SYMBOL INDEX (89 symbols across 9 files)

FILE: camvid.py
  function properties (line 22) | def properties():
  function load_images (line 39) | def load_images(img_path, gt_path, colors, load_greylevel_mask=False,
  function load_dataset_camvid (line 117) | def load_dataset_camvid(path, load_greylevel_mask=False, classes='subset...
  function load_dataset_camvid_segnet (line 230) | def load_dataset_camvid_segnet(path):
  function load_data (line 274) | def load_data(

FILE: evaluate_camvid.py
  function main (line 5) | def main(job_id, params):

FILE: get_info_model.py
  function print_pkl_params (line 12) | def print_pkl_params(pkl_path, *args):
  function print_params (line 32) | def print_params(fp, save_plot_path='', print_commit_hash=False, plot=Fa...

FILE: helper_dataset.py
  function compare_mask_image_filenames (line 22) | def compare_mask_image_filenames(filenames_images, filenames_mask,
  function convert_RGB_mask_to_index (line 33) | def convert_RGB_mask_to_index(im, colors, ignore_missing_labels=False):
  function resize (line 75) | def resize():
  function crop (line 79) | def crop():
  function zero_pad (line 83) | def zero_pad(im, resize_size, inpath="", pad_value=0):
  function rgb2illumination_invariant (line 128) | def rgb2illumination_invariant(img, alpha, hist_eq=False):
  function save_image (line 152) | def save_image(outpath, img):
  function save_RGB_mask (line 163) | def save_RGB_mask(outpath, mask):
  function preprocess_dataset (line 167) | def preprocess_dataset(train, valid, test,
  function preprocess (line 250) | def preprocess(x, mode=None,
  function lecun_lcn (line 287) | def lecun_lcn(input, kernel_size=9, threshold=1e-4, use_divisor=False):
  function local_mean_subtraction (line 333) | def local_mean_subtraction(input, kernel_size=5):
  function global_contrast_normalization (line 353) | def global_contrast_normalization(input, scale=1., subtract_mean=True,
  function gaussian_filter (line 391) | def gaussian_filter(kernel_shape):
  function mean_filter (line 407) | def mean_filter(kernel_size):
  function convolutional_zca (line 413) | def convolutional_zca(input, patch_size=(9, 9), max_patches=int(1e5)):

FILE: layers.py
  class ReSegLayer (line 13) | class ReSegLayer(lasagne.layers.Layer):
    method __init__ (line 14) | def __init__(self,
    method get_output_shape_for (line 434) | def get_output_shape_for(self, input_shape):
    method get_output_for (line 443) | def get_output_for(self, input_var, **kwargs):
  class ReNetLayer (line 451) | class ReNetLayer(lasagne.layers.Layer):
    method __init__ (line 453) | def __init__(self,
    method get_output_shape_for (line 731) | def get_output_shape_for(self, input_shape):
    method get_output_for (line 743) | def get_output_for(self, input_var, **kwargs):
  class BidirectionalRNNLayer (line 751) | class BidirectionalRNNLayer(lasagne.layers.Layer):
    method __init__ (line 754) | def __init__(
    method get_output_shape_for (line 918) | def get_output_shape_for(self, input_shape):
    method get_output_for (line 921) | def get_output_for(self, input_var, **kwargs):
  class LinearUpsamplingLayer (line 929) | class LinearUpsamplingLayer(lasagne.layers.Layer):
    method __init__ (line 931) | def __init__(self,
    method get_output_for (line 956) | def get_output_for(self, input_arr, **kwargs):
    method get_output_shape_for (line 983) | def get_output_shape_for(self, input_shape):
  class CropLayer (line 990) | class CropLayer(lasagne.layers.Layer):
    method __init__ (line 991) | def __init__(self, l_in, crop, data_format='bc01', centered=True,
    method get_output_shape_for (line 1001) | def get_output_shape_for(self, input_shape, **kwargs):
    method get_output_for (line 1025) | def get_output_for(self, input_arr, **kwargs):

FILE: padded.py
  class PaddedConv2DLayer (line 12) | class PaddedConv2DLayer(Conv2DLayer):
    method __init__ (line 13) | def __init__(self, incoming, num_filters, filter_size, stride=(1, 1),
    method get_output_for (line 71) | def get_output_for(self, input_arr, **kwargs):
    method get_output_shape_for (line 84) | def get_output_shape_for(self, input_shape):
    method get_equivalent_input_padding (line 88) | def get_equivalent_input_padding(self, layers_args=[]):
  class PaddedPool2DLayer (line 96) | class PaddedPool2DLayer(Pool2DLayer):
    method __init__ (line 97) | def __init__(self, incoming, pool_size, stride=None, pad=(0, 0),
    method get_output_for (line 135) | def get_output_for(self, input_arr, **kwargs):
    method get_output_shape_for (line 146) | def get_output_shape_for(self, input_shape):
    method get_equivalent_input_padding (line 150) | def get_equivalent_input_padding(self, layers_args=[]):
  class DynamicPaddingLayer (line 158) | class DynamicPaddingLayer(Layer):
    method __init__ (line 159) | def __init__(
    method get_output_for (line 195) | def get_output_for(self, input_arr, **kwargs):
    method get_output_shape_for (line 202) | def get_output_shape_for(self, input_shape):
  function zero_pad (line 207) | def zero_pad(input_arr, patch_size, stride, centered=True, data_format='...
  function zero_pad_shape (line 281) | def zero_pad_shape(input_shape, patch_size, stride, data_format,
  function get_equivalent_input_padding (line 306) | def get_equivalent_input_padding(layer, layers_args=[]):

FILE: reseg.py
  function get_dataset (line 39) | def get_dataset(name):
  function buildReSeg (line 43) | def buildReSeg(input_shape, input_var,
  function getFunctions (line 195) | def getFunctions(input_var, target_var, class_balance_w_var, l_pred,
  function train (line 312) | def train(saveto='model.npz',
  function show_seg (line 1072) | def show_seg(dataset_name, n_exp, dataset_set, mode='sequential', id=-1):

FILE: utils.py
  function iterate_minibatches (line 21) | def iterate_minibatches(inputs, targets, batchsize, rng=None, shuffle=Fa...
  function save_image (line 45) | def save_image(outpath, img):
  function validate (line 56) | def validate(f_pred,
  function zipp (line 180) | def zipp(vparams, params):
  function unzip (line 197) | def unzip(zipped, prefix=None):
  function unroll (line 217) | def unroll(deep_list):
  function retry_if_io_error (line 244) | def retry_if_io_error(exception):
  function save_with_retry (line 256) | def save_with_retry(saveto, args):
  function ceildiv (line 262) | def ceildiv(a, b):
  function to_float (line 280) | def to_float(l):
  function to_int (line 291) | def to_int(l):
  class VariableText (line 302) | class VariableText(FormatWidgetMixin, WidthWidgetMixin):
    method __init__ (line 305) | def __init__(self, format, mapping=mapping, **kwargs):
    method update_str (line 311) | def update_str(self, new_format):
    method update_mapping (line 314) | def update_mapping(self, new_mapping):
    method __call__ (line 317) | def __call__(self, progress, data):

FILE: vgg16.py
  class Vgg16Layer (line 26) | class Vgg16Layer(lasagne.layers.Layer):
    method __init__ (line 27) | def __init__(self,
    method get_output_for (line 174) | def get_output_for(self, input_var, **kwargs):
    method get_output_shape_for (line 181) | def get_output_shape_for(self, input_shape):
  class RGBtoBGRLayer (line 196) | class RGBtoBGRLayer(lasagne.layers.Layer):
    method __init__ (line 197) | def __init__(self, l_in, bgr_mean=numpy.array([103.939, 116.779, 123.6...
    method get_output_for (line 224) | def get_output_for(self, input_im, **kwargs):