SYMBOL INDEX (72 symbols across 4 files)

FILE: classifier.py
  class training (line 13) | class training:
    method __init__ (line 14) | def __init__(self, datadir, modeldir,classifier_filename):
    method main_train (line 19) | def main_train(self):

FILE: detect_face.py
  function layer (line 37) | def layer(op):
  class Network (line 61) | class Network(object):
    method __init__ (line 63) | def __init__(self, inputs, trainable=True):
    method setup (line 75) | def setup(self):
    method load (line 79) | def load(self, data_path, session, ignore_missing=False):
    method feed (line 97) | def feed(self, *args):
    method get_output (line 112) | def get_output(self):
    method get_unique_name (line 116) | def get_unique_name(self, prefix):
    method make_var (line 123) | def make_var(self, name, shape):
    method validate_padding (line 127) | def validate_padding(self, padding):
    method conv (line 132) | def conv(self,
    method prelu (line 167) | def prelu(self, inp, name):
    method max_pool (line 175) | def max_pool(self, inp, k_h, k_w, s_h, s_w, name, padding='SAME'):
    method fc (line 184) | def fc(self, inp, num_out, name, relu=True):
    method softmax (line 209) | def softmax(self, target, axis, name=None):
  class PNet (line 216) | class PNet(Network):
    method setup (line 217) | def setup(self):
  class RNet (line 232) | class RNet(Network):
    method setup (line 233) | def setup(self):
  class ONet (line 251) | class ONet(Network):
    method setup (line 252) | def setup(self):
  function create_mtcnn (line 276) | def create_mtcnn(sess, model_path):
  function detect_face (line 298) | def detect_face(img, minsize, pnet, rnet, onet, threshold, factor):
  function bulk_detect_face (line 420) | def bulk_detect_face(images, detection_window_size_ratio, pnet, rnet, on...
  function bbreg (line 643) | def bbreg(boundingbox,reg):
  function generateBoundingBox (line 657) | def generateBoundingBox(imap, reg, scale, t):
  function nms (line 684) | def nms(boxes, threshold, method):
  function pad (line 717) | def pad(total_boxes, w, h):
  function rerec (line 752) | def rerec(bboxA):
  function imresample (line 762) | def imresample(img, sz):

FILE: facenet.py
  function triplet_loss (line 43) | def triplet_loss(anchor, positive, negative, alpha):
  function decov_loss (line 63) | def decov_loss(xs):
  function center_loss (line 76) | def center_loss(features, label, alfa, nrof_classes):
  function get_image_paths_and_labels (line 90) | def get_image_paths_and_labels(dataset):
  function shuffle_examples (line 98) | def shuffle_examples(image_paths, labels):
  function read_images_from_disk (line 104) | def read_images_from_disk(input_queue):
  function random_rotate_image (line 116) | def random_rotate_image(image):
  function read_and_augment_data (line 120) | def read_and_augment_data(image_list, label_list, image_size, batch_size...
  function _add_loss_summaries (line 153) | def _add_loss_summaries(total_loss):
  function train (line 179) | def train(total_loss, global_step, optimizer, learning_rate, moving_aver...
  function prewhiten (line 224) | def prewhiten(x):
  function crop (line 231) | def crop(image, random_crop, image_size):
  function flip (line 243) | def flip(image, random_flip):
  function to_rgb (line 248) | def to_rgb(img):
  function load_data (line 254) | def load_data(image_paths, do_random_crop, do_random_flip, image_size, d...
  function get_label_batch (line 268) | def get_label_batch(label_data, batch_size, batch_index):
  function get_batch (line 280) | def get_batch(image_data, batch_size, batch_index):
  function get_triplet_batch (line 292) | def get_triplet_batch(triplets, batch_index, batch_size):
  function get_learning_rate_from_file (line 300) | def get_learning_rate_from_file(filename, epoch):
  class ImageClass (line 313) | class ImageClass():
    method __init__ (line 315) | def __init__(self, name, image_paths):
    method __str__ (line 319) | def __str__(self):
    method __len__ (line 322) | def __len__(self):
  function get_dataset (line 325) | def get_dataset(paths, has_class_directories=True):
  function get_image_paths (line 340) | def get_image_paths(facedir):
  function split_dataset (line 347) | def split_dataset(dataset, split_ratio, mode):
  function load_model (line 371) | def load_model(model):
  function get_model_filenames (line 391) | def get_model_filenames(model_dir):
  function calculate_roc (line 410) | def calculate_roc(thresholds, embeddings1, embeddings2, actual_issame, n...
  function calculate_accuracy (line 440) | def calculate_accuracy(threshold, dist, actual_issame):
  function calculate_val (line 454) | def calculate_val(thresholds, embeddings1, embeddings2, actual_issame, f...
  function calculate_val_far (line 488) | def calculate_val_far(threshold, dist, actual_issame):
  function store_revision_info (line 498) | def store_revision_info(src_path, output_dir, arg_string):
  function list_variables (line 517) | def list_variables(filename):
  function put_images_on_grid (line 523) | def put_images_on_grid(images, shape=(16,8)):
  function write_arguments_to_file (line 540) | def write_arguments_to_file(args, filename):

FILE: preprocess.py
  class preprocesses (line 11) | class preprocesses:
    method __init__ (line 12) | def __init__(self, input_datadir, output_datadir):
    method collect_data (line 16) | def collect_data(self):