SYMBOL INDEX (60 symbols across 10 files)

FILE: Attack/attack.py
  function prep (line 17) | def prep(im):
  function main (line 23) | def main(args):
  function parse_arguments (line 209) | def parse_arguments(argv):

FILE: Attack/cos_mx.py
  function prep (line 11) | def prep(im):
  function main (line 17) | def main(args):
  function parse_arguments (line 46) | def parse_arguments(argv):

FILE: Attack/cos_tf.py
  function prep (line 9) | def prep(im):
  function main (line 15) | def main(args):
  function parse_arguments (line 47) | def parse_arguments(argv):

FILE: Attack/face_preparation.py
  function preprocess (line 15) | def preprocess(img, landmark):
  function main (line 31) | def main(args):
  function parse_arguments (line 67) | def parse_arguments(argv):

FILE: Attack/stn.py
  function spatial_transformer_network (line 4) | def spatial_transformer_network(input_fmap, theta, out_dims=None, **kwar...
  function get_pixel_value (line 66) | def get_pixel_value(img, x, y):
  function affine_grid_generator (line 95) | def affine_grid_generator(height, width, theta):
  function bilinear_sampler (line 159) | def bilinear_sampler(img, x, y):

FILE: Attack/utils.py
  function tf_integral (line 5) | def tf_integral(x,a):
  function tf_pre_parabol (line 7) | def tf_pre_parabol(x,par):
  function projector (line 12) | def projector(param,ph,logo):
  function TVloss (line 66) | def TVloss(logo,w_tv):

FILE: Demo/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 detect_face_force (line 419) | def detect_face_force(img, bbox, pnet, rnet, onet):
  function bulk_detect_face (line 490) | def bulk_detect_face(images, detection_window_size_ratio, pnet, rnet, on...
  function bbreg (line 713) | def bbreg(boundingbox,reg):
  function generateBoundingBox (line 727) | def generateBoundingBox(imap, reg, scale, t):
  function nms (line 754) | def nms(boxes, threshold, method):
  function pad (line 787) | def pad(total_boxes, w, h):
  function rerec (line 822) | def rerec(bboxA):
  function imresample (line 832) | def imresample(img, sz):

FILE: Demo/alignment.py
  function to_rgb (line 14) | def to_rgb(img):
  function preprocess (line 21) | def preprocess(img, landmark):
  function main (line 37) | def main(args):
  function parse_arguments (line 86) | def parse_arguments(argv):

FILE: Demo/demo.py
  function preprocess (line 13) | def preprocess(img, landmark):
  function main (line 29) | def main(args):
  function parse_arguments (line 116) | def parse_arguments(argv):

FILE: Demo/dumping.py
  function main (line 8) | def main(args):
  function parse_arguments (line 95) | def parse_arguments(argv):