  curfil | |
 utils | |
  Timer | Used to get seconds or milliseconds passed for profiling purposes |
| Average | A simple class used for averaging |
 Profile | Used to profile different stages of training and prediction |
| RandomTreeExport | Helper class to export a random tree or random forest to disk in compressed (gzip) JSON format |
| Result | Class that stores the results of a hyperopt run |
| HyperoptClient | Client that does a hyperopt parameter search |
| RGBColor | A tuple of three 8-bit uints that represent a RGB color value |
| Depth | Wrapper class that represent a depth value as it occurs in RGB-D images |
| RGBDImage | An RGB-D image that contains four channels for the RGB color and the depth |
| LabelImage | A labelling that usually belongs to a RGBImage |
| LabeledRGBDImage | A tuple of a RGBD image and an according labeling |
| RandomTreeImport | Helper class to import a random tree or random forest from disk in compressed (gzip) JSON format |
| ConfusionMatrix | Helper class to maintain a n×n confusion matrix |
| RandomForestImage | A random forest for RGB-D images |
| SplitFunction | Class used to get the splitting score for a given feature and threshold |
| TrainingConfiguration | Parameters used for training, most of which are provided by the user |
| RandomTree | A sub-tree with histograms and pointers to the parent and children |
| Sampler | A uniform distribution sampler |
| ReservoirSampler | Stores samples (images or pixel instances), if max size is reached, a sample replaces another chosen at random |
| RandomSource | Used to get a uniform sampler after incrementing the seed |
| RandomTreeTrain | Class that does the actual training of a tree |
| XY | A simple 2D tuple |
| PixelInstance | Represents a single-pixel sample in a RGB-D image |
| ImageFeatureFunction | Parametrized visual image feature |
| ImageFeaturesAndThresholds | Helper class to store a list of features and a list of threshold per feature in a compact mannersuch that it can be transferred between CPU and GPU |
| Samples | Helper class to store a list of pixel instances in a compact mannersuch that it can be transferred between CPU and GPU |
| ImageFeatureEvaluation | Helper class for the four phases in the cost-intensive best-split evaluation during random forest training |
| RandomTreeImage | A random tree in a random forest, for RGB-D images |
| TreeNodes | Helper class to map random forest data to texture cache on GPU |
| DeviceCache | Abstract base class that implements a simple LRU cache on GPU |
| ImageCache | A simple LRU cache of RGB-D images on GPU |
| TreeCache | A simple LRU cache of trees on GPU |
| TreeNodeData | Helper class for the unit test |
| InformationGainScore | Information Gain calculation using Shannon entropy of the parent and child nodes |
| NormalizedInformationGainScore | Information gain normalized by the sum of the classification and split entropies see formula (11) in [Wehenkel1991] and appendix A in [Geurts2006] |
 cuv | |
 allocator | |
| default_allocator | Allocator allows allocation, deallocation and copying depending on memory_space_type |
| cuda_allocator | Allocator that uses cudaMallocHost for allocations in host_memory_space |
| pooled_cuda_allocator | Allocator that naively pools device and host memory |
| column_major | Tag for column major matrices |
| row_major | Tag for row major matrices |
| linear_memory_tag | Tag for linear memory |
| pitched_memory_tag | Tag for pitched memory |
| memory | Simply keeps a pointer and deallocates it when destroyed |
| linear_memory | Contiguous memory |
| pitched_memory | 2D non-contiguous ("pitched") memory |
| FalseType | Defines "False" |
| TrueType | Defines "True" |
| IsSame | Checks whether two types are equal |
| IsSame< T, T > | |
| IsDifferent | Checks whether two types are different |
| IsDifferent< T, T > | |
| unconst | Remove "const" from a type |
| unconst< const T > | |
| If | Switch result depending on Condition |
| If< false, Then, Else > | |
| EnableIfC | Enable-if controlled creation of SFINAE conditions |
| EnableIfC< false, T > | |
| EnableIf | |
| DisableIf | |
| ndarray_info | Infos about shape and stride on host and in the ndarray data space |
| ndarray | N-dimensional array on GPU or CPU |
| ndarray_view | Primarily used as result of ndarray::operator[] |
| switch_value_type | Create a ndarray type with the same template parameters, but with switched value type |
| switch_memory_layout_type | Create a ndarray type with the same template parameters, but with switched memory_layout_type |
| switch_memory_space_type | Create a ndarray type with the same template parameters, but with switched memory_space_type |
| reference | This objects acts like a reference to the object stored at the wrapped pointer |
| host_memory_space | Tag for host memory |
| dev_memory_space | Tag for device memory |
1.8.1.2
