# Data Dictionary EgoSpatial-CL is distributed as tar shards. Each shard contains one or more complete episode directories. Each episode is a synchronized sequence of front RGB images, semantic-segmentation images, LiDAR point clouds, ego-vehicle state/control rows, and episode metadata. ## Dataset-Level Structure ```text shards///__XXXXXX.tar ``` After extraction, each tar shard reconstructs episode directories using this layout: ```text //episode_XXXX/ images/ labels/ lidar/ meta.json state.csv index.csv ``` The source dataset before packaging uses the same episode contract under each town directory: ```text /episode_XXXX/ images/ labels/ lidar/ meta.json state.csv index.csv ``` Release-level episode identifiers: - `episode_id` is a town-local integer identifier inherited from the original episode directory naming scheme. - `episode` is the town-local directory name, for example `episode_0000`. - `episode_uid` in `benchmark_manifest.json` is the unique release-level identifier formatted as `//`. - `global_episode_index` in `benchmark_manifest.json` is a unique integer index assigned in manifest order. ## Core Counts ```text 7 towns 7 compact domains 10 spatial slots per town/domain pair 490 episodes 1,000 synchronized saved samples per episode 490,000 synchronized samples 392 train episodes 49 validation episodes 49 test episodes 401 tar shards ``` ## Towns | Town | Episodes | Notes | |---|---:|---| | `Town01_Opt` | 70 | CARLA optimized town map. | | `Town02_Opt` | 70 | CARLA optimized town map. | | `Town04_Opt` | 70 | CARLA optimized town map. | | `Town05_Opt` | 70 | CARLA optimized town map. | | `Town06` | 70 | CARLA town map. | | `Town07` | 70 | CARLA town map. | | `Town10HD_Opt` | 70 | CARLA optimized high-definition town map. | ## Compact Domains | `domain_id` | `domain_name` | Weather condition | NPC variant | Requested vehicles | Requested walkers | |---:|---|---|---|---:|---:| | 0 | `clear__NPC00_none` | clear | no NPC traffic | 0 | 0 | | 1 | `night__NPC00_none` | night | no NPC traffic | 0 | 0 | | 2 | `fog__NPC00_none` | fog | no NPC traffic | 0 | 0 | | 3 | `hardrain__NPC00_none` | hard rain | no NPC traffic | 0 | 0 | | 4 | `clear__NPC11_veh_high` | clear | vehicle traffic | 50 | 0 | | 5 | `hardrain__NPC11_veh_high` | hard rain | vehicle traffic | 50 | 0 | | 6 | `clear__NPC31_both_high` | clear | vehicle and pedestrian traffic | 50 | 200 | `vehicles_spawned` and `walkers_spawned` in `meta.json` may be lower than requested values when valid spawn points or navigation positions are unavailable in a town/episode. ## Modalities | Path | Type | Cardinality per episode | Description | |---|---|---:|---| | `images/` | PNG sequence | 1,000 files | Front RGB camera frames. File names are zero-padded simulator frame IDs, for example `000804.png`. | | `labels/` | PNG sequence | 1,000 files | Semantic-segmentation camera output aligned with RGB frames and saved after CARLA `CityScapesPalette` conversion. | | `lidar/` | NumPy arrays | 1,000 files | LiDAR point clouds stored as `.npy` arrays. File names match the synchronized simulator frame ID. | | `state.csv` | CSV | 1,000 data rows plus header | Ego-vehicle pose, kinematics, control state, IMU, and GNSS values. | | `index.csv` | CSV | 1,000 data rows plus header | Per-frame mapping between synchronized RGB, semantic-segmentation, and LiDAR files. | | `meta.json` | JSON | 1 file | Episode-level simulator, weather, ego vehicle, sensor, seed, and NPC metadata. | ## Synchronization Each saved sample corresponds to one simulator frame selected after advancing `capture_stride` synchronous ticks. For release v1.0.0: ```text fixed_delta_seconds = 0.05 capture_stride_frames = 10 nominal saved-sample interval = 0.5 simulation seconds samples_per_episode = 1,000 ``` The `frame` value is the CARLA simulator frame ID. It is used consistently in `state.csv`, `index.csv`, image file names, semantic-label file names, and LiDAR file names. ## `index.csv` `index.csv` links every saved frame to the modality files inside the same episode directory. Example: ```text frame,rgb_path,semseg_path,lidar_path 804,images/000804.png,labels/000804.png,lidar/000804.npy ``` | Field | Type | Unit / format | Description | |---|---|---|---| | `frame` | integer | CARLA frame ID | Simulator frame associated with the synchronized sample. | | `rgb_path` | string | relative path | Path from the episode directory to the front RGB PNG frame. | | `semseg_path` | string | relative path | Path from the episode directory to the semantic-segmentation PNG frame. Empty only if semantic segmentation was disabled; in release v1.0.0 it is populated. | | `lidar_path` | string | relative path | Path from the episode directory to the LiDAR `.npy` frame. Empty only if LiDAR was disabled; in release v1.0.0 it is populated. | ## `state.csv` `state.csv` stores one synchronized ego-state row per saved sample. Values are recorded after the simulator tick that produced the synchronized sensor measurements. Coordinate and rotation fields follow CARLA/Unreal conventions unless stated otherwise. World positions are in meters. Vehicle rotation angles are in degrees. Ego velocity is in meters per second. Ego acceleration and IMU acceleration are in meters per second squared. Actor angular velocity from `get_angular_velocity()` is in degrees per second; IMU gyroscope values are in radians per second. | Field | Type | Unit / range | Description | |---|---|---|---| | `frame` | integer | CARLA frame ID | Simulator frame associated with this saved sample. | | `sim_time` | float | seconds | Elapsed simulation time from the CARLA world snapshot timestamp. | | `ts_platform` | float | Unix timestamp, seconds | Host/platform wall-clock time when the row was written. Use `sim_time` for simulation-time analyses. | | `ego_x` | float | meters | Ego vehicle world-frame x position. | | `ego_y` | float | meters | Ego vehicle world-frame y position. | | `ego_z` | float | meters | Ego vehicle world-frame z position. | | `ego_roll` | float | degrees | Ego vehicle roll angle from the CARLA transform. | | `ego_pitch` | float | degrees | Ego vehicle pitch angle from the CARLA transform. | | `ego_yaw` | float | degrees | Ego vehicle yaw/heading angle from the CARLA transform. | | `vel_x` | float | m/s | Ego vehicle world-frame velocity x component. | | `vel_y` | float | m/s | Ego vehicle world-frame velocity y component. | | `vel_z` | float | m/s | Ego vehicle world-frame velocity z component. | | `acc_x` | float | m/s^2 | Ego vehicle world-frame acceleration x component returned by the actor state. | | `acc_y` | float | m/s^2 | Ego vehicle world-frame acceleration y component returned by the actor state. | | `acc_z` | float | m/s^2 | Ego vehicle world-frame acceleration z component returned by the actor state. | | `angvel_x` | float | deg/s | Ego vehicle angular-velocity x component returned by the actor state. | | `angvel_y` | float | deg/s | Ego vehicle angular-velocity y component returned by the actor state. | | `angvel_z` | float | deg/s | Ego vehicle angular-velocity z component returned by the actor state. | | `throttle` | float | [0, 1] | Applied vehicle throttle command. | | `steer` | float | [-1, 1] | Applied steering command. Negative and positive values correspond to opposite steering directions in CARLA's vehicle-control convention. | | `brake` | float | [0, 1] | Applied brake command. | | `hand_brake` | integer | 0 or 1 | Whether the hand brake is active. | | `reverse` | integer | 0 or 1 | Whether reverse gear/direction is active. | | `gear` | integer | CARLA gear value | Current vehicle gear reported by the control object. | | `imu_accel_x` | float | m/s^2 | IMU-frame linear acceleration x component from `sensor.other.imu`. | | `imu_accel_y` | float | m/s^2 | IMU-frame linear acceleration y component from `sensor.other.imu`. | | `imu_accel_z` | float | m/s^2 | IMU-frame linear acceleration z component from `sensor.other.imu`; includes gravity according to CARLA IMU behavior. | | `imu_gyro_x` | float | rad/s | IMU-frame angular velocity x component from `sensor.other.imu`. | | `imu_gyro_y` | float | rad/s | IMU-frame angular velocity y component from `sensor.other.imu`. | | `imu_gyro_z` | float | rad/s | IMU-frame angular velocity z component from `sensor.other.imu`. | | `imu_compass` | float | radians | Compass orientation with respect to CARLA north. | | `gnss_lat` | float | degrees | GNSS latitude from `sensor.other.gnss`. | | `gnss_lon` | float | degrees | GNSS longitude from `sensor.other.gnss`. | | `gnss_alt` | float | meters | GNSS altitude from `sensor.other.gnss`. | ## Image Files RGB frames are saved as PNG files after converting CARLA camera raw data from BGRA to RGB. The release uses: ```text image width = 800 pixels image height = 600 pixels field of view = 90 degrees sensor tick = 0.05 seconds camera transform relative to ego = x 1.5 m, y 0.0 m, z 1.7 m, pitch -5 deg, yaw 0 deg, roll 0 deg ``` ## Semantic-Segmentation Files Semantic-segmentation frames are saved as PNG files aligned with the RGB camera. During collection, the CARLA semantic camera output is converted with `carla.ColorConverter.CityScapesPalette` before saving. Therefore, release labels are color-encoded semantic images rather than single-channel integer class-index masks. Users needing class-index tensors should convert the palette colors to class IDs consistently with CARLA's semantic-label definitions for the simulator version used in the release. ## LiDAR Files Each LiDAR file is a NumPy `.npy` array written with `allow_pickle=False`. ```text shape = (N, 4) dtype = float32 columns = x, y, z, intensity ``` | Column | Type | Unit / range | Description | |---|---|---|---| | `x` | float32 | meters | Point x coordinate in the LiDAR sensor frame. | | `y` | float32 | meters | Point y coordinate in the LiDAR sensor frame. | | `z` | float32 | meters | Point z coordinate in the LiDAR sensor frame. | | `intensity` | float32 | unitless | LiDAR return intensity reported by CARLA. | `N` can vary across frames because it depends on ray returns, scene geometry, and simulator conditions. Release v1.0.0 LiDAR generation parameters: ```text sensor type = sensor.lidar.ray_cast transform relative to ego = x 0.0 m, y 0.0 m, z 2.0 m range = 50.0 m points_per_second = 100000 channels = 32 upper_fov = 10.0 deg lower_fov = -30.0 deg rotation_frequency = 20 Hz sensor_tick = 0.05 seconds ``` ## `meta.json` `meta.json` stores episode-level metadata. The table below describes the principal fields observed in release v1.0.0. | Field | Type | Description | |---|---|---| | `created_utc` | string | UTC timestamp when the episode metadata file was written. | | `carla_version` | string | Simulator version used for generation. | | `host` | string | CARLA server host used during collection. | | `port` | integer | CARLA RPC port used during collection. | | `map` | string | CARLA map loaded for the episode. | | `seed` | integer | Episode seed. Release rule: `seed = 12345 + 17 * episode_id`. | | `fixed_delta_seconds` | float | Fixed synchronous simulation step in seconds. | | `synchronous_mode` | boolean | Whether synchronous mode was enabled. | | `no_rendering_mode_capture` | boolean | Whether CARLA no-rendering mode was used during capture. It is `false` for release v1.0.0 because camera data are recorded. | | `weather` | string | High-level weather/domain label used by the collector. | | `weather_params` | object | CARLA weather parameters actually recorded from the world. | | `weather_overrides` | object or null | Explicit weather overrides applied beyond the named preset, if any. | | `ego` | object | Ego-vehicle blueprint, spawn transform, autopilot flag, and traffic-manager settings. | | `npcs` | object | Requested/spawned background vehicles and walkers plus NPC traffic-manager parameters. | | `sensors` | object | Sensor availability, ticks, camera geometry, and camera transform. | | `shutdown` | object | Collector shutdown/parking settings used after episode generation. | ### `meta.json.weather_params` | Field | Type | Unit / range | Description | |---|---|---|---| | `cloudiness` | float | percentage-like CARLA value | Cloud coverage parameter. | | `precipitation` | float | percentage-like CARLA value | Rain intensity parameter. | | `precipitation_deposits` | float | percentage-like CARLA value | Wet-road/rain-deposit parameter. | | `wetness` | float | percentage-like CARLA value | Surface wetness parameter. | | `wind_intensity` | float | percentage-like CARLA value | Wind intensity parameter. | | `fog_density` | float | percentage-like CARLA value | Fog density parameter. | | `fog_distance` | float | meters / CARLA world parameter | Fog distance parameter. | | `fog_falloff` | float | CARLA world parameter | Fog falloff parameter. | | `sun_altitude_angle` | float | degrees | Sun altitude angle. Negative values correspond to night-like lighting. | | `sun_azimuth_angle` | float | degrees | Sun azimuth angle. | | `scattering_intensity` | float | CARLA world parameter | Atmospheric scattering intensity. | | `mie_scattering_scale` | float | CARLA world parameter | Mie scattering scale. | | `rayleigh_scattering_scale` | float | CARLA world parameter | Rayleigh scattering scale. | | `dust_storm` | float | percentage-like CARLA value | Dust storm parameter. | ### `meta.json.ego` | Field | Type | Description | |---|---|---| | `blueprint` | string | Ego vehicle actor blueprint used in the simulator. | | `transform_spawn.location.{x,y,z}` | float | Ego spawn location in world coordinates, meters. | | `transform_spawn.rotation.{pitch,roll,yaw}` | float | Ego spawn rotation in degrees. | | `autopilot` | boolean | Whether CARLA Traffic Manager autopilot controlled the ego vehicle. | | `traffic_manager_port` | integer or null | Traffic Manager port used by the ego autopilot. | | `traffic_manager.distance_to_leading` | float | Target distance to leading vehicle, meters. | | `traffic_manager.ignore_lights_pct` | float | Percentage probability for ignoring traffic lights. | | `traffic_manager.ignore_signs_pct` | float | Percentage probability for ignoring traffic signs. | | `traffic_manager.ignore_walkers_pct` | float | Percentage probability for ignoring walkers. | | `traffic_manager.speed_diff_pct` | float | Traffic Manager speed difference percentage relative to speed limits. | | `traffic_manager.auto_lane_change` | boolean | Whether automatic lane changing was enabled for the ego vehicle. | | `traffic_manager.hybrid_physics` | boolean | Whether Traffic Manager hybrid physics was enabled. | | `traffic_manager.hybrid_radius` | float | Hybrid physics radius, meters. | ### `meta.json.npcs` | Field | Type | Description | |---|---|---| | `npc_seed` | integer | Deterministic seed used for NPC vehicle and walker spawning. | | `vehicles_requested` | integer | Number of NPC vehicles requested by the domain configuration. | | `vehicles_spawned` | integer | Number of NPC vehicles successfully spawned. | | `walkers_requested` | integer | Number of pedestrians requested by the domain configuration. | | `walkers_spawned` | integer | Number of pedestrians successfully spawned. | | `pedestrians_cross_factor` | float | CARLA pedestrian crossing factor used for the episode. | | `npc_vehicle_filter` | string | Blueprint filter used for NPC vehicle selection. | | `npc_min_dist_to_ego` | float | Minimum spawn distance from ego vehicle, meters. | | `tm_npc_speed_diff_pct` | float | Traffic Manager speed difference percentage for NPC vehicles. | | `tm_npc_auto_lane_change` | boolean | Whether automatic lane changing was enabled for NPC vehicles. | | `walker_speed_min` | float | Minimum walker speed, m/s. | | `walker_speed_max` | float | Maximum walker speed, m/s. | ### `meta.json.sensors` | Field | Type | Description | |---|---|---| | `rgb.w` | integer | RGB image width in pixels. | | `rgb.h` | integer | RGB image height in pixels. | | `rgb.fov` | float | RGB camera field of view in degrees. | | `rgb.tick` | float | RGB sensor tick in seconds. | | `rgb.transform.location.{x,y,z}` | float | RGB camera position relative to the ego vehicle, meters. | | `rgb.transform.rotation.{pitch,roll,yaw}` | float | RGB camera rotation relative to the ego vehicle, degrees. | | `semseg` | boolean | Whether semantic-segmentation images were recorded. | | `lidar` | boolean | Whether LiDAR point clouds were recorded. | | `imu.tick` | float | IMU sensor tick in seconds. | | `gnss.tick` | float | GNSS sensor tick in seconds. | ## Release Manifest Files ### `dataset_info.json` Dataset-level summary used for release metadata. | Field | Type | Description | |---|---|---| | `schema_version` | string | Version of the release metadata schema. | | `name` | string | Machine-readable dataset release name. | | `pretty_name` | string | Human-readable short dataset name. | | `title` | string | Full citable dataset title. | | `version` | string | Dataset release version. | | `license` | string | Hugging Face license identifier for the dataset. | | `repository` | string | Public Hugging Face dataset URL. | | `code_repository` | string | Public code repository URL. | | `doi_status` | string | DOI state; remains pending until final release freeze. | | `release_status` | string | Release preparation state. `release_candidate_v1_0_0` indicates final local review before DOI and public freeze. | | `format` | string | Distribution format, `tar_shards` for v1.0.0. | | `episode_order` | string | Episode ordering convention used by the packed release. | | `num_towns` | integer | Number of towns. | | `num_domains_per_town` | integer | Number of compact domains per town. | | `num_base_tasks_expected` | integer | Number of town/domain combinations. | | `num_episodes` | integer | Number of complete episodes. | | `expected_samples_per_episode` | integer | Expected saved synchronized samples per episode. | | `expected_samples_total` | integer | Expected total synchronized samples. | | `num_shards` | integer | Number of tar shards. | | `total_shard_bytes` | integer | Sum of tar-shard byte sizes. | | `splits` | object | Train/validation/test episode counts using technical labels `train`, `val`, and `test`. | | `split_counts_by_town` | object | Split counts for each town. | | `split_aliases` | object | Human-readable aliases for technical split labels, for example `val` = validation. | | `episode_identifier_scope` | object | Scope and uniqueness rules for episode identifiers. | | `modalities` | array | Modalities included in the release. | | `simulator` | string | Simulator version. | | `provenance` | object | Generation provenance summary. | | `notes` | array | Release notes. | ### `benchmark_manifest.json` Episode-level and shard-level manifest. Despite the field name `benchmark_name`, the v1.0.0 public artifact is described primarily as a dataset with benchmark-ready splits. | Field | Type | Description | |---|---|---| | `benchmark_name` | string | Machine-readable release/protocol identifier kept for compatibility. | | `dataset_release_name` | string | Machine-readable dataset release identifier. | | `dataset_name` | string | Human-readable dataset name. | | `title` | string | Full citable title. | | `version` | string | Dataset release version. | | `license` | string | Dataset license identifier. | | `repository` | string | Public Hugging Face dataset URL. | | `code_repository` | string | Public code repository URL. | | `doi_status` | string | DOI state. | | `release_status` | string | Release preparation state. | | `compact_domains` | array | Domain definitions and requested NPC counts. | | `episode_order` | string | Episode ordering convention. | | `episodes` | array | One record per episode with town, split, domain, spatial slot, spawn index, and weather summary. | | `shards` | array | One record per tar shard with path, size, checksum, split, town, and included episodes. | | `towns` | array | Towns included in the release. | | `warnings` | array | Packaging/manifest warnings; empty for the validated v1.0.0 metadata state. | | `provenance` | object | Generation provenance summary. | #### `benchmark_manifest.json.episodes[]` Each object in `episodes` describes one complete episode. Release-level uniqueness is provided by `episode_uid` and `global_episode_index`. | Field | Type | Description | |---|---|---| | `global_episode_index` | integer | Unique release-level integer index assigned in manifest order, from 0 to 489. | | `episode_uid` | string | Unique release-level episode identifier formatted as `//`. | | `episode` | string | Town-local episode directory name, for example `episode_0000`. | | `episode_id` | integer | Town-local episode index inherited from the generated episode naming scheme, from 0 to 69 within each town. | | `town` | string | CARLA town for the episode. | | `split` | string | Technical split label: `train`, `val`, or `test`. | | `domain_id` | integer | Compact domain identifier from 0 to 6. | | `domain_name` | string | Compact domain name combining condition and NPC variant. | | `condition` | string | Public condition label such as `clear`, `night`, `fog`, or `hardrain`. | | `npc_variant` | string | Compact NPC traffic variant. | | `spatial_slot` | integer | Slot index within the 10 selected spawn slots for the town/domain pair. | | `spawn_index` | integer | CARLA spawn-point index used for the ego vehicle. | | `meta_summary` | object | Selected episode metadata copied from `meta.json`, including map, seed, weather label, and key weather parameters. | #### `benchmark_manifest.json.shards[]` Each object in `shards` describes one packed tar shard. | Field | Type | Description | |---|---|---| | `path` | string | Relative path to the tar shard inside the dataset repository. | | `sha256` | string | SHA256 checksum of the tar shard payload. | | `bytes` | integer | Tar shard size in bytes. | | `town` | string | Town represented by the shard. | | `split` | string | Technical split label represented by the shard: `train`, `val`, or `test`. | | `num_episodes` | integer | Number of complete episode directories stored in the shard. | | `episodes` | array | Episode directory names included in the shard. | ### `shards_manifest.csv` Shard-level tabular manifest. | Field | Type | Description | |---|---|---| | `path` | string | Relative path to a tar shard in the HF dataset repository. | | `sha256` | string | SHA256 checksum of the tar shard. | | `bytes` | integer | Tar shard size in bytes. | | `town` | string | Town represented by the shard. | | `split` | string | Split represented by the shard: `train`, `val`, or `test`. | | `num_episodes` | integer | Number of complete episodes stored in the shard. | | `episodes` | string | Pipe-separated list of episode directory names included in the shard. | ### `checksums.sha256` Standard SHA256 checksum file for tar shards. ```text ``` ### `spatial_splits.json` Frozen spatial split by town and split. Values are CARLA spawn indices assigned to train, validation, or test. ## Missing Values And Caveats - Release v1.0.0 expects all synchronized modality paths in `index.csv` to be populated. - `ts_platform` is wall-clock time and should not be used as a simulation-time axis. - Semantic segmentation labels are palette-color PNGs, not class-index rasters. - This release does not include dense depth, optical flow, 2D/3D bounding boxes, tracking IDs, or multi-view camera annotations. - The dataset contains simulated data. Simulator-specific coordinate conventions, rendering behavior, traffic-manager behavior, and semantic labels should be reported when comparing against real-world datasets.