SYMBOL INDEX (299 symbols across 59 files)

FILE: contributed/batch_represent.py
  function main (line 81) | def main(args):
  function parse_arguments (line 134) | def parse_arguments(argv):

FILE: contributed/cluster.py
  function main (line 40) | def main(args):
  function align_data (line 117) | def align_data(image_list, image_size, margin, pnet, rnet, onet):
  function create_network_face_detection (line 149) | def create_network_face_detection(gpu_memory_fraction):
  function load_images_from_folder (line 158) | def load_images_from_folder(folder):
  function parse_arguments (line 167) | def parse_arguments(argv):

FILE: contributed/clustering.py
  function face_distance (line 9) | def face_distance(face_encodings, face_to_compare):
  function load_model (line 24) | def load_model(model_dir, meta_file, ckpt_file):
  function _chinese_whispers (line 29) | def _chinese_whispers(encoding_list, threshold=0.55, iterations=20):
  function cluster_facial_encodings (line 130) | def cluster_facial_encodings(facial_encodings):
  function compute_facial_encodings (line 153) | def compute_facial_encodings(sess,images_placeholder,embeddings,phase_tr...
  function get_onedir (line 183) | def get_onedir(paths):
  function main (line 197) | def main(args):
  function parse_args (line 253) | def parse_args():

FILE: contributed/export_embeddings.py
  function main (line 66) | def main(args):
  function load_and_align_data (line 131) | def load_and_align_data(image_paths, image_size, margin, gpu_memory_frac...
  function parse_arguments (line 164) | def parse_arguments(argv):

FILE: contributed/face.py
  class Face (line 50) | class Face:
    method __init__ (line 51) | def __init__(self):
  class Recognition (line 59) | class Recognition:
    method __init__ (line 60) | def __init__(self):
    method add_identity (line 65) | def add_identity(self, image, person_name):
    method identify (line 74) | def identify(self, image):
  class Identifier (line 86) | class Identifier:
    method __init__ (line 87) | def __init__(self):
    method identify (line 91) | def identify(self, face):
  class Encoder (line 98) | class Encoder:
    method __init__ (line 99) | def __init__(self):
    method generate_embedding (line 104) | def generate_embedding(self, face):
  class Detection (line 117) | class Detection:
    method __init__ (line 123) | def __init__(self, face_crop_size=160, face_crop_margin=32):
    method _setup_mtcnn (line 128) | def _setup_mtcnn(self):
    method find_faces (line 135) | def find_faces(self, image):

FILE: contributed/predict.py
  function main (line 45) | def main(args):
  function load_and_align_data (line 77) | def load_and_align_data(image_paths, image_size, margin, gpu_memory_frac...
  function parse_arguments (line 112) | def parse_arguments(argv):

FILE: contributed/real_time_face_recognition.py
  function add_overlays (line 36) | def add_overlays(frame, faces, frame_rate):
  function main (line 53) | def main(args):
  function parse_arguments (line 94) | def parse_arguments(argv):

FILE: src/align/align_dataset_mtcnn.py
  function main (line 39) | def main(args):
  function parse_arguments (line 141) | def parse_arguments(argv):

FILE: src/align/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 421) | def bulk_detect_face(images, detection_window_size_ratio, pnet, rnet, on...
  function bbreg (line 646) | def bbreg(boundingbox,reg):
  function generateBoundingBox (line 660) | def generateBoundingBox(imap, reg, scale, t):
  function nms (line 687) | def nms(boxes, threshold, method):
  function pad (line 720) | def pad(total_boxes, w, h):
  function rerec (line 755) | def rerec(bboxA):
  function imresample (line 765) | def imresample(img, sz):

FILE: src/calculate_filtering_metrics.py
  function main (line 41) | def main(args):
  function parse_arguments (line 112) | def parse_arguments(argv):

FILE: src/classifier.py
  function main (line 39) | def main(args):
  function split_dataset (line 125) | def split_dataset(dataset, min_nrof_images_per_class, nrof_train_images_...
  function parse_arguments (line 138) | def parse_arguments(argv):

FILE: src/compare.py
  function main (line 39) | def main(args):
  function load_and_align_data (line 79) | def load_and_align_data(image_paths, image_size, margin, gpu_memory_frac...
  function parse_arguments (line 115) | def parse_arguments(argv):

FILE: src/decode_msceleb_dataset.py
  function main (line 48) | def main(args):

FILE: src/download_and_extract.py
  function download_and_extract_file (line 13) | def download_and_extract_file(model_name, data_dir):
  function download_file_from_google_drive (line 23) | def download_file_from_google_drive(file_id, destination):
  function get_confirm_token (line 38) | def get_confirm_token(response):
  function save_response_content (line 45) | def save_response_content(response, destination):

FILE: src/facenet.py
  function triplet_loss (line 44) | def triplet_loss(anchor, positive, negative, alpha):
  function center_loss (line 64) | def center_loss(features, label, alfa, nrof_classes):
  function get_image_paths_and_labels (line 79) | def get_image_paths_and_labels(dataset):
  function shuffle_examples (line 87) | def shuffle_examples(image_paths, labels):
  function random_rotate_image (line 93) | def random_rotate_image(image):
  function create_input_pipeline (line 103) | def create_input_pipeline(input_queue, image_size, nrof_preprocess_threa...
  function get_control_flag (line 139) | def get_control_flag(control, field):
  function _add_loss_summaries (line 142) | def _add_loss_summaries(total_loss):
  function train (line 168) | def train(total_loss, global_step, optimizer, learning_rate, moving_aver...
  function prewhiten (line 213) | def prewhiten(x):
  function crop (line 220) | def crop(image, random_crop, image_size):
  function flip (line 232) | def flip(image, random_flip):
  function to_rgb (line 237) | def to_rgb(img):
  function load_data (line 243) | def load_data(image_paths, do_random_crop, do_random_flip, image_size, d...
  function get_label_batch (line 257) | def get_label_batch(label_data, batch_size, batch_index):
  function get_batch (line 269) | def get_batch(image_data, batch_size, batch_index):
  function get_triplet_batch (line 281) | def get_triplet_batch(triplets, batch_index, batch_size):
  function get_learning_rate_from_file (line 289) | def get_learning_rate_from_file(filename, epoch):
  class ImageClass (line 305) | class ImageClass():
    method __init__ (line 307) | def __init__(self, name, image_paths):
    method __str__ (line 311) | def __str__(self):
    method __len__ (line 314) | def __len__(self):
  function get_dataset (line 317) | def get_dataset(path, has_class_directories=True):
  function get_image_paths (line 332) | def get_image_paths(facedir):
  function split_dataset (line 339) | def split_dataset(dataset, split_ratio, min_nrof_images_per_class, mode):
  function load_model (line 364) | def load_model(model, input_map=None):
  function get_model_filenames (line 384) | def get_model_filenames(model_dir):
  function distance (line 408) | def distance(embeddings1, embeddings2, distance_metric=0):
  function calculate_roc (line 424) | def calculate_roc(thresholds, embeddings1, embeddings2, actual_issame, n...
  function calculate_accuracy (line 457) | def calculate_accuracy(threshold, dist, actual_issame):
  function calculate_val (line 471) | def calculate_val(thresholds, embeddings1, embeddings2, actual_issame, f...
  function calculate_val_far (line 508) | def calculate_val_far(threshold, dist, actual_issame):
  function store_revision_info (line 518) | def store_revision_info(src_path, output_dir, arg_string):
  function list_variables (line 545) | def list_variables(filename):
  function put_images_on_grid (line 551) | def put_images_on_grid(images, shape=(16,8)):
  function write_arguments_to_file (line 568) | def write_arguments_to_file(args, filename):

FILE: src/freeze_graph.py
  function main (line 38) | def main(args):
  function freeze_graph_def (line 65) | def freeze_graph_def(sess, input_graph_def, output_node_names):
  function parse_arguments (line 93) | def parse_arguments(argv):

FILE: src/generative/calculate_attribute_vectors.py
  function main (line 42) | def main(args):
  function read_annotations (line 157) | def read_annotations(filename):
  function parse_arguments (line 172) | def parse_arguments(argv):

FILE: src/generative/models/dfc_vae.py
  class Vae (line 37) | class Vae(generative.models.vae_base.Vae):
    method __init__ (line 39) | def __init__(self, latent_variable_dim):
    method encoder (line 42) | def encoder(self, images, is_training):
    method decoder (line 62) | def decoder(self, latent_var, is_training):
  function leaky_relu (line 90) | def leaky_relu(x):

FILE: src/generative/models/dfc_vae_large.py
  class Vae (line 37) | class Vae(generative.models.vae_base.Vae):
    method __init__ (line 39) | def __init__(self, latent_variable_dim):
    method encoder (line 43) | def encoder(self, images, is_training):
    method decoder (line 64) | def decoder(self, latent_var, is_training):
  function leaky_relu (line 94) | def leaky_relu(x):

FILE: src/generative/models/dfc_vae_resnet.py
  class Vae (line 37) | class Vae(generative.models.vae_base.Vae):
    method __init__ (line 39) | def __init__(self, latent_variable_dim):
    method encoder (line 42) | def encoder(self, images, is_training):
    method decoder (line 72) | def decoder(self, latent_var, is_training):
  function conv2d_block (line 105) | def conv2d_block(inp, scale, *args, **kwargs):
  function leaky_relu (line 108) | def leaky_relu(x):

FILE: src/generative/models/vae_base.py
  class Vae (line 32) | class Vae(object):
    method __init__ (line 34) | def __init__(self, latent_variable_dim, image_size):
    method encoder (line 48) | def encoder(self, images, is_training):
    method decoder (line 52) | def decoder(self, latent_var, is_training):
    method get_image_size (line 56) | def get_image_size(self):

FILE: src/generative/modify_attribute.py
  function main (line 42) | def main(args):
  function parse_arguments (line 122) | def parse_arguments(argv):

FILE: src/generative/train_vae.py
  function main (line 43) | def main(args):
  function get_variables_to_train (line 219) | def get_variables_to_train():
  function get_facenet_variables_to_restore (line 226) | def get_facenet_variables_to_restore():
  function kl_divergence_loss (line 234) | def kl_divergence_loss(mean, log_variance):
  function parse_arguments (line 238) | def parse_arguments(argv):

FILE: src/lfw.py
  function evaluate (line 34) | def evaluate(embeddings, actual_issame, nrof_folds=10, distance_metric=0...
  function get_paths (line 46) | def get_paths(lfw_dir, pairs):
  function add_extension (line 69) | def add_extension(path):
  function read_pairs (line 77) | def read_pairs(pairs_filename):

FILE: src/models/dummy.py
  function inference (line 33) | def inference(images, keep_probability, phase_train=True,  # @UnusedVari...

FILE: src/models/inception_resnet_v1.py
  function block35 (line 30) | def block35(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=...
  function block17 (line 51) | def block17(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=...
  function block8 (line 72) | def block8(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=N...
  function reduction_a (line 91) | def reduction_a(net, k, l, m, n):
  function reduction_b (line 108) | def reduction_b(net):
  function inference (line 130) | def inference(images, keep_probability, phase_train=True,
  function inception_resnet_v1 (line 152) | def inception_resnet_v1(inputs, is_training=True,

FILE: src/models/inception_resnet_v2.py
  function block35 (line 30) | def block35(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=...
  function block17 (line 51) | def block17(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=...
  function block8 (line 72) | def block8(net, scale=1.0, activation_fn=tf.nn.relu, scope=None, reuse=N...
  function inference (line 91) | def inference(images, keep_probability, phase_train=True,
  function inception_resnet_v2 (line 112) | def inception_resnet_v2(inputs, is_training=True,

FILE: src/models/squeezenet.py
  function fire_module (line 8) | def fire_module(inputs,
  function squeeze (line 21) | def squeeze(inputs, num_outputs):
  function expand (line 24) | def expand(inputs, num_outputs):
  function inference (line 30) | def inference(images, keep_probability, phase_train=True, bottleneck_lay...

FILE: src/train_softmax.py
  function main (line 47) | def main(args):
  function find_threshold (line 265) | def find_threshold(var, percentile):
  function filter_dataset (line 273) | def filter_dataset(dataset, data_filename, percentile, min_nrof_images_p...
  function train (line 296) | def train(args, sess, epoch, image_list, label_list, index_dequeue_op, e...
  function validate (line 356) | def validate(args, sess, epoch, image_list, label_list, enqueue_op, imag...
  function evaluate (line 397) | def evaluate(sess, enqueue_op, image_paths_placeholder, labels_placehold...
  function save_variables_and_metagraph (line 457) | def save_variables_and_metagraph(sess, saver, summary_writer, model_dir,...
  function parse_arguments (line 480) | def parse_arguments(argv):

FILE: src/train_tripletloss.py
  function main (line 46) | def main(args):
  function train (line 200) | def train(args, sess, dataset, epoch, image_paths_placeholder, labels_pl...
  function select_triplets (line 271) | def select_triplets(embeddings, nrof_images_per_class, image_paths, peop...
  function sample_people (line 313) | def sample_people(dataset, people_per_batch, images_per_person):
  function evaluate (line 341) | def evaluate(sess, image_paths, embeddings, labels_batch, image_paths_pl...
  function save_variables_and_metagraph (line 381) | def save_variables_and_metagraph(sess, saver, summary_writer, model_dir,...
  function get_learning_rate_from_file (line 404) | def get_learning_rate_from_file(filename, epoch):
  function parse_arguments (line 418) | def parse_arguments(argv):

FILE: src/validate_on_lfw.py
  function main (line 44) | def main(args):
  function evaluate (line 86) | def evaluate(sess, enqueue_op, image_paths_placeholder, labels_placehold...
  function parse_arguments (line 138) | def parse_arguments(argv):

FILE: test/batch_norm_test.py
  class BatchNormTest (line 29) | class BatchNormTest(unittest.TestCase):
    method testBatchNorm (line 33) | def testBatchNorm(self):

FILE: test/center_loss_test.py
  class CenterLossTest (line 28) | class CenterLossTest(unittest.TestCase):
    method testCenterLoss (line 32) | def testCenterLoss(self):
  function create_features (line 70) | def create_features(label_to_center, batch_size, nrof_features, labels):

FILE: test/restore_test.py
  class TrainTest (line 30) | class TrainTest(unittest.TestCase):
    method setUpClass (line 33) | def setUpClass(self):
    method tearDownClass (line 37) | def tearDownClass(self):
    method test_restore_noema (line 41) | def test_restore_noema(self):
    method test_restore_ema (line 91) | def test_restore_ema(self):
  function create_checkpoint_file (line 172) | def create_checkpoint_file(model_dir, model_file):

FILE: test/train_test.py
  function memory_usage_psutil (line 32) | def memory_usage_psutil():
  function align_dataset_if_needed (line 39) | def align_dataset_if_needed(self):
  class TrainTest (line 50) | class TrainTest(unittest.TestCase):
    method setUpClass (line 53) | def setUpClass(self):
    method tearDownClass (line 68) | def tearDownClass(self):
    method tearDown (line 72) | def tearDown(self):
    method test_training_classifier_inception_resnet_v1 (line 75) | def test_training_classifier_inception_resnet_v1(self):
    method test_training_classifier_inception_resnet_v2 (line 93) | def test_training_classifier_inception_resnet_v2(self):
    method test_training_classifier_squeezenet (line 110) | def test_training_classifier_squeezenet(self):
    method test_train_tripletloss_inception_resnet_v1 (line 128) | def test_train_tripletloss_inception_resnet_v1(self):
    method test_finetune_tripletloss_inception_resnet_v1 (line 146) | def test_finetune_tripletloss_inception_resnet_v1(self):
    method test_compare (line 166) | def test_compare(self):
    method test_validate_on_lfw (line 175) | def test_validate_on_lfw(self):
    method test_validate_on_lfw_frozen_graph (line 187) | def test_validate_on_lfw_frozen_graph(self):
    method test_freeze_graph (line 200) | def test_freeze_graph(self):
  function create_mock_dataset (line 209) | def create_mock_dataset(dataset_dir, image_size):
  function create_mock_lfw_pairs (line 226) | def create_mock_lfw_pairs(tmp_dir):

FILE: test/triplet_loss_test.py
  class DemuxEmbeddingsTest (line 28) | class DemuxEmbeddingsTest(unittest.TestCase):
    method testDemuxEmbeddings (line 30) | def testDemuxEmbeddings(self):

FILE: tmp/align_dataset.py
  function main (line 37) | def main(args):
  function parse_arguments (line 117) | def parse_arguments(argv):

FILE: tmp/align_dlib.py
  class AlignDlib (line 69) | class AlignDlib:
    method __init__ (line 89) | def __init__(self, facePredictor):
    method getAllFaceBoundingBoxes (line 102) | def getAllFaceBoundingBoxes(self, rgbImg):
    method getLargestFaceBoundingBox (line 120) | def getLargestFaceBoundingBox(self, rgbImg, skipMulti=False):
    method findLandmarks (line 139) | def findLandmarks(self, rgbImg, bb):
    method align (line 158) | def align(self, imgDim, rgbImg, bb=None,

FILE: tmp/cacd2000_split_identities.py
  function main (line 6) | def main(args):
  function parse_arguments (line 24) | def parse_arguments(argv):

FILE: tmp/dataset_read_speed.py
  function main (line 7) | def main(args):
  function parse_arguments (line 23) | def parse_arguments(argv):

FILE: tmp/deepdream.py
  function main (line 12) | def main():

FILE: tmp/download_vgg_face_dataset.py
  function main (line 39) | def main(args):
  function save_error_message_file (line 83) | def save_error_message_file(filename, error_message):
  function to_rgb (line 88) | def to_rgb(img):
  function parse_arguments (line 94) | def parse_arguments(argv):

FILE: tmp/funnel_dataset.py
  function TemporaryDirectory (line 19) | def TemporaryDirectory():
  function main (line 27) | def main(args):
  function parse_arguments (line 83) | def parse_arguments(argv):

FILE: tmp/mnist_center_loss.py
  function data_type (line 58) | def data_type():
  function maybe_download (line 66) | def maybe_download(filename):
  function extract_data (line 79) | def extract_data(filename, num_images):
  function extract_labels (line 93) | def extract_labels(filename, num_images):
  function fake_data (line 103) | def fake_data(num_images):
  function error_rate (line 116) | def error_rate(predictions, labels):
  function main (line 124) | def main(argv=None):  # pylint: disable=unused-argument

FILE: tmp/mnist_noise_labels.py
  function data_type (line 57) | def data_type():
  function maybe_download (line 65) | def maybe_download(filename):
  function extract_data (line 78) | def extract_data(filename, num_images):
  function extract_labels (line 92) | def extract_labels(filename, num_images):
  function fake_data (line 102) | def fake_data(num_images):
  function error_rate (line 115) | def error_rate(predictions, labels):
  function main (line 123) | def main(argv=None):  # pylint: disable=unused-argument

FILE: tmp/network.py
  function conv (line 35) | def conv(inpOp, nIn, nOut, kH, kW, dH, dW, padType, name, phase_train=Tr...
  function affine (line 52) | def affine(inpOp, nIn, nOut, name, weight_decay=0.0):
  function l2_loss (line 62) | def l2_loss(tensor, weight=1.0, scope=None):
  function lppool (line 78) | def lppool(inpOp, pnorm, kH, kW, dH, dW, padding, name):
  function mpool (line 98) | def mpool(inpOp, kH, kW, dH, dW, padding, name):
  function apool (line 106) | def apool(inpOp, kH, kW, dH, dW, padding, name):
  function batch_norm (line 114) | def batch_norm(x, phase_train):
  function inception (line 148) | def inception(inp, inSize, ks, o1s, o2s1, o2s2, o3s1, o3s2, o4s1, o4s2, ...

FILE: tmp/nn2.py
  function inference (line 31) | def inference(images, keep_probability, phase_train=True, weight_decay=0...

FILE: tmp/nn3.py
  function inference (line 31) | def inference(images, keep_probability, phase_train=True, weight_decay=0...

FILE: tmp/nn4.py
  function inference (line 31) | def inference(images, keep_probability, phase_train=True, weight_decay=0...

FILE: tmp/nn4_small2_v1.py
  function inference (line 31) | def inference(images, keep_probability, phase_train=True, weight_decay=0...

FILE: tmp/rename_casia_directories.py
  function main (line 6) | def main(args):
  function parse_arguments (line 29) | def parse_arguments(argv):

FILE: tmp/seed_test.py
  function run_train (line 25) | def run_train():
  function _conv (line 90) | def _conv(inpOp, nIn, nOut, kH, kW, dH, dW, padType):
  function _affine (line 102) | def _affine(inpOp, nIn, nOut):
  function inference_conv_test (line 111) | def inference_conv_test(images):
  function inference_affine_test (line 117) | def inference_affine_test(images):

FILE: tmp/test_align.py
  function main (line 7) | def main():

FILE: tmp/test_invariance_on_lfw.py
  function main (line 41) | def main(args):
  function save_result (line 134) | def save_result(aug, acc, filename):
  function evaluate_accuracy (line 139) | def evaluate_accuracy(sess, images_placeholder, phase_train_placeholder,...
  function scale_images (line 160) | def scale_images(images, scale, image_size):
  function rotate_images (line 170) | def rotate_images(images, angle, image_size):
  function translate_images (line 180) | def translate_images(images, offset, image_size):
  function parse_arguments (line 187) | def parse_arguments(argv):

FILE: tmp/vggface16.py
  function load (line 9) | def load(filename, images):

FILE: tmp/vggverydeep19.py
  function load (line 9) | def load(filename, images):

FILE: tmp/visualize.py
  function main (line 38) | def main(args):
  function T (line 86) | def T(layer):
  function visstd (line 90) | def visstd(a, s=0.1):
  function render_naive (line 94) | def render_naive(sess, t_input, t_obj, img0, iter_n=20, step=1.0):
  function parse_arguments (line 106) | def parse_arguments(argv):

FILE: tmp/visualize_vgg_model.py
  function sqErrorLossContent (line 31) | def sqErrorLossContent(sess, modelGraph, layer):
  function sqErrorLossStyle (line 46) | def sqErrorLossStyle(sess, modelGraph):

FILE: tmp/visualize_vggface.py
  function main (line 6) | def main():
  function showarray (line 26) | def showarray(a):
  function visstd (line 31) | def visstd(a, s=0.1):
  function render_naive (line 35) | def render_naive(sess, t_input, t_obj, img0, iter_n=20, step=1.0):