OpenCV  4.1.2-dev
Open Source Computer Vision
cv::dnn::ClassificationModel Member List

This is the complete list of members for cv::dnn::ClassificationModel, including all inherited members.

addLayer(const String &name, const String &type, LayerParams &params)cv::dnn::Net
addLayerToPrev(const String &name, const String &type, LayerParams &params)cv::dnn::Net
ClassificationModel(const String &model, const String &config="")cv::dnn::ClassificationModel
ClassificationModel(const Net &network)cv::dnn::ClassificationModel
classify(InputArray frame)cv::dnn::ClassificationModel
classify(InputArray frame, int &classId, float &conf)cv::dnn::ClassificationModel
connect(String outPin, String inpPin)cv::dnn::Net
connect(int outLayerId, int outNum, int inpLayerId, int inpNum)cv::dnn::Net
dump()cv::dnn::Net
dumpToFile(const String &path)cv::dnn::Net
empty() constcv::dnn::Net
enableFusion(bool fusion)cv::dnn::Net
forward(const String &outputName=String())cv::dnn::Net
forward(OutputArrayOfArrays outputBlobs, const String &outputName=String())cv::dnn::Net
forward(OutputArrayOfArrays outputBlobs, const std::vector< String > &outBlobNames)cv::dnn::Net
forward(std::vector< std::vector< Mat > > &outputBlobs, const std::vector< String > &outBlobNames)cv::dnn::Net
forwardAsync(const String &outputName=String())cv::dnn::Net
getFLOPS(const std::vector< MatShape > &netInputShapes) constcv::dnn::Net
getFLOPS(const MatShape &netInputShape) constcv::dnn::Net
getFLOPS(const int layerId, const std::vector< MatShape > &netInputShapes) constcv::dnn::Net
getFLOPS(const int layerId, const MatShape &netInputShape) constcv::dnn::Net
getLayer(LayerId layerId)cv::dnn::Net
getLayerId(const String &layer)cv::dnn::Net
getLayerInputs(LayerId layerId)cv::dnn::Net
getLayerNames() constcv::dnn::Net
getLayersCount(const String &layerType) constcv::dnn::Net
getLayerShapes(const MatShape &netInputShape, const int layerId, std::vector< MatShape > &inLayerShapes, std::vector< MatShape > &outLayerShapes) constcv::dnn::Net
getLayerShapes(const std::vector< MatShape > &netInputShapes, const int layerId, std::vector< MatShape > &inLayerShapes, std::vector< MatShape > &outLayerShapes) constcv::dnn::Net
getLayersShapes(const std::vector< MatShape > &netInputShapes, std::vector< int > &layersIds, std::vector< std::vector< MatShape > > &inLayersShapes, std::vector< std::vector< MatShape > > &outLayersShapes) constcv::dnn::Net
getLayersShapes(const MatShape &netInputShape, std::vector< int > &layersIds, std::vector< std::vector< MatShape > > &inLayersShapes, std::vector< std::vector< MatShape > > &outLayersShapes) constcv::dnn::Net
getLayerTypes(std::vector< String > &layersTypes) constcv::dnn::Net
getMemoryConsumption(const std::vector< MatShape > &netInputShapes, size_t &weights, size_t &blobs) constcv::dnn::Net
getMemoryConsumption(const MatShape &netInputShape, size_t &weights, size_t &blobs) constcv::dnn::Net
getMemoryConsumption(const int layerId, const std::vector< MatShape > &netInputShapes, size_t &weights, size_t &blobs) constcv::dnn::Net
getMemoryConsumption(const int layerId, const MatShape &netInputShape, size_t &weights, size_t &blobs) constcv::dnn::Net
getMemoryConsumption(const std::vector< MatShape > &netInputShapes, std::vector< int > &layerIds, std::vector< size_t > &weights, std::vector< size_t > &blobs) constcv::dnn::Net
getMemoryConsumption(const MatShape &netInputShape, std::vector< int > &layerIds, std::vector< size_t > &weights, std::vector< size_t > &blobs) constcv::dnn::Net
getParam(LayerId layer, int numParam=0)cv::dnn::Net
getPerfProfile(std::vector< double > &timings)cv::dnn::Net
getUnconnectedOutLayers() constcv::dnn::Net
getUnconnectedOutLayersNames() constcv::dnn::Net
implcv::dnn::Modelprotected
LayerId typedefcv::dnn::Net
Model()cv::dnn::Model
Model(const String &model, const String &config="")cv::dnn::Model
Model(const Net &network)cv::dnn::Model
Net()cv::dnn::Net
predict(InputArray frame, OutputArrayOfArrays outs)cv::dnn::Model
readFromModelOptimizer(const String &xml, const String &bin)cv::dnn::Netstatic
setHalideScheduler(const String &scheduler)cv::dnn::Net
setInput(InputArray blob, const String &name="", double scalefactor=1.0, const Scalar &mean=Scalar())cv::dnn::Net
setInputCrop(bool crop)cv::dnn::Model
setInputMean(const Scalar &mean)cv::dnn::Model
setInputParams(double scale=1.0, const Size &size=Size(), const Scalar &mean=Scalar(), bool swapRB=false, bool crop=false)cv::dnn::Model
setInputScale(double scale)cv::dnn::Model
setInputSize(const Size &size)cv::dnn::Model
setInputSize(int width, int height)cv::dnn::Model
setInputsNames(const std::vector< String > &inputBlobNames)cv::dnn::Net
setInputSwapRB(bool swapRB)cv::dnn::Model
setParam(LayerId layer, int numParam, const Mat &blob)cv::dnn::Net
setPreferableBackend(int backendId)cv::dnn::Net
setPreferableTarget(int targetId)cv::dnn::Net
~Net()cv::dnn::Net