configs/evaluate_semantic_bdd.yaml

defaults:
  - dataset: bdd_seg
  - model: dino_downsampler
  - renderer: pixelnerf
  - training: semantic
  - validation: semantic
  - downstream: semantic
  - _self_

training_type: "downstream_training"
mode: "nvs"
seed: 0
backend: null
nproc_per_node: null
with_amp: false
name: "training"
batch_size: 1
gradient_accum_factor: 1
num_workers: 6

renderer:
  n_coarse : 32
  n_fine : 0
  n_fine_depth : 0
  depth_std : 1.0
  sched : []
  white_bkgd : false
  lindisp: true
  hard_alpha_cap: true
  render_mode: volumetric
  eval_batch_size: 65536
  normalize_dino: true

# eval_visualize: [0, 1, 2, 3]

output:
  path: "out/evaluation-paper"
  unique_id: evaluation-bdd

checkpoint: "<PATH-FEATURE-CHECKPOINT>.pt"

evaluations:
  - type: seg
    agg_type: unsup_seg
    args:
      n_classes: 19
      gt_classes: 19

downstream:
  input_dim: 768