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 / zero_experience_required

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

Force PyTorch to be single threaded as

this improves performance considerably