SYMBOL INDEX (100 symbols across 16 files)

FILE: HSequences_bench/tools/HSequences_reader.py
  class HSequences_dataset (line 7) | class HSequences_dataset(object):
    method __init__ (line 9) | def __init__(self, dataset_path, split, split_path):
    method read_image (line 19) | def read_image(self, path):
    method read_homography (line 23) | def read_homography(self, h_name):
    method get_sequence (line 40) | def get_sequence(self, folder_id):
    method extract_hsequences (line 73) | def extract_hsequences(self):

FILE: HSequences_bench/tools/aux_tools.py
  function convert_opencv_matches_to_numpy (line 5) | def convert_opencv_matches_to_numpy(matches):
  function create_results (line 18) | def create_results():
  function create_overlapping_results (line 36) | def create_overlapping_results(detector_name, overlap):
  function check_directory (line 44) | def check_directory(dir):
  function convert_openCV_to_np (line 49) | def convert_openCV_to_np(pts, dsc, order_coord):

FILE: HSequences_bench/tools/geometry_tools.py
  function remove_borders (line 4) | def remove_borders(image, borders):
  function create_common_region_masks (line 20) | def create_common_region_masks(h_dst_2_src, shape_src, shape_dst):
  function prepare_homography (line 42) | def prepare_homography(hom):
  function apply_homography_to_points (line 55) | def apply_homography_to_points(points, h):
  function getAff (line 79) | def getAff(x,y,H):
  function find_index_higher_scores (line 100) | def find_index_higher_scores(map, num_points = 1000, threshold = -1):
  function get_point_coordinates (line 125) | def get_point_coordinates(map, scale_value=1., num_points=1000, threshol...
  function get_point_coordinates3D (line 144) | def get_point_coordinates3D(map, scale_factor=1., up_levels=0, num_point...

FILE: HSequences_bench/tools/matching_tools.py
  function create_precision_recall_results (line 4) | def create_precision_recall_results():
  function compute_matching_based_distance (line 14) | def compute_matching_based_distance(points_src, points_dst, matches, num...
  function compute_precision_recall (line 23) | def compute_precision_recall(matches, true_matches, num_points, eps=1e-6):
  function find_matches (line 51) | def find_matches(dsc_src, dsc_dst):

FILE: HSequences_bench/tools/opencv_matcher.py
  class OpencvBruteForceMatcher (line 5) | class OpencvBruteForceMatcher(object):
    method __init__ (line 11) | def __init__(self, distance='l2'):
    method match (line 14) | def match(self, descs1, descs2):
    method match_putative (line 24) | def match_putative(self, descs1, descs2, knn=2, threshold_ratio=0.7):
    method convert_opencv_matches_to_numpy (line 39) | def convert_opencv_matches_to_numpy(self, matches):

FILE: HSequences_bench/tools/repeatability_tools.py
  function check_common_points (line 4) | def check_common_points(kpts, mask):
  function select_top_k (line 12) | def select_top_k(kpts, k=1000):
  function apply_nms (line 17) | def apply_nms(score_map, size):
  function intersection_area (line 24) | def intersection_area(R, r, d = 0):
  function union_area (line 44) | def union_area(r, R, intersection):
  function compute_repeatability (line 48) | def compute_repeatability(src_indexes, dst_indexes, overlap_err=0.4, eps...

FILE: extract_multiscale_features.py
  function check_directory (line 17) | def check_directory(dir):
  function create_result_dir (line 21) | def create_result_dir(path):
  function extract_multiscale_features (line 30) | def extract_multiscale_features():

FILE: hsequeces_bench.py
  function hsequences_metrics (line 14) | def hsequences_metrics():

FILE: keyNet/aux/desc_aux_function.py
  function _meshgrid (line 3) | def _meshgrid(height, width):
  function transformer_crop (line 23) | def transformer_crop(images, out_size, batch_inds, kpts_xy, kpts_scale=N...
  function build_patch_extraction (line 143) | def build_patch_extraction(kpts, batch_inds, images, kpts_scale, name='P...

FILE: keyNet/aux/tools.py
  function remove_borders (line 4) | def remove_borders(images, borders=3):
  function check_directory (line 28) | def check_directory(file_path):
  function check_tensorboard_directory (line 33) | def check_tensorboard_directory(version_network_name):

FILE: keyNet/datasets/dataset_utils.py
  function read_bw_image (line 9) | def read_bw_image(path):
  function read_color_image (line 14) | def read_color_image(path):
  function apply_h_2_source_image (line 18) | def apply_h_2_source_image(source_im, h):
  function generate_composed_homography (line 24) | def generate_composed_homography(max_angle=45, max_scaling=2.0, max_shea...
  function color_distorsion (line 50) | def color_distorsion(im_c):
  function to_black_and_white (line 56) | def to_black_and_white(img):
  function colorDistorsion (line 61) | def colorDistorsion(image, lower=0.5, upper=1.5, delta=18.0, delta_brigt...
  function check_margins (line 104) | def check_margins(img, axis=-1):
  function swap_channels (line 114) | def swap_channels(image, swaps):

FILE: keyNet/datasets/tf_dataset.py
  class tf_dataset (line 8) | class tf_dataset(object):
    method __init__ (line 10) | def __init__(self, dataset_root, tfrecord_root, size_patches, batch_si...
    method get_num_patches (line 51) | def get_num_patches(self, is_val=False):
    method create_dataset_object (line 57) | def create_dataset_object(self, is_val=False):
    method _compute_num_examples (line 74) | def _compute_num_examples(self):
    method _parse_function (line 84) | def _parse_function(self, sample_pair):
    method _prepare_data (line 88) | def _prepare_data(self, sample_pair):
    method _find_data_path (line 111) | def _find_data_path(self, data_path):
    method _load_data_names (line 116) | def _load_data_names(self, data_path):
    method _bytes_feature (line 130) | def _bytes_feature(self, value):
    method _create_tfrecords (line 133) | def _create_tfrecords(self, is_val):
    method _create_pair_images (line 137) | def _create_pair_images(self, is_val):

FILE: keyNet/loss/score_loss_function.py
  function ip_layer (line 6) | def ip_layer(scores, window_size, kernels):
  function ip_softscores (line 33) | def ip_softscores(scores, window_size, kernels):
  function unpool (line 56) | def unpool(pool, ind, ksize=[1, 2, 2, 1], scope='unpool'):
  function grid_indexes_nms_conv (line 83) | def grid_indexes_nms_conv(scores, kernels, window_size):
  function loss_ln_indexes_norm (line 100) | def loss_ln_indexes_norm(src_indexes, label_indexes, weights_indexes, wi...
  function msip_loss_function (line 109) | def msip_loss_function(src_im, src_score_maps, dst_score_maps, window_si...

FILE: keyNet/model/hardnet_pytorch.py
  class L2Norm (line 7) | class L2Norm(nn.Module):
    method __init__ (line 8) | def __init__(self):
    method forward (line 12) | def forward(self, x):
  class L1Norm (line 18) | class L1Norm(nn.Module):
    method __init__ (line 19) | def __init__(self):
    method forward (line 23) | def forward(self, x):
  class HardNet (line 29) | class HardNet(nn.Module):
    method __init__ (line 33) | def __init__(self):
    method input_norm (line 62) | def input_norm(self, x):
    method forward (line 69) | def forward(self, input):

FILE: keyNet/model/keynet_architecture.py
  function gaussian_multiple_channels (line 5) | def gaussian_multiple_channels(num_channels, sigma):
  function ones_multiple_channels (line 23) | def ones_multiple_channels(size, num_channels):
  function grid_indexes (line 34) | def grid_indexes(size):
  function get_kernel_size (line 54) | def get_kernel_size(factor):
  function linear_upsample_weights (line 61) | def linear_upsample_weights(half_factor, number_of_classes):
  function create_derivatives_kernel (line 81) | def create_derivatives_kernel():
  class keynet (line 99) | class keynet(object):
    method __init__ (line 100) | def __init__(self, args, MSIP_sizes=[]):
    method create_kernels (line 136) | def create_kernels(self, MSIP_sizes, name_scope):
    method get_kernels (line 163) | def get_kernels(self):
    method model (line 166) | def model(self, input_data, is_training, dim, reuse=False, train_score...
    method compute_handcrafted_features (line 184) | def compute_handcrafted_features(self, image, network, idx, name_scope):
    method local_norm_image (line 217) | def local_norm_image(self, x, k_size=65, eps=1e-10):
    method compute_features (line 228) | def compute_features(self, input_data, dim, reuse, is_training):
    method conv_block (line 264) | def conv_block(self, features, name, reuse, is_training, num_filters, ...
    method non_maximum_supression (line 283) | def non_maximum_supression(self, map, thresh=0.):

FILE: train_network.py
  function suppress_stdout (line 16) | def suppress_stdout():
  function save_log (line 25) | def save_log(str, file):
  function train_keynet_architecture (line 36) | def train_keynet_architecture():