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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
repo_id: string
release: string
complete: bool
state: string
expected_shards: int64
verified_shards: int64
expected_source_bytes: int64
verified_source_bytes: int64
expected_files: int64
verified_files: int64
updated_utc: timestamp[s]
components: list<item: struct<name: string, files: int64, bytes: int64, kinds: struct<annotation: int64, canonic (... 99 chars omitted)
  child 0, item: struct<name: string, files: int64, bytes: int64, kinds: struct<annotation: int64, canonical_label: i (... 87 chars omitted)
      child 0, name: string
      child 1, files: int64
      child 2, bytes: int64
      child 3, kinds: struct<annotation: int64, canonical_label: int64, filtered_gt: int64, calibration: int64, depth: int (... 15 chars omitted)
          child 0, annotation: int64
          child 1, canonical_label: int64
          child 2, filtered_gt: int64
          child 3, calibration: int64
          child 4, depth: int64
          child 5, rgb: int64
      child 4, shards: int64
shards: list<item: struct<key: string, component: string, path: string, files: int64, kinds: struct<rgb: int (... 454 chars omitted)
  child 0, item: struct<key: string, component: string, path: string, files: int64, kinds: struct<rgb: int64, annotat (... 442 chars omitted)
      child 0, key: string
      child 1, component: string
      child 2, path: string
      child 3, files: int64
      child 4, kinds: struct<rgb: int64, annotation: int64, canonical_label: int64, filtered_gt: int64, calibration: int6
...
_frames: int64
      child 4, H2O/val: struct<rgb_frames: int64, official_pose_frames: int64, canonical_refit_frames: int64>
          child 0, rgb_frames: int64
          child 1, official_pose_frames: int64
          child 2, canonical_refit_frames: int64
      child 5, H2O/test: struct<rgb_frames: int64, official_pose_frames: int64, canonical_refit_frames: int64>
          child 0, rgb_frames: int64
          child 1, official_pose_frames: int64
          child 2, canonical_refit_frames: int64
  child 5, source_gaps: list<item: struct<recording: string, frames: list<item: int64>>>
      child 0, item: struct<recording: string, frames: list<item: int64>>
          child 0, recording: string
          child 1, frames: list<item: int64>
              child 0, item: int64
  child 6, encoding: string
  child 7, labels: string
  child 8, base_release: string
  child 9, base_revision: string
  child 10, g2_inventory_sha256: string
  child 11, local_completion: struct<status: string, root: string, files: int64, source_bytes: int64, copied_files: int64, copied_ (... 46 chars omitted)
      child 0, status: string
      child 1, root: string
      child 2, files: int64
      child 3, source_bytes: int64
      child 4, copied_files: int64
      child 5, copied_bytes: int64
      child 6, all_files_sha256_verified: bool
source_content_unchanged: bool
preserve_splits: bool
image_format: string
sha256: string
width: int64
height: int64
path: string
kind: string
bytes: int64
mode: string
to
{'path': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string'), 'kind': Value('string'), 'image_format': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'mode': Value('string')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1835, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 621, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 361, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2381, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2309, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              repo_id: string
              release: string
              complete: bool
              state: string
              expected_shards: int64
              verified_shards: int64
              expected_source_bytes: int64
              verified_source_bytes: int64
              expected_files: int64
              verified_files: int64
              updated_utc: timestamp[s]
              components: list<item: struct<name: string, files: int64, bytes: int64, kinds: struct<annotation: int64, canonic (... 99 chars omitted)
                child 0, item: struct<name: string, files: int64, bytes: int64, kinds: struct<annotation: int64, canonical_label: i (... 87 chars omitted)
                    child 0, name: string
                    child 1, files: int64
                    child 2, bytes: int64
                    child 3, kinds: struct<annotation: int64, canonical_label: int64, filtered_gt: int64, calibration: int64, depth: int (... 15 chars omitted)
                        child 0, annotation: int64
                        child 1, canonical_label: int64
                        child 2, filtered_gt: int64
                        child 3, calibration: int64
                        child 4, depth: int64
                        child 5, rgb: int64
                    child 4, shards: int64
              shards: list<item: struct<key: string, component: string, path: string, files: int64, kinds: struct<rgb: int (... 454 chars omitted)
                child 0, item: struct<key: string, component: string, path: string, files: int64, kinds: struct<rgb: int64, annotat (... 442 chars omitted)
                    child 0, key: string
                    child 1, component: string
                    child 2, path: string
                    child 3, files: int64
                    child 4, kinds: struct<rgb: int64, annotation: int64, canonical_label: int64, filtered_gt: int64, calibration: int6
              ...
              _frames: int64
                    child 4, H2O/val: struct<rgb_frames: int64, official_pose_frames: int64, canonical_refit_frames: int64>
                        child 0, rgb_frames: int64
                        child 1, official_pose_frames: int64
                        child 2, canonical_refit_frames: int64
                    child 5, H2O/test: struct<rgb_frames: int64, official_pose_frames: int64, canonical_refit_frames: int64>
                        child 0, rgb_frames: int64
                        child 1, official_pose_frames: int64
                        child 2, canonical_refit_frames: int64
                child 5, source_gaps: list<item: struct<recording: string, frames: list<item: int64>>>
                    child 0, item: struct<recording: string, frames: list<item: int64>>
                        child 0, recording: string
                        child 1, frames: list<item: int64>
                            child 0, item: int64
                child 6, encoding: string
                child 7, labels: string
                child 8, base_release: string
                child 9, base_revision: string
                child 10, g2_inventory_sha256: string
                child 11, local_completion: struct<status: string, root: string, files: int64, source_bytes: int64, copied_files: int64, copied_ (... 46 chars omitted)
                    child 0, status: string
                    child 1, root: string
                    child 2, files: int64
                    child 3, source_bytes: int64
                    child 4, copied_files: int64
                    child 5, copied_bytes: int64
                    child 6, all_files_sha256_verified: bool
              source_content_unchanged: bool
              preserve_splits: bool
              image_format: string
              sha256: string
              width: int64
              height: int64
              path: string
              kind: string
              bytes: int64
              mode: string
              to
              {'path': Value('string'), 'bytes': Value('int64'), 'sha256': Value('string'), 'kind': Value('string'), 'image_format': Value('string'), 'width': Value('int64'), 'height': Value('int64'), 'mode': Value('string')}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1379, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 956, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1702, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1887, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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path
string
bytes
int64
sha256
string
kind
string
image_format
string
width
int64
height
int64
mode
string
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End of preview.

EgoNet SFT:H2O / ARCTIC 完整 ego 数据池

新版 releases/20261028_ego_full/ 在此前筛选版上补齐 G2 全部已存 H2O cam4、ARCTIC ego view 0 图像及配套原生标注/标定。已有分片按哈希引用,新增差额单独上传,旧版本不被覆盖。是否上传完成以新版 upload_status.json 的 complete 字段为准。

图像与划分

数据 Train RGB Val RGB Test RGB
H2O cam4 68,929 14,676 30,724
ARCTIC ego view 0 192,383 25,883 25,140

这里按录制所属的官方 split 统计目录内全部 RGB,不把图像总数等同于有效姿态监督数量。H2O 官方 pose_train/val/test.txt 分别引用 55,742 / 11,638 / 23,391 帧,均已覆盖;目录中的额外 RGB 不自动获得姿态监督资格。ARCTIC train/val 有原生 MANO,test 图像无本包可用的公开手部 GT。

ARCTIC 已补回 s01/microwave_use_02 的 662 帧;s06/notebook_use_01 的 675–681 共 7 帧在核验的官方图像包中也缺失,显式保留缺口,不复制邻帧伪造补齐。ARCTIC 图像为官方 cropped_images 的 ego 全帧缩放版,通常 840×600,不是原始 2800×2000,也不是按手框裁剪;reader 仍需按原始标定和 ioi_offset 对齐并去畸变。

H2O RGB 保留 PNG,metric depth 保留无损 PNG;ARCTIC 保留源 JPEG。本次不进行 Q95 重编码。仓库不含 HOT3D、渲染数据或第三人称图像;EgoRenderer 继续复用独立仓库。

原生标签与 refit 覆盖

原生 MANO、关节、相机内外参和官方划分用于全量数据读取。此前 380 份 canonical/refit 标签、3,867 份 filtered GT及冻结训练/评估清单保留原字节。

补图像不等于补 refit。 现有 corrected-left / rotation-fix 训练标签仍只覆盖 H2O 47,594 帧、ARCTIC 170,301 帧;新增训练 RGB 合计 43,417 帧不被冒称已有 refit。metadata/ego_full_20261028/frames.jsonl.gz 逐帧登记录制 split、官方 pose split、是否存在旧 canonical/refit 帧条目。帧条目存在性不是左右手每项监督均有效,仍需读取对应 mask。

此版本是完整数据池,没有替换正在使用的训练 manifest、监督、归一化或评估口径,也没有启动训练。官方 train/val/test 保持隔离;旧 development/confirmation 仍是固定小面板,不自动变成全量官方评估。

下载、解包和校验

pip install -U huggingface_hub
hf download WhynotGPT/SFT releases/20261028_ego_full/download_release.py \
  --repo-type dataset --local-dir ./sft_download
python ./sft_download/releases/20261028_ego_full/download_release.py \
  --root /your/data/EgoNet_SFT --extract

新版 catalog 包含旧版复用分片及新增分片,默认一次下载完整并集。--only metadata,canonical_labels,filtered_gt,h2o_ego,arctic_ego 可选择组件。脚本固定一次 revision,逐分片/逐文件核对 SHA256,拒绝目录穿越和覆盖不同内容的已有文件。已有同路径同哈希的下载和解包文件可复用。下载 tar 会保留,磁盘需同时容纳归档与解包数据。

EgoNet_SFT/
├── H2O/extracted/                       # cam4 全部已有 RGB/depth/原生标注/标定与官方 split
├── ARCTIC/data/                         # ego 图、raw_seqs、meta、官方 split
├── canonical_labels/                   # 原有训练 refit,不冒称已补全
├── filtered_gt/{H2O,ARCTIC}/
└── metadata/
    ├── ego_full_20261028/               # 全量逐帧清单、scope、G2 补全审计
    ├── cache/                           # 原有筛选版训练清单与两源索引
    └── eval/frozen_panels_sync_v2/       # 原有固定评估面板

绝对路径迁移见新版 path_mapping.json。原始标注与历史清单不改写,不将新生成的文件哈希冒充旧资产。MANO 模型、视觉初始化、checkpoint 和归一化训练资产不在本数据包中。

G1 完整入口:/SSD2/wuyifan_EgoNet/EgoNet_Data/sft/ego_full_20261028/。本地通过经过哈希核验的现有文件与新增副本构建目录链接,依赖链接目标,不能只复制软链接到另一台机器;HF tar 内均为实际文件。

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