counts dict | dataset stringclasses 1
value | dataset_split stringclasses 1
value | format stringclasses 1
value | log_id stringclasses 10
values | payload_file stringclasses 10
values | payload_sha256 stringclasses 10
values | protocol dict | provenance stringclasses 1
value | schema_version int64 1 1 |
|---|---|---|---|---|---|---|---|---|---|
{
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"frames": 2233,
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} | argoverse2 | train | armgs_prepared_manifest_sidecar | 38f30522-2d43-3ff3-a94b-84887ab1671d | 38f30522-2d43-3ff3-a94b-84887ab1671d.pt | 5f59279baca631797c5dbb3f502394c980dabf0cf820b8ee57a9d90d1eeedc32 | {
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"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"frames": 2233,
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} | argoverse2 | train | armgs_prepared_manifest_sidecar | 4d9e3bdf-7216-3161-8281-72863f3c2bf6 | 4d9e3bdf-7216-3161-8281-72863f3c2bf6.pt | 62647b953d231534bef206ff93598aa68b9fcb8f1660db287c08b356916357e5 | {
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"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2234,
"unique_lidar_sources": 79
} | argoverse2 | train | armgs_prepared_manifest_sidecar | 511b93af-f16e-3195-8628-fbb972a17f74 | 511b93af-f16e-3195-8628-fbb972a17f74.pt | 842fea86e0922cf880cccf879bda6d256825cff142b75141bdb22f178b0ad715 | {
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},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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],
"frames": 2234,
"unique_lidar_sources": 78
} | argoverse2 | train | armgs_prepared_manifest_sidecar | 5f2b8881-3447-3905-99f8-def9d72aae42 | 5f2b8881-3447-3905-99f8-def9d72aae42.pt | 43bb77c376336bead09845452e0cc060005d664d4f723a8a0c4038292aad7ab3 | {
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"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2234,
"unique_lidar_sources": 79
} | argoverse2 | train | armgs_prepared_manifest_sidecar | 756f4ed0-5352-31e4-b3c6-2841b9e779d7 | 756f4ed0-5352-31e4-b3c6-2841b9e779d7.pt | 46e10d7035b940145c5d5eaf3c3a910c8777a9be4761bfa1d3497c0b457e8804 | {
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"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2234,
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} | argoverse2 | train | armgs_prepared_manifest_sidecar | 76c3f58f-9003-3bdb-90a3-b87cfbfa1c3b | 76c3f58f-9003-3bdb-90a3-b87cfbfa1c3b.pt | 94ef69e30c70080c28e260cea406d9364581d8a725fdfebcc36be5369a19e220 | {
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"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2234,
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} | argoverse2 | train | armgs_prepared_manifest_sidecar | 91cded81-9f72-3930-bab7-5d3e3fa0a220 | 91cded81-9f72-3930-bab7-5d3e3fa0a220.pt | f4795901461fd019d4aa261f8199d5ff722c9e239a255645f85a77572bb0cc61 | {
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"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2234,
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} | argoverse2 | train | armgs_prepared_manifest_sidecar | a7bcdabb-f9b7-3c16-806d-3ddf1c2d49a2 | a7bcdabb-f9b7-3c16-806d-3ddf1c2d49a2.pt | ae9ce718b9fba5762de7bfd4ffc39d75693b86ab2dd39a2866de53dbd6aecc07 | {
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"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
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"camera_ids": [
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],
"frames": 2235,
"unique_lidar_sources": 79
} | argoverse2 | train | armgs_prepared_manifest_sidecar | d201af7e-48c8-34ad-be1c-e649af2cb5c2 | d201af7e-48c8-34ad-be1c-e649af2cb5c2.pt | d95f2e39d51f7b3df8a7a930cce37a6deb9aec1b12e5001e26a3e1098401fd4b | {
"actor_policy": {
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"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
{
"actor_tracks": 115,
"camera_ids": [
0,
1,
2,
3,
4,
5,
6
],
"frames": 2233,
"unique_lidar_sources": 79
} | argoverse2 | train | armgs_prepared_manifest_sidecar | f5a3ee79-a131-3f8a-91e9-a6475d778149 | f5a3ee79-a131-3f8a-91e9-a6475d778149.pt | 268448dd6425cff5071fa1bdc9a3227be1ac8c01dace2d4aaed84da05d37cea2 | {
"actor_policy": {
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"lifecycle_bounds": "full_source",
"pose_lookup": "timestamp_interpolation",
"source_annotations": "full",
"training_knots": "selected_lidar_timestamps",
"training_timestamp_match": "exact"
},
"camera_channels": [
"ring_front... | local-cache-only; load only when generated locally by the matching ArmGS preparation command | 1 |
Ours-V2_argoverse2_ArmGS
Preprocessing artifacts for the 10 selected scenes/logs used by this ArmGS workspace. This is not the entire upstream dataset and not an evaluation/trained-model repository.
Includes the CURRENT bottom-cropped all-ring canonical CPU tensor caches and SHA256 sidecars (argoverse2_prepared_crop), not the obsolete uncropped caches. Original Argoverse 2 camera RGB files are not included and remain required.
Layout and use
Files retain their ArmGS-workspace-relative paths (data/... and configs/...). Download to a separate directory and inspect before copying into a matching ArmGS checkout. These are preprocessing artifact files, not a Hugging Face datasets.load_dataset table.
Portability: JSON mappings and Torch caches may contain absolute source-workspace paths. They are preserved as provenance, not silently rewritten. Rebuild canonical manifests using the matching ArmGS preparation command, or carefully rebase path fields for your local dataset/workspace before training. Do not assume this snapshot runs without the original dataset or without path adjustment.
Torch cache safety: .pt files contain prepared data, not trained model checkpoints. Only load trusted artifacts; when inspecting, use CPU torch.load(..., weights_only=True). SHA256 checks detect accidental changes and do not establish trust in an unknown publisher.
Scope: Training checkpoints, optimizer states, training logs, W&B data, credentials, quarantined/obsolete variants and visualization renders are excluded. Decoded dataset RGB PNGs and segmentation-mask PNGs, where included, are training inputs rather than visualization renders.
Upstream data: No new license to upstream data is granted by this snapshot. Users must obtain required source data through the original dataset providers and comply with their terms.
See UPLOAD_FILE_MANIFEST.json for byte sizes and SHA256 digests of all data/configuration files.
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