This inheritance list is sorted roughly, but not completely, alphabetically:

[detail level 12]

CBpFileHandling	Class to retrieve path of stereo set files for reading and for output
▼CBpImage< T >	Class to define images that are used in bp processing
CDisparityMap< float >
CDisparityMap< T >	Child class of BpImage to define disparity map image that is output from bp processing
CBpLevel< T >	Class to store and retrieve properties of a bp processing level including a data type specified as a class template parameter
Cbeliefprop::BpLevelProperties	POD struct to store bp level data. Struct can be passed to global CUDAs kernel so needs to take restrictions of what's allowed for passing data from the host to a CUDA kernel into account
Cbeliefprop::BpOnDevice< T, DISP_VALS, ACCELERATION >	Structure with pointers to objects containing functions for smoothing images, processing bp, and memory management on target device using specified acceleration
Cbeliefprop::BpRunOutput	Structure with output disparity map, runtime, and other evaluation data
Cbeliefprop::BpSettings	Structure to store the belief propagation settings including the number of levels and iterations
Cbeliefprop::BpStereoSet	Structure with stereo set name, disparity count, and scale factor for output disparity map
Cbp_single_thread_imp::Convolve
CCPUThreadsPinnedToSocket	Class to adjust and retrieve settings corresponding to CPU threads pinned to socket
CDetailedTimings< T >	Class to store timings of one or more segments taken during the run(s) of an implementation or across multiple implementations. Index for timing segments must be enum type
CDisparityMapEvaluation	Class to store disparity map evaluation results. Specifically comparison between two disparity maps such as output disparity map from bp processing and ground truth disparity map
Cbeliefprop::DisparityMapEvaluationParams	Struct to store parameters for evaluation of disparity map from stereo processing
CEvalAcrossRunsData	Structure to store data with mappings for evaluating results across runs as well as speedup headers in order
CEvaluateAcrossRuns	Class with operator function to evaluate implementation runs across multiple architectures. Outputs a file with speedup data on every run with the runs ordered from fastest to slowest
▼CEvaluateImpResults	Class with operator function to evaluate implementations of the same algorithm across different data types and acceleration methods
CEvaluateImpResultsBp	Child class of EvaluateImpResults that defines member functions for belief propagation evaluation which override pure virtual functions in parent class
Cbp_single_thread_imp::FilterImage
Cbp_single_thread_imp::image< T >
CInputSignature	Class defines input signature for evaluation run that contains evaluation set number, data type, and whether or not to use templated loop iteration count
▼CMemoryManagement< T >	Class for memory management with functions defined for standard memory allocation using CPU. Class functions can be overridden to support other computation devices such as GPU
CMemoryManagementCUDA< T >	Child class of MemoryManagement with overriden member functions to manage memory on CUDA device including transferring data between host and CUDA device
Crun_eval::OutFileInfo
▼CParallelParams	Abstract class for holding and processing parallelization parameters. Child class(es) specific to implementation(s) must be defined
CParallelParamsBp	Child class of ParallelParams to store and process parallelization parameters to use in each BP kernel at each level
Cbp_single_thread_imp::pnm_error
▼CProcessBp< T, DISP_VALS, ACCELERATION >	Abstract class to run belief propagation on target device. Some of the class functions need to be overridden for processing on target device
CProcessBpCUDA< T, DISP_VALS, ACCELERATION >	Child class of ProcessBp that define functions used in processing bp in the CUDA implementation
CProcessBpOptimizedCPU< T, DISP_VALS, ACCELERATION >	Child class of ProcessBp that defines functions used in processing bp in the optimized CPU implementation
Cbp_single_thread_imp::rgb
▼CRunBpOnStereoSet< T, DISP_VALS, ACCELERATION >	Abstract class to set up and run belief propagation on target device using specified acceleration
CRunBpOnStereoSetCUDA< T, DISP_VALS, ACCELERATION >	Child class of RunBpOnStereoSet to run CUDA implementation of belief propagation on a given stereo set as defined by reference and test image file paths
CRunBpOnStereoSetOptimizedCPU< T, DISP_VALS, ACCELERATION >	Child class of RunBpOnStereoSet to run optimized CPU implementation of belief propagation on a given stereo set as defined by reference and test image file paths
CRunBpOnStereoSetSingleThreadCPU< T, DISP_VALS, ACCELERATION >	Child class of RunBpOnStereoSet to run single-threaded CPU implementation of belief propagation on a given stereo set as defined by reference and test image file paths
CRunData	Class to store headers with data corresponding to current program run and evaluation
▼CRunImpMultInputs	Base class for running and evaluating multiple runs of an implementation that may be optimized on CPU or GPU
CRunImpMultInputsBp	Child class of RunImpMultInputs to run specified belief propagation implementation on a number of inputs
CRunImpMultTypesAccels	Class to run and evaluate implementation(s) of an algorithm using multiple settings including different datatype, inputs, and acceleration methods
▼CRunImpOnInput< T, OPT_IMP_ACCEL, NUM_INPUT >	Virtual class to run and evaluate implementation on a input specified by index number
CRunImpOnInputBp< T, OPT_IMP_ACCEL, NUM_INPUT >	Child class of RunImpOnInput to run and evaluate belief propagation implementation on a specified input
Crun_environment::RunImpSettings	Structure that stores settings for current implementation run
CRunResultsSpeedups	Class to load and store run results data including speedups from evaluation
▼CSmoothImage	Class for smoothing the images before running BP. Smoothing image always uses float data type
CSmoothImageCPU	Child class of SmoothImage for smoothing images in the optimized CPU implementation
CSmoothImageCUDA	Child class of SmoothImage for smoothing images in the CUDA implementation