SYMBOL INDEX (176 symbols across 16 files)

FILE: ResNet/ThreeDMM_shape.py
  class ResNet_101 (line 9) | class ResNet_101(Network_Shape):
    method setup (line 10) | def setup(self):

FILE: get_Rts.py
  function run_pose_estimation (line 35) | def run_pose_estimation(root_model_path, inputFile, outputDB, model_used...
  function esimatePose (line 110) | def esimatePose(root_model_path, inputFile, outputDB, model_used, lr_rat...

FILE: kaffe/errors.py
  class KaffeError (line 3) | class KaffeError(Exception):
  function print_stderr (line 6) | def print_stderr(msg):

FILE: kaffe/graph.py
  class Node (line 8) | class Node(object):
    method __init__ (line 10) | def __init__(self, name, kind, layer=None):
    method add_parent (line 20) | def add_parent(self, parent_node):
    method add_child (line 26) | def add_child(self, child_node):
    method get_only_parent (line 32) | def get_only_parent(self):
    method parameters (line 39) | def parameters(self):
    method __str__ (line 44) | def __str__(self):
    method __repr__ (line 47) | def __repr__(self):
  class Graph (line 51) | class Graph(object):
    method __init__ (line 53) | def __init__(self, nodes=None, name=None):
    method add_node (line 58) | def add_node(self, node):
    method get_node (line 62) | def get_node(self, name):
    method get_input_nodes (line 68) | def get_input_nodes(self):
    method get_output_nodes (line 71) | def get_output_nodes(self):
    method topologically_sorted (line 74) | def topologically_sorted(self):
    method compute_output_shapes (line 96) | def compute_output_shapes(self):
    method replaced (line 101) | def replaced(self, new_nodes):
    method transformed (line 104) | def transformed(self, transformers):
    method __contains__ (line 113) | def __contains__(self, key):
    method __str__ (line 116) | def __str__(self):
  class GraphBuilder (line 129) | class GraphBuilder(object):
    method __init__ (line 132) | def __init__(self, def_path, phase='test'):
    method load (line 142) | def load(self):
    method filter_layers (line 148) | def filter_layers(self, layers):
    method make_node (line 172) | def make_node(self, layer):
    method make_input_nodes (line 182) | def make_input_nodes(self):
    method build (line 202) | def build(self):
  class NodeMapper (line 259) | class NodeMapper(NodeDispatch):
    method __init__ (line 261) | def __init__(self, graph):
    method map (line 264) | def map(self):
    method map_chain (line 291) | def map_chain(self, chain):
    method map_node (line 294) | def map_node(self, node):
    method commit (line 301) | def commit(self, mapped_chains):

FILE: kaffe/layers.py
  class NodeKind (line 58) | class NodeKind(LayerType):
    method map_raw_kind (line 61) | def map_raw_kind(kind):
    method compute_output_shape (line 67) | def compute_output_shape(node):
  class NodeDispatchError (line 75) | class NodeDispatchError(KaffeError):
  class NodeDispatch (line 80) | class NodeDispatch(object):
    method get_handler_name (line 83) | def get_handler_name(node_kind):
    method get_handler (line 91) | def get_handler(self, node_kind, prefix):
  class LayerAdapter (line 101) | class LayerAdapter(object):
    method __init__ (line 103) | def __init__(self, layer, kind):
    method parameters (line 108) | def parameters(self):
    method get_kernel_value (line 117) | def get_kernel_value(scalar, repeated, idx, default=None):
    method kernel_parameters (line 134) | def kernel_parameters(self):

FILE: kaffe/shapes.py
  function get_filter_output_shape (line 9) | def get_filter_output_shape(i_h, i_w, params, round_func):
  function get_strided_kernel_output_shape (line 15) | def get_strided_kernel_output_shape(node, round_func):
  function shape_not_implemented (line 26) | def shape_not_implemented(node):
  function shape_identity (line 30) | def shape_identity(node):
  function shape_scalar (line 35) | def shape_scalar(node):
  function shape_data (line 39) | def shape_data(node):
  function shape_mem_data (line 57) | def shape_mem_data(node):
  function shape_concat (line 62) | def shape_concat(node):
  function shape_convolution (line 73) | def shape_convolution(node):
  function shape_pool (line 77) | def shape_pool(node):
  function shape_inner_product (line 81) | def shape_inner_product(node):

FILE: kaffe/tensorflow/network_shape.py
  function layer (line 7) | def layer(op):
  class Network_Shape (line 32) | class Network_Shape(object):
    method __init__ (line 34) | def __init__(self, inputs, trainable=True):
    method setup (line 50) | def setup(self):
    method load (line 55) | def load(self, data_path, prefix_name, session, ignore_missing=False):
    method load_specific_vars (line 113) | def load_specific_vars(self, data_path, op_name, session, ignore_missi...
    method feed (line 133) | def feed(self, *args):
    method get_output (line 148) | def get_output(self):
    method get_unique_name (line 152) | def get_unique_name(self, prefix):
    method make_var (line 159) | def make_var(self, name, shape):
    method make_var_fixed (line 165) | def make_var_fixed(self, name, shape):
    method validate_padding (line 171) | def validate_padding(self, padding):
    method conv (line 176) | def conv(self,
    method relu (line 234) | def relu(self, input, name):
    method max_pool (line 238) | def max_pool(self, input, k_h, k_w, s_h, s_w, name, padding=DEFAULT_PA...
    method avg_pool (line 247) | def avg_pool(self, input, k_h, k_w, s_h, s_w, name, padding=DEFAULT_PA...
    method lrn (line 256) | def lrn(self, input, radius, alpha, beta, name, bias=1.0):
    method concat (line 265) | def concat(self, inputs, axis, name):
    method add (line 269) | def add(self, inputs, name):
    method fc (line 273) | def fc(self, input, num_out, name, relu=True):
    method softmax (line 291) | def softmax(self, input, name):
    method batch_normalization (line 304) | def batch_normalization(self, input, name, scale_offset=True, relu=Fal...
    method dropout (line 332) | def dropout(self, input, keep_prob, name):

FILE: kaffe/transformers.py
  class DataInjector (line 14) | class DataInjector(object):
    method __init__ (line 19) | def __init__(self, def_path, data_path):
    method load (line 31) | def load(self):
    method load_using_caffe (line 37) | def load_using_caffe(self):
    method load_using_pb (line 43) | def load_using_pb(self):
    method normalize_pb_data (line 51) | def normalize_pb_data(self, layer):
    method adjust_parameters (line 66) | def adjust_parameters(self, node, data):
    method __call__ (line 82) | def __call__(self, graph):
  class DataReshaper (line 92) | class DataReshaper(object):
    method __init__ (line 94) | def __init__(self, mapping, replace=True):
    method has_spatial_parent (line 103) | def has_spatial_parent(self, node):
    method map (line 111) | def map(self, node_kind):
    method __call__ (line 117) | def __call__(self, graph):
  class SubNodeFuser (line 151) | class SubNodeFuser(object):
    method __call__ (line 156) | def __call__(self, graph):
    method is_eligible_pair (line 182) | def is_eligible_pair(self, parent, child):
    method merge (line 186) | def merge(self, parent, child):
  class ReLUFuser (line 191) | class ReLUFuser(SubNodeFuser):
    method __init__ (line 196) | def __init__(self, allowed_parent_types=None):
    method is_eligible_pair (line 201) | def is_eligible_pair(self, parent, child):
    method merge (line 205) | def merge(self, parent, _):
  class BatchNormScaleBiasFuser (line 209) | class BatchNormScaleBiasFuser(SubNodeFuser):
    method is_eligible_pair (line 219) | def is_eligible_pair(self, parent, child):
    method merge (line 223) | def merge(self, parent, child):
  class BatchNormPreprocessor (line 227) | class BatchNormPreprocessor(object):
    method __call__ (line 233) | def __call__(self, graph):
  class NodeRenamer (line 253) | class NodeRenamer(object):
    method __init__ (line 259) | def __init__(self, renamer):
    method __call__ (line 262) | def __call__(self, graph):
  class ParameterNamer (line 268) | class ParameterNamer(object):
    method __call__ (line 273) | def __call__(self, graph):

FILE: main_predict_6DoF.py
  function extract_3dmm_pose (line 52) | def extract_3dmm_pose():
  function main (line 315) | def main(_):

FILE: main_predict_ProjMat.py
  function extract_3dmm_ProjMat (line 52) | def extract_3dmm_ProjMat():
  function main (line 322) | def main(_):

FILE: myparse.py
  function parse_input (line 3) | def parse_input(input_file):

FILE: pose_model.py
  class ThreeD_Pose_Estimation (line 40) | class ThreeD_Pose_Estimation(object):
    method __init__ (line 43) | def __init__(self, images, labels, mode, ifdropout, keep_rate_fc6, kee...
    method _build_graph (line 70) | def _build_graph(self):
    method _stride_arr (line 80) | def _stride_arr(self, stride):
    method _build_model (line 84) | def _build_model(self):
    method conv (line 146) | def conv(self, input, kernel, biases, k_h, k_w, c_o, s_h, s_w,  paddin...
    method _ST (line 171) | def _ST(self, name, x, channel_x, out_size, filter_size, out_filters, ...
    method _variable_with_weight_decay (line 343) | def _variable_with_weight_decay(self, name, shape, stddev, wd):
    method _variable_on_cpu (line 368) | def _variable_on_cpu(self, name, shape, initializer):
    method _build_train_op (line 385) | def _build_train_op(self):
    method _batch_norm (line 412) | def _batch_norm(self, name, x):
    method _residual (line 457) | def _residual(self, x, in_filter, out_filter, stride,
    method _bottleneck_residual (line 490) | def _bottleneck_residual(self, x, in_filter, out_filter, stride,
    method _decay (line 525) | def _decay(self):
    method _conv (line 537) | def _conv(self, name, x, filter_size, in_filters, out_filters, strides):
    method _relu (line 547) | def _relu(self, x, leakiness=0.0):
    method _fully_connected (line 551) | def _fully_connected(self, x, out_dim):
    method _fully_connected_ST (line 567) | def _fully_connected_ST(self, x, out_dim):
    method _global_avg_pool (line 582) | def _global_avg_pool(self, x):
    method _repeat (line 587) | def _repeat(self, x, n_repeats):
    method _interpolate (line 596) | def _interpolate(self, im, x, y, out_size, channel_x):
    method _meshgrid (line 670) | def _meshgrid(self, height, width):
    method _transform (line 689) | def _transform(self, theta, input_dim, out_size, channel_input):

FILE: pose_utils.py
  function increaseBbox (line 11) | def increaseBbox(bbox, factor):
  function image_bbox_processing_v2 (line 34) | def image_bbox_processing_v2(img, bbox):
  function preProcessImage (line 80) | def preProcessImage(_savingDir, data_dict, data_root, factor, _alexNetSi...
  function replaceInFile (line 136) | def replaceInFile(filep, before, after):

FILE: renderer_fpn.py
  function render_fpn (line 36) | def render_fpn(inputFile, output_pose_db, outputFolder):

FILE: tf_utils.py
  function conv2d (line 21) | def conv2d(x, n_filters,
  function linear (line 70) | def linear(x, n_units, scope=None, stddev=0.02,
  function weight_variable (line 98) | def weight_variable(shape):
  function bias_variable (line 111) | def bias_variable(shape):
  function dense_to_one_hot (line 123) | def dense_to_one_hot(labels, n_classes=2):
  function prepare_trainVal_img_list (line 133) | def prepare_trainVal_img_list(img_list, num_subjs):
  function select_eval_img_list (line 184) | def select_eval_img_list(img_list, num_subjs, save_file_name):
  function input_processing (line 249) | def input_processing(images, pose_labels, id_labels, train_mean_vec, mea...
  function train_mean_vec2mat (line 271) | def train_mean_vec2mat(train_mean, images_array):
  function create_file_list (line 288) | def create_file_list(csv_file_path):

FILE: utils/pose_utils.py
  function increaseBbox (line 16) | def increaseBbox(bbox, factor):
  function increaseBbox_rescaleCASIA (line 40) | def increaseBbox_rescaleCASIA(bbox, factor):
  function increaseBbox_rescaleYOLO (line 67) | def increaseBbox_rescaleYOLO(bbox, im):
  function image_bbox_processing_v2 (line 112) | def image_bbox_processing_v2(img, bbox, landmarks=None):
  function image_bbox_processing_v3 (line 171) | def image_bbox_processing_v3(img, bbox):
  function preProcessImage (line 221) | def preProcessImage(im, lmks, bbox, factor, _alexNetSize, flipped):
  function resize_crop_rescaleCASIA (line 280) | def resize_crop_rescaleCASIA(im, bbox, lmks, factor):
  function resize_crop_rescaleCASIA_v2 (line 326) | def resize_crop_rescaleCASIA_v2(im, bbox, lmks, factor, bbox_type):
  function resize_crop_AFLW (line 400) | def resize_crop_AFLW(im, bbox, lmks):
  function preProcessImage_v2 (line 438) | def preProcessImage_v2(im, bbox, factor, _resNetSize, if_cropbyLmks_resc...
  function preProcessImage_useGTBBox (line 504) | def preProcessImage_useGTBBox(im, lmks, bbox, factor, _alexNetSize, flip...
  function replaceInFile (line 590) | def replaceInFile(filep, before, after):
  function flip_lmk_idx (line 596) | def flip_lmk_idx(img, lmarks):
  function pose_to_LMs (line 612) | def pose_to_LMs(pose_Rt):
  function RotationMatrix (line 637) | def RotationMatrix(angle_x, angle_y, angle_z):
  function matrix2angle (line 655) | def matrix2angle(R):
  function P2sRt (line 689) | def P2sRt(P):