lenModel=0) |
Reads a network model stored in Darknet model files. More... | |
Net | readNetFromModelOptimizer (const String &xml, const String &bin) |
Load a network from Intel's Model Optimizer intermediate representation. More... | |
Net | readNetFromModelOptimizer (const std::vector< uchar > &bufferModelConfig, const std::vector< uchar > &bufferWeights) |
Load a network from Intel's Model Optimizer intermediate representation. More... | |
Net | readNetFromModelOptimizer (const uchar *bufferModelConfigPtr, size_t bufferModelConfigSize, const uchar *bufferWeightsPtr, size_t bufferWeightsSize) |
Load a network from Intel's Model Optimizer intermediate representation. More... | |
Net | readNetFromONNX (const String &onnxFile) |
Reads a network model ONNX. More... | |
Net | readNetFromONNX (const char *buffer, size_t sizeBuffer) |
Reads a network model from ONNX in-memory buffer. More... | |
Net | readNetFromONNX (const std::vector< uchar > &buffer) |
Reads a network model from ONNX in-memory buffer. More... | |
Net | readNetFromTensorflow (const String &model, const String &config=String()) |
Reads a network model stored in TensorFlow framework's format. More... | |
Net | readNetFromTensorflow (const std::vector< uchar > &bufferModel, const std::vector< uchar > &bufferConfig=std::vector< uchar >()) |
Reads a network model stored in TensorFlow framework's format. More... | |
Net | readNetFromTensorflow (const char *bufferModel, size_t lenModel, const char *bufferConfig=NULL, size_t lenConfig=0) |
Reads a network model stored in TensorFlow framework's format. More... | |
Net | readNetFromTorch (const String &model, bool isBinary=true, bool evaluate=true) |
Reads a network model stored in Torch7 framework's format. More... | |
Mat | readTensorFromONNX (const String &path) |
Creates blob from .pb file. More... | |
Mat | readTorchBlob (const String &filename, bool isBinary=true) |
Loads blob which was serialized as torch.Tensor object of Torch7 framework. More... | |
void | releaseHDDLPlugin () |
Release a HDDL plugin. More... | |
void | resetMyriadDevice () |
Release a Myriad device (binded by OpenCV). More... | |
cv::String | setInferenceEngineBackendType (const cv::String &newBackendType) |
Specify Inference Engine internal backend API. More... | |
static MatShape | shape (const int *dims, const int n) |
static MatShape | shape (const Mat &mat) |
static MatShape | shape (const MatSize &sz) |
static MatShape | shape (const UMat &mat) |
static MatShape | shape (int a0, int a1=-1, int a2=-1, int a3=-1) |
void | shrinkCaffeModel (const String &src, const String &dst, const std::vector< String > &layersTypes=std::vector< String >()) |
Convert all weights of Caffe network to half precision floating point. More... | |
void | skipModelImport (bool skip) |
Skip model import after diagnostic run in readNet() functions. More... | |
static Mat | slice (const Mat &m, const _Range &r0) |
static Mat | slice (const Mat &m, const _Range &r0, const _Range &r1) |
static Mat | slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2) |
static Mat | slice (const Mat &m, const _Range &r0, const _Range &r1, const _Range &r2, const _Range &r3) |
void | softNMSBoxes (const std::vector< Rect > &bboxes, const std::vector< float > &scores, std::vector< float > &updated_scores, const float score_threshold, const float nms_threshold, std::vector< int > &indices, size_t top_k=0, const float sigma=0.5, SoftNMSMethod method=SoftNMSMethod::SOFTNMS_GAUSSIAN) |
Performs soft non maximum suppression given boxes and corresponding scores. Reference: https://arxiv.org/abs/1704.04503. More... | |
static std::string | toString (const MatShape &shape, const String &name="") |
static int | total (const MatShape &shape, int start=-1, int end=-1) |
void | writeTextGraph (const String &model, const String &output) |
Create a text representation for a binary network stored in protocol buffer format. More... | |
cv::String cv::dnn::getInferenceEngineBackendType | ( | ) |
Returns Inference Engine internal backend API.
See values of CV_DNN_BACKEND_INFERENCE_ENGINE_*
macros.
Default value is controlled through OPENCV_DNN_BACKEND_INFERENCE_ENGINE_TYPE
runtime parameter (environment variable).
cv::String cv::dnn::getInferenceEngineCPUType | ( | ) |
Returns Inference Engine CPU type.
Specify OpenVINO plugin: CPU or ARM.
cv::String cv::dnn::getInferenceEngineVPUType | ( | ) |
Returns Inference Engine VPU type.
See values of CV_DNN_INFERENCE_ENGINE_VPU_TYPE_*
macros.
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Converts axis from [-dims; dims)
(similar to Python's slice notation) to [0; dims)
range.
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void cv::dnn::releaseHDDLPlugin | ( | ) |
Release a HDDL plugin.
void cv::dnn::resetMyriadDevice | ( | ) |
Release a Myriad device (binded by OpenCV).
Single Myriad device cannot be shared across multiple processes which uses Inference Engine's Myriad plugin.
cv::String cv::dnn::setInferenceEngineBackendType | ( | const cv::String & | newBackendType | ) |
Specify Inference Engine internal backend API.
See values of CV_DNN_BACKEND_INFERENCE_ENGINE_*
macros.
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void cv::dnn::skipModelImport | ( | bool | skip | ) |
Skip model import after diagnostic run in readNet() functions.
[in] | skip | Indicates whether to skip the import. |
This is an internal OpenCV function not intended for users.
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