SYMBOL INDEX (296 symbols across 18 files)

FILE: camera.py
  class Pose (line 11) | class Pose():
    method __call__ (line 17) | def __call__(self,R=None,t=None):
    method invert (line 36) | def invert(self,pose,use_inverse=False):
    method compose (line 44) | def compose(self,pose_list):
    method compose_pair (line 52) | def compose_pair(self,pose_a,pose_b):
  class Lie (line 61) | class Lie():
    method so3_to_SO3 (line 66) | def so3_to_SO3(self,w): # [...,3]
    method SO3_to_so3 (line 75) | def SO3_to_so3(self,R,eps=1e-7): # [...,3,3]
    method se3_to_SE3 (line 83) | def se3_to_SE3(self,wu): # [...,3]
    method SE3_to_se3 (line 96) | def SE3_to_se3(self,Rt,eps=1e-8): # [...,3,4]
    method skew_symmetric (line 109) | def skew_symmetric(self,w):
    method taylor_A (line 117) | def taylor_A(self,x,nth=10):
    method taylor_B (line 125) | def taylor_B(self,x,nth=10):
    method taylor_C (line 133) | def taylor_C(self,x,nth=10):
  class Quaternion (line 142) | class Quaternion():
    method q_to_R (line 144) | def q_to_R(self,q):
    method R_to_q (line 152) | def R_to_q(self,R,eps=1e-8): # [B,3,3]
    method invert (line 178) | def invert(self,q):
    method product (line 184) | def product(self,q1,q2): # [B,4]
  function to_hom (line 197) | def to_hom(X):
  function world2cam (line 203) | def world2cam(X,pose): # [B,N,3]
  function cam2img (line 206) | def cam2img(X,cam_intr):
  function img2cam (line 208) | def img2cam(X,cam_intr):
  function cam2world (line 210) | def cam2world(X,pose):
  function angle_to_rotation_matrix (line 215) | def angle_to_rotation_matrix(a,axis):
  function get_center_and_ray (line 226) | def get_center_and_ray(opt,pose,intr=None): # [HW,2]
  function get_camera_cords_grid_3D (line 246) | def get_camera_cords_grid_3D(opt,batch_size,intr=None,ray_idx=None): # [...
  function gather_camera_cords_grid_3D (line 263) | def gather_camera_cords_grid_3D(opt,batch_size,intr=None,ray_idx=None): ...
  function get_3D_points_from_depth (line 280) | def get_3D_points_from_depth(opt,center,ray,depth,multi_samples=False):
  function convert_NDC (line 286) | def convert_NDC(opt,center,ray,intr,near=1):
  function rotation_distance (line 305) | def rotation_distance(R1,R2,eps=1e-7):
  function procrustes_analysis (line 312) | def procrustes_analysis(X0,X1): # [N,3]
  function get_novel_view_poses (line 331) | def get_novel_view_poses(opt,pose_anchor,N=60,scale=1):

FILE: data/base.py
  class Dataset (line 16) | class Dataset(torch.utils.data.Dataset):
    method __init__ (line 18) | def __init__(self,opt,split="train"):
    method setup_loader (line 31) | def setup_loader(self,opt,shuffle=False,drop_last=False):
    method get_list (line 42) | def get_list(self,opt):
    method preload_worker (line 45) | def preload_worker(self,data_list,load_func,q,lock,idx_tqdm):
    method preload_threading (line 53) | def preload_threading(self,opt,load_func,data_str="images"):
    method __getitem__ (line 68) | def __getitem__(self,idx):
    method get_image (line 71) | def get_image(self,opt,idx):
    method generate_augmentation (line 74) | def generate_augmentation(self,opt):
    method preprocess_image (line 92) | def preprocess_image(self,opt,image,aug=None):
    method preprocess_camera (line 109) | def preprocess_camera(self,opt,intr,pose,aug=None):
    method apply_color_jitter (line 119) | def apply_color_jitter(self,opt,image,color_jitter):
    method __len__ (line 129) | def __len__(self):

FILE: data/blender.py
  class Dataset (line 17) | class Dataset(base.Dataset):
    method __init__ (line 19) | def __init__(self,opt,split="train",subset=None):
    method prefetch_all_data (line 36) | def prefetch_all_data(self,opt):
    method get_all_camera_poses (line 41) | def get_all_camera_poses(self,opt):
    method __getitem__ (line 46) | def __getitem__(self,idx):
    method get_image (line 61) | def get_image(self,opt,idx):
    method preprocess_image (line 66) | def preprocess_image(self,opt,image,aug=None):
    method get_camera (line 73) | def get_camera(self,opt,idx):
    method parse_raw_camera (line 81) | def parse_raw_camera(self,opt,pose_raw):

FILE: data/iphone.py
  class Dataset (line 17) | class Dataset(base.Dataset):
    method __init__ (line 19) | def __init__(self,opt,split="train",subset=None):
    method prefetch_all_data (line 36) | def prefetch_all_data(self,opt):
    method get_all_camera_poses (line 41) | def get_all_camera_poses(self,opt):
    method __getitem__ (line 45) | def __getitem__(self,idx):
    method get_image (line 60) | def get_image(self,opt,idx):
    method get_camera (line 65) | def get_camera(self,opt,idx):

FILE: data/llff.py
  class Dataset (line 17) | class Dataset(base.Dataset):
    method __init__ (line 19) | def __init__(self,opt,split="train",subset=None):
    method prefetch_all_data (line 37) | def prefetch_all_data(self,opt):
    method parse_cameras_and_bounds (line 42) | def parse_cameras_and_bounds(self,opt):
    method center_camera_poses (line 60) | def center_camera_poses(self,opt,poses):
    method get_all_camera_poses (line 71) | def get_all_camera_poses(self,opt):
    method __getitem__ (line 76) | def __getitem__(self,idx):
    method get_image (line 91) | def get_image(self,opt,idx):
    method get_camera (line 96) | def get_camera(self,opt,idx):
    method parse_raw_camera (line 104) | def parse_raw_camera(self,opt,pose_raw):

FILE: evaluate.py
  function main (line 12) | def main():

FILE: external/pohsun_ssim/pytorch_ssim/__init__.py
  function gaussian (line 7) | def gaussian(window_size, sigma):
  function create_window (line 11) | def create_window(window_size, channel):
  function _ssim (line 17) | def _ssim(img1, img2, window, window_size, channel, size_average = True):
  class SSIM (line 39) | class SSIM(torch.nn.Module):
    method __init__ (line 40) | def __init__(self, window_size = 11, size_average = True):
    method forward (line 47) | def forward(self, img1, img2):
  function ssim (line 65) | def ssim(img1, img2, window_size = 11, size_average = True):

FILE: model/barf.py
  class Model (line 19) | class Model(nerf.Model):
    method __init__ (line 21) | def __init__(self,opt):
    method build_networks (line 24) | def build_networks(self,opt):
    method setup_optimizer (line 49) | def setup_optimizer(self,opt):
    method train_iteration (line 62) | def train_iteration(self,opt,var,loader):
    method validate (line 79) | def validate(self,opt,ep=None):
    method log_scalars (line 85) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 100) | def visualize(self,opt,var,step=0,split="train"):
    method get_all_training_poses (line 109) | def get_all_training_poses(self,opt):
    method prealign_cameras (line 116) | def prealign_cameras(self,opt,pose,pose_GT):
    method evaluate_camera_alignment (line 134) | def evaluate_camera_alignment(self,opt,pose_aligned,pose_GT):
    method evaluate_full (line 144) | def evaluate_full(self,opt):
    method evaluate_test_time_photometric_optim (line 163) | def evaluate_test_time_photometric_optim(self,opt,var):
    method generate_videos_pose (line 181) | def generate_videos_pose(self,opt):
  class Graph (line 217) | class Graph(nerf.Graph):
    method __init__ (line 219) | def __init__(self,opt):
    method forward (line 226) | def forward(self,opt,var,mode=None):
    method get_pose (line 249) | def get_pose(self,opt,var,mode=None):
  class NeRF (line 278) | class NeRF(nerf.NeRF):
    method __init__ (line 280) | def __init__(self,opt):
    method positional_encoding (line 284) | def positional_encoding(self,opt,input,L): # [B,...,N]

FILE: model/base.py
  class Model (line 18) | class Model():
    method __init__ (line 20) | def __init__(self,opt):
    method load_dataset (line 24) | def load_dataset(self,opt,eval_split="val"):
    method build_networks (line 34) | def build_networks(self,opt):
    method setup_optimizer (line 39) | def setup_optimizer(self,opt):
    method restore_checkpoint (line 49) | def restore_checkpoint(self,opt):
    method setup_visualizer (line 62) | def setup_visualizer(self,opt):
    method train (line 78) | def train(self,opt):
    method train_epoch (line 94) | def train_epoch(self,opt):
    method train_iteration (line 111) | def train_iteration(self,opt,var,loader):
    method summarize_loss (line 130) | def summarize_loss(self,opt,var,loss):
    method validate (line 145) | def validate(self,opt,ep=None):
    method log_scalars (line 165) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 175) | def visualize(self,opt,var,step=0,split="train"):
    method save_checkpoint (line 178) | def save_checkpoint(self,opt,ep=0,it=0,latest=False):
  class Graph (line 185) | class Graph(torch.nn.Module):
    method __init__ (line 187) | def __init__(self,opt):
    method forward (line 190) | def forward(self,opt,var,mode=None):
    method compute_loss (line 194) | def compute_loss(self,opt,var,mode=None):
    method L1_loss (line 199) | def L1_loss(self,pred,label=0):
    method MSE_loss (line 202) | def MSE_loss(self,pred,label=0):

FILE: model/l2g_nerf.py
  class Model (line 20) | class Model(nerf.Model):
    method __init__ (line 22) | def __init__(self,opt):
    method build_networks (line 25) | def build_networks(self,opt):
    method setup_optimizer (line 55) | def setup_optimizer(self,opt):
    method train_iteration (line 69) | def train_iteration(self,opt,var,loader):
    method validate (line 86) | def validate(self,opt,ep=None):
    method log_scalars (line 92) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 107) | def visualize(self,opt,var,step=0,split="train"):
    method get_all_training_poses (line 116) | def get_all_training_poses(self,opt):
    method prealign_cameras (line 123) | def prealign_cameras(self,opt,pose,pose_GT):
    method evaluate_camera_alignment (line 141) | def evaluate_camera_alignment(self,opt,pose_aligned,pose_GT):
    method evaluate_full (line 151) | def evaluate_full(self,opt):
    method evaluate_test_time_photometric_optim (line 170) | def evaluate_test_time_photometric_optim(self,opt,var):
    method generate_videos_pose (line 188) | def generate_videos_pose(self,opt):
  class Graph (line 224) | class Graph(nerf.Graph):
    method __init__ (line 226) | def __init__(self,opt):
    method get_pose (line 233) | def get_pose(self,opt,var,mode=None):
    method forward (line 274) | def forward(self,opt,var,mode=None):
    method compute_loss (line 314) | def compute_loss(self,opt,var,mode=None):
    method local_render (line 348) | def local_render(self,opt,local_pose,intr=None,ray_idx=None,mode=None):
  class NeRF (line 380) | class NeRF(nerf.NeRF):
    method __init__ (line 382) | def __init__(self,opt):
    method positional_encoding (line 386) | def positional_encoding(self,opt,input,L): # [B,...,N]
  class localWarp (line 400) | class localWarp(torch.nn.Module):
    method __init__ (line 401) | def __init__(self, opt):
    method forward (line 413) | def forward(self,opt,uvf):

FILE: model/l2g_planar.py
  class Model (line 21) | class Model(base.Model):
    method __init__ (line 23) | def __init__(self,opt):
    method load_dataset (line 27) | def load_dataset(self,opt,eval_split=None):
    method build_networks (line 31) | def build_networks(self,opt):
    method setup_optimizer (line 36) | def setup_optimizer(self,opt):
    method setup_visualizer (line 65) | def setup_visualizer(self,opt):
    method train (line 77) | def train(self,opt):
    method train_iteration (line 104) | def train_iteration(self,opt,var,loader):
    method generate_warp_perturbation (line 113) | def generate_warp_perturbation(self,opt):
    method visualize_patches_compose (line 167) | def visualize_patches_compose(self,opt, homo_pert, rot_pert, trans_pert):
    method visualize_patches_use_matrix (line 181) | def visualize_patches_use_matrix(self,opt,warp_matrix):
    method predict_entire_image (line 196) | def predict_entire_image(self,opt):
    method log_scalars (line 203) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 222) | def visualize(self,opt,var,step=0,split="train"):
  class Graph (line 245) | class Graph(base.Graph):
    method __init__ (line 247) | def __init__(self,opt):
    method forward (line 251) | def forward(self,opt,var,mode=None):
    method compute_loss (line 292) | def compute_loss(self,opt,var,mode=None):
  class NeuralImageFunction (line 301) | class NeuralImageFunction(torch.nn.Module):
    method __init__ (line 303) | def __init__(self,opt):
    method define_network (line 308) | def define_network(self,opt):
    method forward (line 324) | def forward(self,opt,coord_2D): # [B,...,3]
    method positional_encoding (line 339) | def positional_encoding(self,opt,input,L): # [B,...,N]
  class localWarp (line 358) | class localWarp(torch.nn.Module):
    method __init__ (line 359) | def __init__(self, opt):
    method forward (line 371) | def forward(self,opt,uvf):

FILE: model/nerf.py
  class Model (line 19) | class Model(base.Model):
    method __init__ (line 21) | def __init__(self,opt):
    method load_dataset (line 25) | def load_dataset(self,opt,eval_split="val"):
    method setup_optimizer (line 31) | def setup_optimizer(self,opt):
    method train (line 46) | def train(self,opt):
    method log_scalars (line 71) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 88) | def visualize(self,opt,var,step=0,split="train",eps=1e-10):
    method get_all_training_poses (line 114) | def get_all_training_poses(self,opt):
    method evaluate_full (line 120) | def evaluate_full(self,opt,eps=1e-10):
    method generate_videos_synthesis (line 164) | def generate_videos_synthesis(self,opt,eps=1e-10):
  class Graph (line 210) | class Graph(base.Graph):
    method __init__ (line 212) | def __init__(self,opt):
    method forward (line 218) | def forward(self,opt,var,mode=None):
    method compute_loss (line 233) | def compute_loss(self,opt,var,mode=None):
    method get_pose (line 247) | def get_pose(self,opt,var,mode=None):
    method render (line 250) | def render(self,opt,pose,intr=None,ray_idx=None,mode=None):
    method render_by_slices (line 278) | def render_by_slices(self,opt,pose,intr=None,mode=None):
    method sample_depth (line 291) | def sample_depth(self,opt,batch_size,num_rays=None):
    method sample_depth_from_pdf (line 303) | def sample_depth_from_pdf(self,opt,pdf):
  class NeRF (line 324) | class NeRF(torch.nn.Module):
    method __init__ (line 326) | def __init__(self,opt):
    method define_network (line 330) | def define_network(self,opt):
    method tensorflow_init_weights (line 356) | def tensorflow_init_weights(self,opt,linear,out=None):
    method forward (line 368) | def forward(self,opt,points_3D,ray_unit=None,mode=None): # [B,...,3]
    method forward_samples (line 401) | def forward_samples(self,opt,center,ray,depth_samples,mode=None):
    method composite (line 410) | def composite(self,opt,ray,rgb_samples,density_samples,depth_samples):
    method positional_encoding (line 428) | def positional_encoding(self,opt,input,L): # [B,...,N]

FILE: model/planar.py
  class Model (line 20) | class Model(base.Model):
    method __init__ (line 22) | def __init__(self,opt):
    method load_dataset (line 26) | def load_dataset(self,opt,eval_split=None):
    method build_networks (line 30) | def build_networks(self,opt):
    method setup_optimizer (line 35) | def setup_optimizer(self,opt):
    method setup_visualizer (line 49) | def setup_visualizer(self,opt):
    method train (line 61) | def train(self,opt):
    method train_iteration (line 90) | def train_iteration(self,opt,var,loader):
    method generate_warp_perturbation (line 95) | def generate_warp_perturbation(self,opt):
    method visualize_patches (line 149) | def visualize_patches(self,opt,warp_param):
    method visualize_patches_compose (line 163) | def visualize_patches_compose(self,opt, homo_pert, rot_pert, trans_pert):
    method predict_entire_image (line 178) | def predict_entire_image(self,opt):
    method log_scalars (line 185) | def log_scalars(self,opt,var,loss,metric=None,step=0,split="train"):
    method visualize (line 205) | def visualize(self,opt,var,step=0,split="train"):
  class Graph (line 224) | class Graph(base.Graph):
    method __init__ (line 226) | def __init__(self,opt):
    method forward (line 230) | def forward(self,opt,var,mode=None):
    method compute_loss (line 238) | def compute_loss(self,opt,var,mode=None):
  class NeuralImageFunction (line 245) | class NeuralImageFunction(torch.nn.Module):
    method __init__ (line 247) | def __init__(self,opt):
    method define_network (line 252) | def define_network(self,opt):
    method forward (line 268) | def forward(self,opt,coord_2D): # [B,...,3]
    method positional_encoding (line 283) | def positional_encoding(self,opt,input,L): # [B,...,N]

FILE: options.py
  function parse_arguments (line 16) | def parse_arguments(args):
  function set (line 41) | def set(opt_cmd={}):
  function load_options (line 54) | def load_options(fname):
  function override_options (line 69) | def override_options(opt,opt_over,key_stack=None,safe_check=False):
  function process_options (line 87) | def process_options(opt):
  function save_options_file (line 107) | def save_options_file(opt):

FILE: train.py
  function main (line 12) | def main():

FILE: util.py
  function red (line 15) | def red(message,**kwargs): return termcolor.colored(str(message),color="...
  function green (line 16) | def green(message,**kwargs): return termcolor.colored(str(message),color...
  function blue (line 17) | def blue(message,**kwargs): return termcolor.colored(str(message),color=...
  function cyan (line 18) | def cyan(message,**kwargs): return termcolor.colored(str(message),color=...
  function yellow (line 19) | def yellow(message,**kwargs): return termcolor.colored(str(message),colo...
  function magenta (line 20) | def magenta(message,**kwargs): return termcolor.colored(str(message),col...
  function grey (line 21) | def grey(message,**kwargs): return termcolor.colored(str(message),color=...
  function get_time (line 23) | def get_time(sec):
  function add_datetime (line 30) | def add_datetime(func):
  function add_functionname (line 37) | def add_functionname(func):
  function pre_post_actions (line 43) | def pre_post_actions(pre=None,post=None):
  class Log (line 55) | class Log:
    method __init__ (line 56) | def __init__(self): pass
    method process (line 57) | def process(self,pid):
    method title (line 59) | def title(self,message):
    method info (line 61) | def info(self,message):
    method options (line 63) | def options(self,opt,level=0):
    method loss_train (line 70) | def loss_train(self,opt,ep,lr,loss,timer):
    method loss_val (line 79) | def loss_val(self,opt,loss):
  function update_timer (line 85) | def update_timer(opt,timer,ep,it_per_ep):
  function move_to_device (line 95) | def move_to_device(X,device):
  function to_dict (line 110) | def to_dict(D,dict_type=dict):
  function get_child_state_dict (line 117) | def get_child_state_dict(state_dict,key):
  function restore_checkpoint (line 120) | def restore_checkpoint(opt,model,load_name=None,resume=False):
  function save_checkpoint (line 143) | def save_checkpoint(opt,model,ep,it,latest=False,children=None):
  function check_socket_open (line 161) | def check_socket_open(hostname,port):
  function get_layer_dims (line 172) | def get_layer_dims(layers):
  function suppress (line 177) | def suppress(stdout=False,stderr=False):
  function colorcode_to_number (line 186) | def colorcode_to_number(code):

FILE: util_vis.py
  function tb_image (line 16) | def tb_image(opt,tb,step,group,name,images,num_vis=None,from_range=(0,1)...
  function preprocess_vis_image (line 27) | def preprocess_vis_image(opt,images,from_range=(0,1),cmap="gray"):
  function dump_images (line 35) | def dump_images(opt,idx,name,images,masks=None,from_range=(0,1),cmap="gr...
  function get_heatmap (line 43) | def get_heatmap(opt,gray,cmap): # [N,H,W]
  function color_border (line 48) | def color_border(images,colors,width=3):
  function vis_cameras (line 58) | def vis_cameras(opt,vis,step,poses=[],colors=["blue","magenta"],plot_dis...
  function get_camera_mesh (line 141) | def get_camera_mesh(pose,depth=1):
  function merge_wireframes (line 157) | def merge_wireframes(wireframe):
  function merge_meshes (line 164) | def merge_meshes(vertices,faces):
  function merge_centers (line 169) | def merge_centers(centers):
  function plot_save_poses (line 177) | def plot_save_poses(opt,fig,pose,pose_ref=None,path=None,ep=None):
  function plot_save_poses_blender (line 220) | def plot_save_poses_blender(opt,fig,pose,pose_ref=None,path=None,ep=None):
  function setup_3D_plot (line 257) | def setup_3D_plot(ax,elev,azim,lim=None):
  function apply_colormap (line 294) | def apply_colormap(image, cmap="viridis"):
  function apply_depth_colormap (line 317) | def apply_depth_colormap(

FILE: warp.py
  function get_normalized_pixel_grid (line 11) | def get_normalized_pixel_grid(opt):
  function get_normalized_pixel_grid_crop (line 19) | def get_normalized_pixel_grid_crop(opt):
  function warp_grid (line 29) | def warp_grid(opt,xy_grid,warp):
  function warp_grid_use_matrix (line 51) | def warp_grid_use_matrix(opt,xy_grid,warp_matrix):
  function warp_corners (line 70) | def warp_corners(opt,warp_param):
  function warp_corners_compose (line 80) | def warp_corners_compose(opt, homo_pert, rot_pert, trans_pert):
  function warp_corners_use_matrix (line 97) | def warp_corners_use_matrix(opt,warp_matrix):
  function check_corners_in_range (line 107) | def check_corners_in_range(opt,warp_param):
  function check_corners_in_range_compose (line 113) | def check_corners_in_range_compose(opt, homo_pert, rot_pert, trans_pert):
  class Lie (line 120) | class Lie():
    method so2_to_SO2 (line 122) | def so2_to_SO2(self,theta): # [...,1]
    method SO2_to_so2 (line 128) | def SO2_to_so2(self,R): # [...,2,2]
    method so2_jacobian (line 132) | def so2_jacobian(self,X,theta): # [...,N,2],[...,1]
    method se2_to_SE2 (line 138) | def se2_to_SE2(self,delta): # [...,3]
    method SE2_to_se2 (line 148) | def SE2_to_se2(self,Rt,eps=1e-7): # [...,2,3]
    method se2_jacobian (line 160) | def se2_jacobian(self,X,delta): # [...,N,2],[...,3]
    method sl3_to_SL3 (line 178) | def sl3_to_SL3(self,h):
    method taylor_A (line 188) | def taylor_A(self,x,nth=10):
    method taylor_B (line 196) | def taylor_B(self,x,nth=10):
    method taylor_C (line 205) | def taylor_C(self,x,nth=10):
    method taylor_D (line 214) | def taylor_D(self,x,nth=10):