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Miss sementic dataset for gibson objectnav: data/scene_datasets/gibson_semantic #4

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Hoyyyaard opened this issue Jan 8, 2023 · 1 comment

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@Hoyyyaard
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Hi! When I wanted to run the zer/objectnav dataset , it occurred an error as followed:

File "anaconda3/envs/zsvlnhl/lib/python3.8/site-packages/habitat_sim/simulator.py", line 200, in _config_backend
super().init(config.sim_cfg, config.metadata_mediator)
AssertionError: ESP_CHECK failed: Missing (at least) one of scene dataset attributes, stage attributes, or dataset scene attributes for scene 'data/scene_datasets/gibson_semantic/Markleeville.glb'. Likely an invalid scene name.

But I cannot find the dataset "data/scene_datasets/gibson_semantic" . Can you please inform me the link of the dataset ? Thank you very much!

some config:

habitat:
environment:
type: "gibson"
max_episode_steps: 100

simulator:
turn_angle: 30
tilt_angle: 30
action_space_config: "v1"
agent_0:
sensors: ['rgb_sensor']
height: 0.88
radius: 0.18
habitat_sim_v0:
gpu_device_id: 0
allow_sliding: False
rgb_sensor:
width: 128
height: 128
hfov: 79
position: [0, 0.88, 0]

task:
type: ObjectNav-v1
end_on_success: True
reward_measure: "distance_to_goal_reward"
success_measure: "spl"

possible_actions: ["stop", "move_forward", "turn_left", "turn_right"]

sensors: ['OBJECTgoaltext_sensor', 'compass_sensor', 'gps_sensor']
goal_sensor_uuid: objectgoal

measurements: ['distance_to_goal', 'success', 'spl', 'soft_spl', 'distance_to_goal_reward']

distance_to_goal:
  distance_to: VIEW_POINTS
success:
  success_distance: 0.1

dataset:
type: ObjectNav-v1
split: train
data_path: "data/datasets/zer/objectnav/gibson/v1/{split}/{split}.json.gz"
scenes_dir: "data/scene_datasets/"

habitat_baselines:
base_task_config_path: "exp_config/base_task_config/objectnav_gibson.yaml"
cmd_trailing_opts: ["habitat.environment.iterator_options.max_scene_repeat_steps", "50000"]
simulator_gpu_id: 0
torch_gpu_id: 0
video_option: []
tensorboard_dir: "tb"
video_dir: "video_dir"
test_episode_count: -1
eval_ckpt_path_dir: "data/new_checkpoints"
num_environments: 4
sensors: ["rgb_sensor"]
num_updates: 270000
log_interval: 10
num_checkpoints: 100

Force PyTorch to be single threaded as

this improves performance considerably

force_torch_single_threaded: True

eval:
use_ckpt_config: False
split: val

rl:
policy:
name: "NavNetPolicy"

ppo:
  # para for policy network
  backbone: fast_resnet9
  goal_backbone: clip_text
  rnn_type: GRU
  num_recurrent_layers: 2

  num_steps: 128

  hidden_size: 128
  input_size: 128
  visual_encoder_embedding_size: 512
  goal_embedding_size: 128

  visual_obs_inputs: ['rgb', "imagegoal_sensor_v2"]

  random_crop: False
  rgb_color_jitter: 0.0
  tie_inputs_and_goal_param: False

  task_type_embed: False
  task_type_embed_size: 64

habitat:
simulator:
turn_angle: 30

@ziadalh
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ziadalh commented Feb 17, 2023

It looks that the Gibson dataset is missing or not in the correct path. You can download the Gibson dataset from here and the relevant semantic annotations from here. Make sure that the downloaded dataset is in the correct path data/scene_datasets/gibson_semantic or change that path in the configuration file.

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