SYMBOL INDEX (154 symbols across 19 files)

FILE: faces_notexturemap_blender.py
  function load_npy (line 11) | def load_npy(_path):
  function _calculate_fov (line 15) | def _calculate_fov(focal, pixels):
  function setup_ambient_light (line 18) | def setup_ambient_light():
  function create_camera (line 40) | def create_camera(name, position, rot_matrix, fovx, fovy, image_width, i...
  function gen_faces_from_texture_map (line 72) | def gen_faces_from_texture_map(_path, _cam_json_path=None, _wanted_cam_i...

FILE: generate_pseudomesh.py
  function main (line 8) | def main(ply_path: Path, algorithm: str, scale_muls: np.ndarray, no_of_p...
  function read_args (line 100) | def read_args():

FILE: gs_utils.py
  function load_games_pt (line 16) | def load_games_pt(path):
  function get_games_scales_and_rots (line 36) | def get_games_scales_and_rots(data, eps=1e-8):
  function load_ply (line 79) | def load_ply(path, max_sh_degree):
  function normalize_rots (line 119) | def normalize_rots(mat):
  function build_euler_rotation (line 122) | def build_euler_rotation(r):
  function get_scaling (line 146) | def get_scaling(scales: np.ndarray) -> np.ndarray:
  function get_opacity (line 149) | def get_opacity(opacities: np.ndarray) -> np.ndarray:
  function generate_pseudomesh_games (line 153) | def generate_pseudomesh_games(ckpt_data: dict, xyz: np.ndarray, features...
  function generate_pseudomesh_surfels (line 169) | def generate_pseudomesh_surfels(xyz: np.ndarray, features_dc: np.ndarray...
  function generate_pseudomesh_2dgs (line 180) | def generate_pseudomesh_2dgs(xyz: np.ndarray, features_dc: np.ndarray, o...
  function generate_pseudomesh_sugar_2d (line 190) | def generate_pseudomesh_sugar_2d(xyz: np.ndarray, features_dc: np.ndarra...
  function generate_pseudomesh_sugar_3d (line 203) | def generate_pseudomesh_sugar_3d(xyz: np.ndarray, features_dc: np.ndarra...
  function _get_vertices (line 293) | def _get_vertices(origin, scales, rots, scale_mul, no_of_points):
  function gen_2d_pseudomesh (line 306) | def gen_2d_pseudomesh(scale_muls, no_of_points, init_colors, init_opacit...
  function get_rgb_colors (line 353) | def get_rgb_colors(color_features):
  function generate_3dgs_pseudomesh (line 360) | def generate_3dgs_pseudomesh(xyz: np.ndarray, features_dc: np.ndarray, o...

FILE: mesh_optim/2dgs_experiments_run.py
  function main (line 19) | def main():

FILE: mesh_optim/cam_utils.py
  function qvec2rotmat (line 45) | def qvec2rotmat(qvec):
  class Image (line 58) | class Image(BaseImage):
    method qvec2rotmat (line 59) | def qvec2rotmat(self):
  function read_next_bytes (line 63) | def read_next_bytes(fid, num_bytes, format_char_sequence, endian_charact...
  function read_extrinsics_binary (line 75) | def read_extrinsics_binary(path_to_model_file):
  function read_intrinsics_binary (line 110) | def read_intrinsics_binary(path_to_model_file):

FILE: mesh_optim/data.py
  function create_blend_proj_mats (line 12) | def create_blend_proj_mats(camera_angle_x, img_shape, transf_mat, far, n...
  function create_colmap_proj_mats (line 34) | def create_colmap_proj_mats(focal_x, focal_y, img_shape, transf_mat, far...
  class ImageCamDataset (line 55) | class ImageCamDataset(Dataset):
    method __init__ (line 56) | def __init__(self, dataset_path, near, far, imgs_in_ram=True, res=1, t...
    method _load_blender_cameras (line 74) | def _load_blender_cameras(self):
    method _load_colmap_cameras (line 107) | def _load_colmap_cameras(self):
    method load_cameras (line 181) | def load_cameras(self):
    method load_image (line 188) | def load_image(path, res=None, get_shape=False):
    method __len__ (line 204) | def __len__(self):
    method __getitem__ (line 207) | def __getitem__(self, idx):

FILE: mesh_optim/diff_render.py
  function create_obj (line 10) | def create_obj(device):
  function load_pseudomesh (line 99) | def load_pseudomesh(_path):
  function create_proj_mats (line 108) | def create_proj_mats(camera_angle_x, img_size, transf_mat, far, near):
  function create_camera_mats (line 130) | def create_camera_mats(cam_data, img_size=512, near=0.01, far=100., devi...
  function render (line 175) | def render(glctx, verts, colors, faces, cam_data, img_size, device):
  function to_torch (line 290) | def to_torch(*args, device="cpu"):
  function test_render (line 294) | def test_render():
  function render_pseudomesh (line 330) | def render_pseudomesh():
  function render_with_depth_peeling (line 372) | def render_with_depth_peeling(glctx, verts, vert_colors, faces, cam_data...

FILE: mesh_optim/generate_multi_views_circle.py
  function get_depth_map (line 14) | def get_depth_map(model, mvp_mat, width, height, cam_pos, num_layers):
  function get_gray_map (line 31) | def get_gray_map(model, mvp_mat, width, height, color_verts, num_layers):
  function get_normal_map (line 36) | def get_normal_map(model, mvp_mat, width, height, num_layers):
  function get_all_maps (line 41) | def get_all_maps(model, mvp_mat, width, height, cam_pos, num_layers, col...
  function normalize (line 65) | def normalize(v, eps=1e-6):
  function look_at (line 70) | def look_at(eye, target, up):
  function generate_camera_matrices (line 91) | def generate_camera_matrices(target, radius, num_views=20,
  function calculate_mvp (line 128) | def calculate_mvp(focal_x, focal_y, img_shape, view_mat, far, near):
  function create_gif (line 140) | def create_gif(image_paths, output_path, fps):
  function calculate_alphas (line 149) | def calculate_alphas(img1, img2, left_int, dist_interval):
  function main (line 161) | def main(cfg_path, no_sec, fps):

FILE: mesh_optim/lpipsPyTorch/__init__.py
  function lpips (line 6) | def lpips(x: torch.Tensor,
  function get_lpips_model (line 23) | def get_lpips_model(device, net_type: str = 'alex', version: str = '0.1'):

FILE: mesh_optim/lpipsPyTorch/modules/lpips.py
  class LPIPS (line 8) | class LPIPS(nn.Module):
    method __init__ (line 17) | def __init__(self, net_type: str = 'alex', version: str = '0.1'):
    method forward (line 30) | def forward(self, x: torch.Tensor, y: torch.Tensor):

FILE: mesh_optim/lpipsPyTorch/modules/networks.py
  function get_network (line 12) | def get_network(net_type: str):
  class LinLayers (line 23) | class LinLayers(nn.ModuleList):
    method __init__ (line 24) | def __init__(self, n_channels_list: Sequence[int]):
  class BaseNet (line 36) | class BaseNet(nn.Module):
    method __init__ (line 37) | def __init__(self):
    method set_requires_grad (line 46) | def set_requires_grad(self, state: bool):
    method z_score (line 50) | def z_score(self, x: torch.Tensor):
    method forward (line 53) | def forward(self, x: torch.Tensor):
  class SqueezeNet (line 66) | class SqueezeNet(BaseNet):
    method __init__ (line 67) | def __init__(self):
  class AlexNet (line 77) | class AlexNet(BaseNet):
    method __init__ (line 78) | def __init__(self):
  class VGG16 (line 88) | class VGG16(BaseNet):
    method __init__ (line 89) | def __init__(self):

FILE: mesh_optim/lpipsPyTorch/modules/utils.py
  function normalize_activation (line 6) | def normalize_activation(x, eps=1e-10):
  function get_state_dict (line 11) | def get_state_dict(net_type: str = 'alex', version: str = '0.1'):

FILE: mesh_optim/mesh_utils.py
  function hard_prune_mesh (line 6) | def hard_prune_mesh(vertices, faces, vertex_color, mask):
  function soft_prune_mesh (line 19) | def soft_prune_mesh(vertices, faces, vertex_color, mask):
  function prune_mesh (line 38) | def prune_mesh(vertices, faces, vertex_color, mask, mode):
  function prune_optimizer (line 49) | def prune_optimizer(optimizer, mask):

FILE: mesh_optim/metrics.py
  function PILtoTorch (line 26) | def PILtoTorch(pil_image):
  function readImages (line 34) | def readImages(renders_dir, gt_dir, mesh_renders_dir):
  function evaluate (line 65) | def evaluate(model_path, dset_path, algorithm):

FILE: mesh_optim/ml_utils.py
  function _exp_schedule (line 9) | def _exp_schedule(init_val, gamma, timestep):
  function _step_schedule (line 13) | def _step_schedule(curr_val, steps, timestep):
  function dp_schedule (line 17) | def dp_schedule(_type, curr_val, init_val, epoch, params):
  class ColorExponentialLR (line 26) | class ColorExponentialLR(torch.optim.lr_scheduler.ExponentialLR):
    method __init__ (line 27) | def __init__(self, optimizer, gamma, param_group_index=0, last_epoch=-...
    method get_lr (line 31) | def get_lr(self):
  function _calc_bs_mul (line 42) | def _calc_bs_mul(method: str, init_bs: float, curr_bs: float) -> float:
  function get_optimizer (line 52) | def get_optimizer(config: dict, params: dict) -> torch.optim.Optimizer:
  function get_scheduler (line 72) | def get_scheduler(optimizer: torch.optim.Optimizer, params: dict) -> Col...
  class Losser (line 82) | class Losser:
    method __init__ (line 83) | def __init__(self, loss_cfg: dict) -> None:
    method vector_norm_mean (line 143) | def vector_norm_mean(self, loss_data: dict, params: list) -> torch.Ten...
    method img_l1_wrap (line 150) | def img_l1_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method ssim_wrap (line 153) | def ssim_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method mse_wrap (line 156) | def mse_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method pips_wrap (line 159) | def pips_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method dice_wrap (line 167) | def dice_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method delta_wrap (line 170) | def delta_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method psnr_wrap (line 173) | def psnr_wrap(self, loss_data: dict, params: list) -> torch.Tensor:
    method __call__ (line 178) | def __call__(self, loss_data: dict) -> dict:
  function psnr (line 189) | def psnr(pred_img: torch.Tensor, gt_img: torch.Tensor, reduction: str = ...
  function dice_loss (line 195) | def dice_loss(mask_pred: torch.Tensor, mask_gt: torch.Tensor, smooth: fl...
  function norm_loss (line 205) | def norm_loss(data: torch.Tensor, p: int = 1, dim: int = 1) -> torch.Ten...
  function l1_loss (line 209) | def l1_loss(network_output: torch.Tensor, gt: torch.Tensor) -> torch.Ten...
  function mse_loss (line 213) | def mse_loss(network_output: torch.Tensor, gt: torch.Tensor) -> torch.Te...
  function gaussian (line 217) | def gaussian(window_size: int, sigma: float) -> torch.Tensor:
  function create_window (line 222) | def create_window(window_size: int, channel: int) -> torch.Tensor:
  function ssim (line 229) | def ssim(img1: torch.Tensor, img2: torch.Tensor, window_size: int = 11, ...
  function _ssim (line 240) | def _ssim(img1: torch.Tensor, img2: torch.Tensor, window: int, window_si...

FILE: mesh_optim/models.py
  class Pseudomesh (line 7) | class Pseudomesh(nn.Module):
    method __init__ (line 8) | def __init__(self, config):
  class PseudomeshRenderer (line 19) | class PseudomeshRenderer():
    method __init__ (line 20) | def __init__(self, config):
    method create_model (line 25) | def create_model(cls, config):
    method vert_requires_grad (line 32) | def vert_requires_grad(self):
    method vert_col_requires_grad (line 36) | def vert_col_requires_grad(self):
    method set_values (line 39) | def set_values(self, vertices, faces, vertex_colors, grad_acc=None):
    method acc_grad (line 62) | def acc_grad(self):
    method reset_acc_grad (line 67) | def reset_acc_grad(self):
    method to (line 71) | def to(self, device):
    method __call__ (line 75) | def __call__(self, mvp_mat, width, height, num_layers):
    method get_depth_map (line 112) | def get_depth_map(self, mvp_mat, width, height, cam_pos, num_layers):
    method get_gray_map (line 155) | def get_gray_map(self, mvp_mat, width, height, num_layers, color_verts):
    method get_normal_map (line 191) | def get_normal_map(self, mvp_mat, width, height, num_layers):
    method render_all_maps (line 260) | def render_all_maps(self, mvp_mat, width, height, cam_pos, num_layers,...

FILE: mesh_optim/optimize_pseudomesh.py
  function _load_config (line 26) | def _load_config(path):
  function setup_logger (line 31) | def setup_logger(config):
  function iter_pass (line 45) | def iter_pass(model: PseudomeshRenderer, data: dict, config: dict, loss_...
  function wandb_log (line 93) | def wandb_log(losses: dict, step: int, data_to_loss: dict = None, mode: ...
  function _collect_imgs_for_logs (line 136) | def _collect_imgs_for_logs(data_to_loss:dict, container: dict, _iter: in...
  function _save_ckpt (line 151) | def _save_ckpt(ckpt_dir: Path, epoch: int, model: PseudomeshRenderer, op...
  function batch_to_device (line 163) | def batch_to_device(data, device):
  function pruning (line 168) | def pruning(model, optimizer, alpha_eps, grad_eps, mode, _type):
  function train (line 195) | def train(pseudomesh: PseudomeshRenderer, dloader: DataLoader, config: d...
  function test (line 306) | def test(pseudomesh: PseudomeshRenderer, dloader: DataLoader, config: di...
  function prepare_output_dir (line 333) | def prepare_output_dir(config: dict, cfg_path: str) -> None:
  function setup_wandb (line 353) | def setup_wandb(config: dict) -> None:
  function _load_best_model (line 369) | def _load_best_model(config: dict) -> PseudomeshRenderer:
  function _save_results (line 383) | def _save_results(results: dict, config: dict) -> None:
  function main (line 389) | def main() -> None:

FILE: mesh_optim/render_pseudomesh.py
  function _load_config (line 14) | def _load_config(path):
  function render_img (line 20) | def render_img(model, mvp_mat, img_shape, white_background, depth_steps,...
  function main (line 35) | def main(cfg_path, method, white_background):

FILE: scripts/visualize_cameras_nerf_blender.py
  function _calculate_fov (line 16) | def _calculate_fov(focal, pixels):
  function create_camera (line 20) | def create_camera(name, position, rot_matrix, fovx, fovy, image_width, i...
  function main (line 52) | def main():