Image Model

class ImageModel : public ModelBase

Subclassed by AnomalyModel, ClassificationModel, DetectionModel, KeypointDetectionModel, MaskRCNNModel, SegmentationModel

Public Functions

ImageModel(const std::string &modelFile, const std::string &resize_type, bool useAutoResize, const std::string &layout = "")

Constructor

Parameters:

• modelFile – name of model to load

• useAutoResize – - if true, image is resized by openvino

• layout – - model input layout

ImageModel(std::shared_ptr<ov::Model> &model, const ov::AnyMap &configuration)

ImageModel(std::shared_ptr<InferenceAdapter> &adapter, const ov::AnyMap &configuration = {})

virtual std::shared_ptr<InternalModelData> preprocess(const InputData &inputData, InferenceInput &input) override

std::shared_ptr<ov::Model> embedProcessing(std::shared_ptr<ov::Model> &model, const std::string &inputName, const ov::Layout&, RESIZE_MODE resize_mode, const cv::InterpolationFlags interpolationMode, const ov::Shape &targetShape, uint8_t pad_value, bool brg2rgb, const std::vector<float> &mean, const std::vector<float> &scale, const std::type_info &dtype = typeid(int))

virtual void inferAsync(const ImageInputData &inputData, const ov::AnyMap &callback_args = {})

std::unique_ptr<ResultBase> inferImage(const ImageInputData &inputData)

std::vector<std::unique_ptr<ResultBase>> inferBatchImage(const std::vector<ImageInputData> &inputData)

ModelBase(const std::string &modelFile, const std::string &layout = "")

ModelBase(std::shared_ptr<InferenceAdapter> &adapter, const ov::AnyMap &configuration = {})

ModelBase(std::shared_ptr<ov::Model> &model, const ov::AnyMap &configuration)

Public Static Functions

static std::vector<std::string> loadLabels(const std::string &labelFilename)