SYMBOL INDEX (169 symbols across 24 files)

FILE: configs/Config_unet.py
  function get_config (line 23) | def get_config():

FILE: configs/Config_unet_spleen.py
  function get_config (line 23) | def get_config():

FILE: datasets/data_loader.py
  class WrappedDataset (line 22) | class WrappedDataset(Dataset):
    method __init__ (line 23) | def __init__(self, dataset, transform):
    method __getitem__ (line 31) | def __getitem__(self, index):
    method __len__ (line 40) | def __len__(self):
  class MultiThreadedDataLoader (line 44) | class MultiThreadedDataLoader(object):
    method __init__ (line 45) | def __init__(self, data_loader, transform, num_processes, **kwargs):
    method get_worker_init_fn (line 57) | def get_worker_init_fn(self):
    method __iter__ (line 63) | def __iter__(self):
    method __next__ (line 68) | def __next__(self):
    method renew (line 73) | def renew(self):
    method restart (line 79) | def restart(self):
    method kill_iterator (line 83) | def kill_iterator(self):

FILE: datasets/example_dataset/create_splits.py
  function create_splits (line 25) | def create_splits(output_dir, image_dir):
  function splits_sanity_check (line 70) | def splits_sanity_check(path):

FILE: datasets/example_dataset/preprocessing.py
  function preprocess_data (line 29) | def preprocess_data(root_dir, y_shape=64, z_shape=64):
  function preprocess_single_file (line 74) | def preprocess_single_file(image_file):
  function postprocess_single_image (line 83) | def postprocess_single_image(image):

FILE: datasets/spleen/create_splits.py
  function create_splits (line 25) | def create_splits(output_dir, image_dir):

FILE: datasets/spleen/preprocessing.py
  function preprocess_data (line 28) | def preprocess_data(root_dir, y_shape=64, z_shape=64):
  function preprocess_single_file (line 68) | def preprocess_single_file(image_file):
  function postprocess_single_image (line 87) | def postprocess_single_image(image):

FILE: datasets/three_dim/NumpyDataLoader.py
  function load_dataset (line 29) | def load_dataset(base_dir, pattern='*.npy', keys=None):
  class NumpyDataSet (line 52) | class NumpyDataSet(object):
    method __init__ (line 56) | def __init__(self, base_dir, mode="train", batch_size=16, num_batches=...
    method __len__ (line 73) | def __len__(self):
    method __iter__ (line 76) | def __iter__(self):
    method __next__ (line 82) | def __next__(self):
  class NumpyDataLoader (line 86) | class NumpyDataLoader(SlimDataLoaderBase):
    method __init__ (line 87) | def __init__(self, base_dir, mode="train", batch_size=16, num_batches=...
    method reshuffle (line 112) | def reshuffle(self):
    method generate_train_batch (line 117) | def generate_train_batch(self):
    method __len__ (line 121) | def __len__(self):
    method __getitem__ (line 125) | def __getitem__(self, item):
    method get_data_from_array (line 150) | def get_data_from_array(self, open_array):

FILE: datasets/three_dim/data_augmentation.py
  function get_transforms (line 24) | def get_transforms(mode="train", target_size=128):

FILE: datasets/two_dim/NumpyDataLoader.py
  function load_dataset (line 29) | def load_dataset(base_dir, pattern='*.npy', slice_offset=5, keys=None):
  class NumpyDataSet (line 52) | class NumpyDataSet(object):
    method __init__ (line 56) | def __init__(self, base_dir, mode="train", batch_size=16, num_batches=...
    method __len__ (line 73) | def __len__(self):
    method __iter__ (line 76) | def __iter__(self):
    method __next__ (line 82) | def __next__(self):
  class NumpyDataLoader (line 86) | class NumpyDataLoader(SlimDataLoaderBase):
    method __init__ (line 87) | def __init__(self, base_dir, mode="train", batch_size=16, num_batches=...
    method reshuffle (line 112) | def reshuffle(self):
    method generate_train_batch (line 117) | def generate_train_batch(self):
    method __len__ (line 121) | def __len__(self):
    method __getitem__ (line 125) | def __getitem__(self, item):
    method get_data_from_array (line 150) | def get_data_from_array(self, open_array):

FILE: datasets/two_dim/data_augmentation.py
  function get_transforms (line 26) | def get_transforms(mode="train", target_size=128):

FILE: datasets/utils.py
  function download_dataset (line 25) | def download_dataset(dest_path, dataset, id=''):

FILE: evaluation/evaluator.py
  class Evaluator (line 15) | class Evaluator:
    method __init__ (line 45) | def __init__(self,
    method set_test (line 84) | def set_test(self, test):
    method set_reference (line 89) | def set_reference(self, reference):
    method set_labels (line 94) | def set_labels(self, labels):
    method construct_labels (line 110) | def construct_labels(self):
    method set_metrics (line 122) | def set_metrics(self, metrics):
    method add_metric (line 132) | def add_metric(self, metric):
    method evaluate (line 137) | def evaluate(self, test=None, reference=None, advanced=False, **metric...
    method to_dict (line 210) | def to_dict(self):
    method to_array (line 216) | def to_array(self):
    method to_pandas (line 237) | def to_pandas(self):
  class NiftiEvaluator (line 252) | class NiftiEvaluator(Evaluator):
    method __init__ (line 254) | def __init__(self, *args, **kwargs):
    method set_test (line 260) | def set_test(self, test):
    method set_reference (line 270) | def set_reference(self, reference):
    method evaluate (line 280) | def evaluate(self, test=None, reference=None, voxel_spacing=None, **me...
  function aggregate_scores (line 289) | def aggregate_scores(test_ref_pairs,
  function aggregate_scores_for_experiment (line 376) | def aggregate_scores_for_experiment(score_file,

FILE: evaluation/metrics.py
  function assert_shape (line 5) | def assert_shape(test, reference):
  class ConfusionMatrix (line 11) | class ConfusionMatrix:
    method __init__ (line 13) | def __init__(self, test=None, reference=None):
    method set_test (line 27) | def set_test(self, test):
    method set_reference (line 32) | def set_reference(self, reference):
    method reset (line 37) | def reset(self):
    method compute (line 49) | def compute(self):
    method get_matrix (line 66) | def get_matrix(self):
    method get_size (line 75) | def get_size(self):
    method get_existence (line 81) | def get_existence(self):
  function dice (line 91) | def dice(test=None, reference=None, confusion_matrix=None, nan_for_nonex...
  function jaccard (line 109) | def jaccard(test=None, reference=None, confusion_matrix=None, nan_for_no...
  function precision (line 127) | def precision(test=None, reference=None, confusion_matrix=None, nan_for_...
  function sensitivity (line 145) | def sensitivity(test=None, reference=None, confusion_matrix=None, nan_fo...
  function recall (line 163) | def recall(test=None, reference=None, confusion_matrix=None, nan_for_non...
  function specificity (line 169) | def specificity(test=None, reference=None, confusion_matrix=None, nan_fo...
  function accuracy (line 187) | def accuracy(test=None, reference=None, confusion_matrix=None, **kwargs):
  function fscore (line 198) | def fscore(test=None, reference=None, confusion_matrix=None, nan_for_non...
  function false_positive_rate (line 208) | def false_positive_rate(test=None, reference=None, confusion_matrix=None...
  function false_omission_rate (line 214) | def false_omission_rate(test=None, reference=None, confusion_matrix=None...
  function false_negative_rate (line 232) | def false_negative_rate(test=None, reference=None, confusion_matrix=None...
  function true_negative_rate (line 238) | def true_negative_rate(test=None, reference=None, confusion_matrix=None,...
  function false_discovery_rate (line 244) | def false_discovery_rate(test=None, reference=None, confusion_matrix=Non...
  function negative_predictive_value (line 250) | def negative_predictive_value(test=None, reference=None, confusion_matri...
  function total_positives_test (line 256) | def total_positives_test(test=None, reference=None, confusion_matrix=Non...
  function total_negatives_test (line 267) | def total_negatives_test(test=None, reference=None, confusion_matrix=Non...
  function total_positives_reference (line 278) | def total_positives_reference(test=None, reference=None, confusion_matri...
  function total_negatives_reference (line 289) | def total_negatives_reference(test=None, reference=None, confusion_matri...
  function hausdorff_distance (line 300) | def hausdorff_distance(test=None, reference=None, confusion_matrix=None,...
  function hausdorff_distance_95 (line 318) | def hausdorff_distance_95(test=None, reference=None, confusion_matrix=No...
  function avg_surface_distance (line 336) | def avg_surface_distance(test=None, reference=None, confusion_matrix=Non...
  function avg_surface_distance_symmetric (line 354) | def avg_surface_distance_symmetric(test=None, reference=None, confusion_...

FILE: experiments/UNetExperiment.py
  class UNetExperiment (line 34) | class UNetExperiment(PytorchExperiment):
    method setup (line 53) | def setup(self):
    method train (line 92) | def train(self, epoch):
    method validate (line 131) | def validate(self, epoch):
    method test (line 160) | def test(self):
    method segment_single_image (line 197) | def segment_single_image(self, data):

FILE: experiments/UNetExperiment3D.py
  class UNetExperiment3D (line 34) | class UNetExperiment3D(PytorchExperiment):
    method setup (line 53) | def setup(self):
    method train (line 92) | def train(self, epoch):
    method validate (line 126) | def validate(self, epoch):
    method test (line 156) | def test(self):

FILE: loss_functions/ND_Crossentropy.py
  class CrossentropyND (line 4) | class CrossentropyND(torch.nn.CrossEntropyLoss):
    method forward (line 8) | def forward(self, inp, target):

FILE: loss_functions/dice_loss.py
  function softmax_helper (line 8) | def softmax_helper(x):
  function get_tp_fp_fn (line 16) | def get_tp_fp_fn(net_output, gt, axes=None, mask=None):
  function sum_tensor (line 63) | def sum_tensor(inp, axes, keepdim=False):
  function mean_tensor (line 74) | def mean_tensor(inp, axes, keepdim=False):
  class SoftDiceLoss (line 85) | class SoftDiceLoss(nn.Module):
    method __init__ (line 86) | def __init__(self, smooth=1., apply_nonlin=None, batch_dice=False, do_...
    method forward (line 112) | def forward(self, x, y):
  function soft_dice_per_batch (line 140) | def soft_dice_per_batch(net_output, gt, smooth=1., smooth_in_nom=1., bac...
  function soft_dice_per_batch_2 (line 152) | def soft_dice_per_batch_2(net_output, gt, smooth=1., smooth_in_nom=1., b...
  function soft_dice (line 173) | def soft_dice(net_output, gt, smooth=1., smooth_in_nom=1.):
  class MultipleOutputLoss (line 181) | class MultipleOutputLoss(nn.Module):
    method __init__ (line 182) | def __init__(self, loss, weight_factors=None):
    method forward (line 192) | def forward(self, x, y):
  class DC_and_CE_loss (line 204) | class DC_and_CE_loss(nn.Module):
    method __init__ (line 205) | def __init__(self, soft_dice_kwargs, ce_kwargs, aggregate="sum"):
    method forward (line 211) | def forward(self, net_output, target):
  class DC_and_topk_loss (line 221) | class DC_and_topk_loss(nn.Module):
    method __init__ (line 222) | def __init__(self, soft_dice_kwargs, ce_kwargs, aggregate="sum"):
    method forward (line 228) | def forward(self, net_output, target):
  class CrossentropyWithLossMask (line 238) | class CrossentropyWithLossMask(nn.CrossEntropyLoss):
    method __init__ (line 239) | def __init__(self, k=None):
    method forward (line 247) | def forward(self, inp, target, loss_mask=None):

FILE: loss_functions/topk_loss.py
  class TopKLoss (line 6) | class TopKLoss(CrossentropyND):
    method __init__ (line 11) | def __init__(self, weight=None, ignore_index=-100, k=10):
    method forward (line 15) | def forward(self, inp, target):

FILE: networks/RecursiveUNet.py
  class UNet (line 28) | class UNet(nn.Module):
    method __init__ (line 29) | def __init__(self, num_classes=3, in_channels=1, initial_filter_size=6...
    method forward (line 46) | def forward(self, x):
  class UnetSkipConnectionBlock (line 53) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 54) | def __init__(self, in_channels=None, out_channels=None, num_classes=1,...
    method contract (line 90) | def contract(in_channels, out_channels, kernel_size=3, norm_layer=nn.I...
    method expand (line 98) | def expand(in_channels, out_channels, kernel_size=3):
    method center_crop (line 106) | def center_crop(layer, target_width, target_height):
    method forward (line 112) | def forward(self, x):

FILE: networks/RecursiveUNet3D.py
  class UNet3D (line 28) | class UNet3D(nn.Module):
    method __init__ (line 29) | def __init__(self, num_classes=3, in_channels=1, initial_filter_size=6...
    method forward (line 46) | def forward(self, x):
  class UnetSkipConnectionBlock (line 53) | class UnetSkipConnectionBlock(nn.Module):
    method __init__ (line 54) | def __init__(self, in_channels=None, out_channels=None, num_classes=1,...
    method contract (line 90) | def contract(in_channels, out_channels, kernel_size=3, norm_layer=nn.I...
    method expand (line 98) | def expand(in_channels, out_channels, kernel_size=3):
    method center_crop (line 106) | def center_crop(layer, target_depth, target_width, target_height):
    method forward (line 113) | def forward(self, x):

FILE: networks/UNET.py
  class UNet (line 22) | class UNet(nn.Module):
    method __init__ (line 24) | def __init__(self, num_classes, in_channels=1, initial_filter_size=64,...
    method contract (line 75) | def contract(in_channels, out_channels, kernel_size=3, instancenorm=Tr...
    method expand (line 88) | def expand(in_channels, out_channels, kernel_size=3):
    method center_crop (line 96) | def center_crop(layer, target_width, target_height):
    method forward (line 102) | def forward(self, x, enable_concat=True, print_layer_shapes=False):

FILE: segment_a_spleen.py
  function save_single_image (line 28) | def save_single_image(image, image_header, filename):

FILE: utilities/file_and_folder_operations.py
  function subdirs (line 21) | def subdirs(folder, join=True, prefix=None, suffix=None, sort=True):
  function subfiles (line 34) | def subfiles(folder, join=True, prefix=None, suffix=None, sort=True):
  function maybe_mkdir_p (line 47) | def maybe_mkdir_p(directory):