Mason-McGough

def raw2outputs(
  raw: torch.Tensor,
  z_vals: torch.Tensor,
  rays_d: torch.Tensor,
  raw_noise_std: float = 0.0,
  white_bkgd: bool = False
) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
  r"""
  Convert the raw NeRF output into RGB and other maps.
  """

Mason-McGough

class PositionalEncoder(nn.Module):
  r"""
  Sine-cosine positional encoder for input points.
  """
  def __init__(
    self,
    d_input: int,
    n_freqs: int,
    log_space: bool = False
  ):

Mason-McGough

import time
import threading

import numpy as np
import cv2 as cv

def _is_window_open(win_name):
    return cv.getWindowProperty(win_name, cv.WND_PROP_VISIBLE) > 0

class VideoGetter():

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
weights = self.calc_volume_weights(di, ray_vector, sigma_sum)
feat_map = torch.sum(weights.unsqueeze(-1) * feat_weighted, dim=-2)

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
sigma_sum, feat_weighted = self.composite_function(sigma, feat)

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
z_shape_obj, z_app_obj, z_shape_bg, z_app_bg = latent_codes

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
from im2scene.giraffe.models import generator
# ...
generator_dict = {
    'simple': generator.Generator,
}

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
n_iter = n_boxes if not_render_background else n_boxes + 1
# ...
for i in range(n_iter):
    if i < n_boxes:  # Object
        p_i, r_i = self.get_evaluation_points(pixels_world,
            camera_world, di, transformations, i)
        z_shape_i, z_app_i = z_shape_obj[:, i], z_app_obj[:, i]
        feat_i, sigma_i = self.decoder(p_i, r_i, z_shape_i, z_app_i)
        # ...

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
class Generator(nn.Module):
    # ...
    def get_latent_codes(self, batch_size=32, tmp=1.):
        z_dim, z_dim_bg = self.z_dim, self.z_dim_bg
        n_boxes = self.get_n_boxes()
        def sample_z(x): return self.sample_z(x, tmp=tmp)
        z_shape_obj = sample_z((batch_size, n_boxes, z_dim))
        z_app_obj = sample_z((batch_size, n_boxes, z_dim))
        z_shape_bg = sample_z((batch_size, z_dim_bg))

Mason-McGough

# adapted from https://github.com/autonomousvision/giraffe (MIT License)
class Renderer(object):
    # ...
    def render_object_rotation(self, img_out_path, batch_size=15, n_steps=32):
        gen = self.generator
        bbox_generator = gen.bounding_box_generator

        n_boxes = bbox_generator.n_boxes

        # Set rotation range