SB SDK 1.11
Data Structures
Here are the data structures with brief descriptions:
[detail level 12]
 Nsb_csSB Namespace
 NTutorial11_CheckLicenseConfiguration
 NTutorial12_DeepCortexDetect
 NTutorial14_DeepSurfaceDetect
 NTutorial1_InitLibrary
 NTutorial3_RetinaDetect
 NTutorial7_RetinaMultiProject
 NTutorial9_SurfaceDetect
 Cretina_svl_user_data
 Csb_svl_user_data
 Csb_t_bgraDefines the color in the format BGRA
 Csb_t_blobDefines a blob
 Csb_t_blob_parDefines the parameters for blob analysis
 Csb_t_blobsDefines a blobs list
 Csb_t_blobs_infoDefines the information about the blob analysis
 Csb_t_device_infoInformations about a computing device
 Csb_t_devices_infoList of computing devices available on the machine
 Csb_t_devices_parProperty of computational devices
 Csb_t_fileDefines the single file
 Csb_t_folderDefines the list of the file in a folder
 Csb_t_imageDefines an image
 Csb_t_image_info_detailImage information details structure
 Csb_t_image_info_detailsArray of the image information details structure
 Csb_t_infoGeneral information about sb library and computing devices like CPU and GPUs
 Csb_t_licenseDefines the license and its properties
 Csb_t_license_configurationDefines the configurations of the license
 Csb_t_license_moduleDefines all the attributes and properties of a license module
 Csb_t_lut_pointStruct that defines the coordinates of a point of a lut
 Csb_t_memory_infoMemory information
 Csb_t_ocr_resResults of OCR analysis
 Csb_t_parProject parameters
 Csb_t_par_changes_infoInformation on what sb_project_set_par and sb_image_info_apply_par_changes do when they apply the new parameters
 Csb_t_par_levelLevel parameters
 Csb_t_par_levelsLevels parameter array
 Csb_t_par_modelParameters of a model
 Csb_t_par_model_lutInformation about mapping between old and new models and levels in the sb_t_par structure
 Csb_t_par_modelsArray of models parameters
 Csb_t_par_perturbationDescribes the perturbation of a sample
 Csb_t_par_perturbationsList of the perturbations of a sample
 Csb_t_par_slShallow Learning modules parameters
 Csb_t_pointRepresents an ordered pair of integer x and y coordinates that defines a point in a two-dimensional plane
 Csb_t_project_infoProject info structure
 Csb_t_projects_infoArray of the projects info
 Csb_t_rangeRepresents an ordered pair of integer minimum and maximum values that defines a range
 Csb_t_range_fltRepresents an ordered pair of float minimum and maximum values that defines a range
 Csb_t_rectDefines the position and size of a rectangle in a two-dimensional plane
 Csb_t_resResults of detection
 Csb_t_res_modelDefines the results of a model
 Csb_t_res_modelsDefines the results of the models
 Csb_t_rgbaDefines the color in the format RGBA
 Csb_t_rleDefines a RLE
 Csb_t_rle_segDefine a RLE segment
 Csb_t_roiDefines a roi
 Csb_t_sampleSample of an image
 Csb_t_sample_weights_imageImage of weights of the sample
 Csb_t_samplesSamples of an image
 Csb_t_sizeRepresents an ordered pair of integer x and y length that defines a rectangle in a two-dimensional plane
 Csb_t_size_fltRepresents an ordered pair of float x and y length that defines a rectangle in a two-dimensional plane
 Csb_t_solution_infoSolution info structure
 Csb_t_statStatistics of the elaborations done with the function sb_project_detection
 Csb_t_stat_modelStatistics of a model
 Csb_t_stat_modelsStatistics of a model
 Csb_t_surface_resDefines the result of the Surface analysis
 Csb_t_svl_dl_parSVL parameters to configure the Deep Learning training
 Csb_t_svl_dl_par_networkDeep Learning modules parameters
 Csb_t_svl_dl_par_perturbationDescribes the perturbation of the image / defect
 Csb_t_svl_errContains information regarding the error of the SVL
 Csb_t_svl_parSVL parameters
 Csb_t_svl_pre_elaborationContains the results of the image pre-processing
 Csb_t_svl_resDefines the results of SVL
 Csb_t_svl_res_epochResults of a training epoch
 Csb_t_svl_res_epochsResults of the training epochs
 Csb_t_svl_res_imageDefines the results of the elaboration of the SVL of an image
 Csb_t_svl_res_imagesDefines the results of the elaboration of the SVL images
 Csb_t_svl_res_levelResults of the SVL of a level per model
 Csb_t_svl_res_levelsResults of the SVL of a levels processed
 Csb_t_svl_res_modelResults of the SVL of a specific model
 Csb_t_svl_res_modelsResults of the SVL of a models processed
 Csb_t_svl_sl_parSVL parameters that configure the Shallow Learning training
 Csb_t_versionDefines the version