Man pages for neuroimaginador/dl4ni
Deep Learning Flows for Neuroimaging
| add_attribute | Add an Attribute to a Scheme |
| add_inputs | FUNCTION_TITLE |
| add_layers | Add Layers to a Previous Tensor |
| add_process | FUNCTION_TITLE |
| add_trainable_model | FUNCTION_TITLE |
| analyze_input | FUNCTION_TITLE |
| analyze_output | FUNCTION_TITLE |
| bce_dice_loss | Binary Cross Entropy and Dice Loss |
| block_categorical | Categorical Block |
| block_clf | Continuous Learning of Features Block |
| block_double | Block Double |
| block_half | Block Half |
| block_multivalued | Multivalued Block |
| block_paths | Create Independent Paths |
| block_regression | FUNCTION_TITLE |
| block_resnet | ResNet Block |
| categorical | Categorical Block |
| clf | Continuous Learning of Features Block |
| clone_flow | FUNCTION_TITLE |
| compute_batch_size | Compute Optimal Batch Size |
| concatenate_layers | FUNCTION_TITLE |
| conv3d | Convolutional Layer |
| convert_to_bytes | Convert a Character String to Bytes |
| create_flow | FUNCTION_TITLE |
| create_generator | FUNCTION_TITLE |
| create_generator_from_config | FUNCTION_TITLE |
| create_inference_function_from_config | Generic Inference Function for a Model Configuration |
| create_model_from_config | Builds a DLmodel from a Given Configuration |
| create_scheme | Create Model Scheme |
| create_vol_layers | Create Volume Layers Definition from Pattern |
| decode | Decode Inputs using AutoEncoder |
| define_config | Configuration Definition |
| define_last_layer | Define the Last Layer of a Model according to Problem Type |
| dense | Dense Layer |
| dice_coef | Dice Coefficient |
| dice_loss | Dice Loss |
| DLflow | DLflow Class |
| DLflow.add | Add an Item to a Flow |
| DLflow.clone | Clone Flow |
| DLflow.execute | Execute a Flow |
| DLflow.get_inputs | Flow Inputs |
| DLflow.get_model | Models from a Flow |
| DLflow.get_outputs | Flow Outputs |
| DLflow.graph | Flow Graph |
| DLflow.initialize | Flow Creation |
| DLflow.load | Load a Flow |
| DLflow.name | Name of a Flow |
| DLflow.plot | Plot a Flow |
| DLflow.replace | Replace Part of a Flow |
| DLflow.reset | Reset Outputs of a Flow |
| DLflow.run | Execute a Flow |
| DLflow.save | Save a Flow |
| DLflow.subset | Flow Subsetting |
| DLflow.train | Train Part of a Flow |
| DLmodel | DLmodel Class |
| DLmodel.add_to_history | FUNCTION_TITLE |
| DLmodel.check_memory | FUNCTION_TITLE |
| DLmodel.clone | FUNCTION_TITLE |
| DLmodel.errors | FUNCTION_TITLE |
| DLmodel.fit | FUNCTION_TITLE |
| DLmodel.get_config | FUNCTION_TITLE |
| DLmodel.get_decoder | FUNCTION_TITLE |
| DLmodel.get_encoder | FUNCTION_TITLE |
| DLmodel.get_history | FUNCTION_TITLE |
| DLmodel.get_loss | FUNCTION_TITLE |
| DLmodel.get_model | FUNCTION_TITLE |
| DLmodel.get_width | FUNCTION_TITLE |
| DLmodel.graph | FUNCTION_TITLE |
| DLmodel.infer | FUNCTION_TITLE |
| DLmodel.initialize | FUNCTION_TITLE |
| DLmodel.load | FUNCTION_TITLE |
| DLmodel.log | FUNCTION_TITLE |
| DLmodel.plot | FUNCTION_TITLE |
| DLmodel.plot_history | FUNCTION_TITLE |
| DLmodel.print_log | FUNCTION_TITLE |
| DLmodel.render_history | FUNCTION_TITLE |
| DLmodel.reset | FUNCTION_TITLE |
| DLmodel.reset_history | FUNCTION_TITLE |
| DLmodel.save | FUNCTION_TITLE |
| DLmodel.save_log | FUNCTION_TITLE |
| DLmodel.set_loss | FUNCTION_TITLE |
| DLmodel.set_width | FUNCTION_TITLE |
| DLmodel.summary | FUNCTION_TITLE |
| DLmodel.update | FUNCTION_TITLE |
| DLmodel.update_render | FUNCTION_TITLE |
| DLmodel.use_data | FUNCTION_TITLE |
| DLmodel.warnings | FUNCTION_TITLE |
| DLscheme | DLscheme Class |
| DLscheme.add | FUNCTION_TITLE |
| DLscheme.clone | FUNCTION_TITLE |
| DLscheme.from_list | FUNCTION_TITLE |
| DLscheme.from_model | FUNCTION_TITLE |
| DLscheme.initialize | FUNCTION_TITLE |
| DLscheme.instantiate | FUNCTION_TITLE |
| DLscheme.to_list | FUNCTION_TITLE |
| double | Doubling Convolutional Block |
| encode | Encode Inputs using AutoEncoder |
| eval_optimizer | Evaluate a Parsed Optimizer |
| execute_flow | FUNCTION_TITLE |
| fit_with_generator | Fit a Model using Generators |
| gaussian_kernel | FUNCTION_TITLE |
| get_activations | Get Activations in Intermediate Layer |
| get_dl4ni_config | Get Default Configuration |
| get_problem_info | FUNCTION_TITLE |
| graph_from_model | Create Graph from a Model |
| half | Halving Convolutional Block |
| layer_shape | Layer Output Shape |
| layer_units | Layer Output Units |
| load_flow | FUNCTION_TITLE |
| load_keras | Load KERAS |
| load_model | Load DLmodel |
| map_ids | FUNCTION_TITLE |
| model_size | Compute Model Total Size |
| multivalued | Multivalued Block |
| normalize_layers | Normalize Layers |
| object_shape | Object Output Shape |
| ortho_plot | Orthographic Plot |
| parse_optimizer | Parse Keras Optimizer |
| plot_flow | FUNCTION_TITLE |
| plot_graph | FUNCTION_TITLE |
| prepare_files_for_inference | Read Multiple Files |
| read_nifti_to_array | Read Nifti File |
| regression | Regression Block |
| reset_flow | FUNCTION_TITLE |
| reset_outputs | FUNCTION_TITLE |
| resnet | ResNet Block |
| save_flow | FUNCTION_TITLE |
| save_model | Save DLmodel |
| scale_max | FUNCTION_TITLE |
| scale_max_masked | FUNCTION_TITLE |
| scale_meanmax | FUNCTION_TITLE |
| scale_meanmax_masked | FUNCTION_TITLE |
| scale_z | FUNCTION_TITLE |
| scale_z_masked | FUNCTION_TITLE |
| segnet | imlab-uiip/keras-segnet |
| set_trainability | Set Trainability of Layers in Model |
| smooth_by_gaussian_kernel | FUNCTION_TITLE |
| split_train_test_sets | Split Problem into Train and Test Sets |
| subset_flow | FUNCTION_TITLE |
| subset_problem | FUNCTION_TITLE |
| to_categorical_volume | Split a Label Volume in One-hot Encoding |
| train_output | FUNCTION_TITLE |
| transform_coords | Tranform Coords Between Images |
| unet | U-Net Block |
| which_to_compute | FUNCTION_TITLE |
