Add TsFile (converted from 1g0rrr/sam_frames5)

.gitattributes

@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+data/sam_frames5_train.tsfile filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,148 @@
+---
+license: apache-2.0
+task_categories:
+- robotics
+tags:
+- LeRobot
+- robotics
+- tsfile
+- timeseries
+- time-series
+- modality:timeseries
+pretty_name: SAM Frames5 (TsFile)
+size_categories:
+- 10K<n<100K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/sam_frames5_train.tsfile
+---
+
+# SAM Frames5 (TsFile)
+
+This dataset is an Apache TsFile conversion of the Hugging Face dataset
+[`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5).
+The source was created with
+[LeRobot](https://github.com/huggingface/lerobot) and contains `sam_double`
+robot demonstrations for peeling the protective layer from adhesive tape.
+
+Modalities: Time-series. The source repository also contains three synchronized
+camera streams; videos are not included in this converted repository.
+
+## Source Dataset
+
+- Original dataset: [`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5)
+- License: `apache-2.0`
+- LeRobot codebase version: `v2.1`
+- Robot type: `sam_double`
+- Task: `Peel off the protective layer from the adhesive tape.`
+- Split: `train` (`0:51`)
+- Scale: `51` episodes, `32,369` frames, `1` task
+- Sampling rate: `30` fps
+- Source frame files: `51` Parquet files
+- Source videos: `153` MP4 files across `3` camera streams
+- Source data layout: `data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet`
+- Source video layout: `videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4`
+
+The camera streams are `observation.images.laptop`,
+`observation.images.phone`, and `observation.images.side`. Each stream contains
+51 videos at 30 fps. Source video frames are 480 x 640 RGB, encoded with AV1,
+and contain no audio.
+
+## Converted File
+
+- TsFile: `data/sam_frames5_train.tsfile`
+- TsFile table: `sam_frames5_train`
+- Converted rows: `32,369`
+- Episodes: `51`
+- Time precision: milliseconds
+- TAG columns: `episode_index`, `task_index`
+- File size: `537,440` bytes
+- SHA-256: `7415819c4cfe7786f3fe18ff489fe58e8c22abb1c7128c51ebc324c47c4bc788`
+
+All train episodes are merged into one TsFile. The source `episode_index` and
+`task_index` columns are retained as TAG columns, so queries can select an
+episode without synthetic aliases.
+
+## Schema
+
+`Time` is computed as `Time = round(timestamp * 1000)` in milliseconds and
+restarts in each episode. At 30 fps, consecutive frames are approximately
+33.333 ms apart. The source `timestamp` column is not retained because it is
+redundant with `Time / 1000` seconds. No source rows are dropped.
+
+TAG columns:
+
+- `episode_index`
+- `task_index`
+
+FIELD columns:
+
+- `frame_index`
+- `sample_index` (renamed from source `index`)
+- `action_0` through `action_6` (FLOAT)
+- `observation_state_0` through `observation_state_6` (FLOAT)
+
+The seven vector elements use this source order for both `action` and
+`observation.state`:
+
+1. `main_shoulder_pan`
+2. `main_shoulder_lift`
+3. `main_elbow_flex`
+4. `main_wrist_flex`
+5. `main_wrist_side`
+6. `main_wrist_roll`
+7. `main_gripper`
+
+Vector column names preserve the complete source feature name: `.` is replaced
+with `_`, then the zero-based element index is appended.
+
+## Video Policy
+
+The three source video features are not converted or uploaded. Use the original
+dataset for synchronized videos:
+[`1g0rrr/sam_frames5/videos`](https://huggingface.co/datasets/1g0rrr/sam_frames5/tree/main/videos).
+
+Each numeric row retains `episode_index`, `frame_index`, `task_index`, and
+`sample_index`, preserving alignment with the original per-episode videos.
+
+## Metadata
+
+The source `meta/` files are mirrored in this repository. `meta/info.json` is
+updated so `data_path` points to `data/sam_frames5_train.tsfile`. Its
+`tsfile_conversion` object records the source and converted file counts, table
+name, Time formula, TAG columns, row count, feature mappings, and frame/video
+alignment. The converted `total_videos` is `0`; the source count of `153` is
+preserved as `tsfile_conversion.source_video_count`.
+
+## Validation
+
+The converted file was compared with all 51 source Parquet files and read back
+with the TsFile Python SDK:
+
+- source and staged rows: `32,369`
+- duplicate `(episode_index, task_index, Time)` rows: `0`
+- maximum action-vector difference: `0`
+- maximum observation-state-vector difference: `0`
+- source `index` to converted `sample_index` mismatches: `0`
+
+## Usage
+
+```python
+from tsfile import TsFileReader
+
+path = "data/sam_frames5_train.tsfile"
+with TsFileReader(path) as reader:
+    schemas = reader.get_all_table_schemas()
+    table = schemas["sam_frames5_train"]
+    print([(column.get_column_name(), column.get_category())
+           for column in table.get_columns()])
+```
+
+## Source & License
+
+The source dataset is maintained at
+[`1g0rrr/sam_frames5`](https://huggingface.co/datasets/1g0rrr/sam_frames5) and
+is distributed under the Apache License 2.0. The source card does not provide a
+paper, author list, or citation entry.

data/sam_frames5_train.tsfile

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7415819c4cfe7786f3fe18ff489fe58e8c22abb1c7128c51ebc324c47c4bc788
+size 537440

meta/episodes.jsonl

@@ -0,0 +1,51 @@
+{"episode_index": 0, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 621}
+{"episode_index": 1, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 477}
+{"episode_index": 2, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 555}
+{"episode_index": 3, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 533}
+{"episode_index": 4, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 703}
+{"episode_index": 5, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 635}
+{"episode_index": 6, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 737}
+{"episode_index": 7, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 947}
+{"episode_index": 8, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 437}
+{"episode_index": 9, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 527}
+{"episode_index": 10, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 560}
+{"episode_index": 11, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 496}
+{"episode_index": 12, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 732}
+{"episode_index": 13, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 667}
+{"episode_index": 14, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 724}
+{"episode_index": 15, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 566}
+{"episode_index": 16, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 568}
+{"episode_index": 17, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 814}
+{"episode_index": 18, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 670}
+{"episode_index": 19, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 788}
+{"episode_index": 20, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 981}
+{"episode_index": 21, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 623}
+{"episode_index": 22, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 547}
+{"episode_index": 23, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 573}
+{"episode_index": 24, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 687}
+{"episode_index": 25, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 597}
+{"episode_index": 26, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 522}
+{"episode_index": 27, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 586}
+{"episode_index": 28, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 752}
+{"episode_index": 29, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 1019}
+{"episode_index": 30, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 566}
+{"episode_index": 31, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 1042}
+{"episode_index": 32, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 540}
+{"episode_index": 33, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 703}
+{"episode_index": 34, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 485}
+{"episode_index": 35, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 902}
+{"episode_index": 36, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 565}
+{"episode_index": 37, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 590}
+{"episode_index": 38, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 442}
+{"episode_index": 39, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 477}
+{"episode_index": 40, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 658}
+{"episode_index": 41, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 542}
+{"episode_index": 42, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 549}
+{"episode_index": 43, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 396}
+{"episode_index": 44, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 525}
+{"episode_index": 45, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 714}
+{"episode_index": 46, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 581}
+{"episode_index": 47, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 569}
+{"episode_index": 48, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 491}
+{"episode_index": 49, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 951}
+{"episode_index": 50, "tasks": ["Peel off the protective layer from the adhesive tape."], "length": 437}

meta/info.json

@@ -0,0 +1,298 @@
+{
+  "codebase_version": "v2.1",
+  "robot_type": "sam_double",
+  "total_episodes": 51,
+  "total_frames": 32369,
+  "total_tasks": 1,
+  "total_videos": 0,
+  "total_chunks": 1,
+  "chunks_size": 1000,
+  "fps": 30,
+  "splits": {
+    "train": "0:51"
+  },
+  "data_path": "data/sam_frames5_train.tsfile",
+  "features": {
+    "Time": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "TIME",
+      "unit": "ms"
+    },
+    "episode_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "TAG"
+    },
+    "task_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "TAG"
+    },
+    "frame_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "sample_index": {
+      "dtype": "int64",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_0": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_1": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_2": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_3": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_4": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_5": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "action_6": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_0": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_1": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_2": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_3": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_4": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_5": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    },
+    "observation_state_6": {
+      "dtype": "float32",
+      "shape": [
+        1
+      ],
+      "tsfile_role": "FIELD"
+    }
+  },
+  "video_path_original": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
+  "tsfile_conversion": {
+    "source_dataset": "1g0rrr/sam_frames5",
+    "source_data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet",
+    "converted_data_path": "data/sam_frames5_train.tsfile",
+    "table_name": "sam_frames5_train",
+    "granularity": "per_split",
+    "time_precision": "ms",
+    "time_mapping": {
+      "source": "timestamp",
+      "formula": "Time = round(timestamp * 1000)",
+      "source_unit": "seconds",
+      "fps": 30,
+      "unit": "milliseconds"
+    },
+    "tag_columns": [
+      "episode_index",
+      "task_index"
+    ],
+    "row_count": 32369,
+    "feature_source": "features describe the converted TsFile schema",
+    "flattened_features": {
+      "action": [
+        "action_0",
+        "action_1",
+        "action_2",
+        "action_3",
+        "action_4",
+        "action_5",
+        "action_6"
+      ],
+      "observation.state": [
+        "observation_state_0",
+        "observation_state_1",
+        "observation_state_2",
+        "observation_state_3",
+        "observation_state_4",
+        "observation_state_5",
+        "observation_state_6"
+      ]
+    },
+    "renamed_features": {
+      "index": "sample_index"
+    },
+    "dropped_features": [
+      "timestamp"
+    ],
+    "omitted_features": [
+      "observation.images.laptop",
+      "observation.images.phone",
+      "observation.images.side"
+    ],
+    "original_video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4",
+    "original_video_features": {
+      "observation.images.laptop": {
+        "dtype": "video",
+        "shape": [
+          480,
+          640,
+          3
+        ],
+        "names": [
+          "height",
+          "width",
+          "channels"
+        ],
+        "info": {
+          "video.fps": 30.0,
+          "video.height": 480,
+          "video.width": 640,
+          "video.channels": 3,
+          "video.codec": "av1",
+          "video.pix_fmt": "yuv420p",
+          "video.is_depth_map": false,
+          "has_audio": false
+        }
+      },
+      "observation.images.phone": {
+        "dtype": "video",
+        "shape": [
+          480,
+          640,
+          3
+        ],
+        "names": [
+          "height",
+          "width",
+          "channels"
+        ],
+        "info": {
+          "video.fps": 30.0,
+          "video.height": 480,
+          "video.width": 640,
+          "video.channels": 3,
+          "video.codec": "av1",
+          "video.pix_fmt": "yuv420p",
+          "video.is_depth_map": false,
+          "has_audio": false
+        }
+      },
+      "observation.images.side": {
+        "dtype": "video",
+        "shape": [
+          480,
+          640,
+          3
+        ],
+        "names": [
+          "height",
+          "width",
+          "channels"
+        ],
+        "info": {
+          "video.fps": 30.0,
+          "video.height": 480,
+          "video.width": 640,
+          "video.channels": 3,
+          "video.codec": "av1",
+          "video.pix_fmt": "yuv420p",
+          "video.is_depth_map": false,
+          "has_audio": false
+        }
+      }
+    },
+    "original_video_source": "https://huggingface.co/datasets/1g0rrr/sam_frames5/tree/main/videos",
+    "video_policy": "Videos are not uploaded to this repository; use the original HuggingFace dataset videos.",
+    "source_video_count": 153,
+    "source_episode_file_count": 51,
+    "converted_tsfile_count": 1,
+    "table_names": [
+      "sam_frames5_train"
+    ],
+    "frame_video_alignment": {
+      "relationship": "one converted row per source frame",
+      "preserved_columns": [
+        "episode_index",
+        "task_index",
+        "frame_index",
+        "sample_index"
+      ],
+      "sample_index_mapping": {
+        "source": "index",
+        "converted": "sample_index"
+      },
+      "video_location": "original_dataset_only"
+    }
+  }
+}

meta/tasks.jsonl

@@ -0,0 +1 @@
+{"task_index": 0, "task": "Peel off the protective layer from the adhesive tape."}