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The dataset generation failed because of a cast error
Error code: DatasetGenerationCastError
Exception: DatasetGenerationCastError
Message: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'view_type', 'notes', 'clip_id', 'duration_seconds', 'recording_date', 'fps', 'filename', 'file_size_mb', 'resolution', 'activity', 'duration', 'sub_activity'}) and 4 missing columns ({'__index_level_2__', '# 🍳 Cooking & Chopping Activity — Egocentric Video Dataset', '__index_level_1__', '__index_level_0__'}).
This happened while the csv dataset builder was generating data using
zip://annotations.csv::hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking-chopping-egocentric.zip, ['hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking-chopping-egocentric.zip', 'hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking_metadata.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)
Traceback: Traceback (most recent call last):
File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1837, in _prepare_split_single
writer.write_table(table)
~~~~~~~~~~~~~~~~~~^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 765, in write_table
self._write_table(pa_table, writer_batch_size=writer_batch_size)
~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.14/site-packages/datasets/arrow_writer.py", line 773, in _write_table
pa_table = table_cast(pa_table, self._schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2369, in table_cast
return cast_table_to_schema(table, schema)
File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2297, in cast_table_to_schema
raise CastError(
...<3 lines>...
)
datasets.table.CastError: Couldn't cast
clip_id: string
filename: string
activity: string
sub_activity: string
duration: string
duration_seconds: int64
file_size_mb: double
recording_date: string
resolution: string
fps: int64
view_type: string
notes: string
-- schema metadata --
pandas: '{"index_columns": [{"kind": "range", "name": null, "start": 0, "' + 1697
to
{'# 🍳 Cooking & Chopping Activity — Egocentric Video Dataset': Value('string'), '__index_level_0__': Value('string'), '__index_level_1__': Value('string'), '__index_level_2__': Value('string')}
because column names don't match
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, 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 948, 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 1683, 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 1839, in _prepare_split_single
raise DatasetGenerationCastError.from_cast_error(
...<4 lines>...
)
datasets.exceptions.DatasetGenerationCastError: An error occurred while generating the dataset
All the data files must have the same columns, but at some point there are 12 new columns ({'view_type', 'notes', 'clip_id', 'duration_seconds', 'recording_date', 'fps', 'filename', 'file_size_mb', 'resolution', 'activity', 'duration', 'sub_activity'}) and 4 missing columns ({'__index_level_2__', '# 🍳 Cooking & Chopping Activity — Egocentric Video Dataset', '__index_level_1__', '__index_level_0__'}).
This happened while the csv dataset builder was generating data using
zip://annotations.csv::hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking-chopping-egocentric.zip, ['hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking-chopping-egocentric.zip', 'hf://datasets/VerboseTechLabs/cooking-chopping-egocentric@d2880b5038cd21263910d2c50c353efd5c60db63/cooking_metadata.csv']
Please either edit the data files to have matching columns, or separate them into different configurations (see docs at https://hf.co/docs/hub/datasets-manual-configuration#multiple-configurations)Need help to make the dataset viewer work? Make sure to review how to configure the dataset viewer, and open a discussion for direct support.
# 🍳 Cooking & Chopping Activity — Egocentric Video Dataset string | __index_level_0__ string | __index_level_1__ string | __index_level_2__ string |
|---|---|---|---|
and kitchen activity analysis research. | First-person point-of-view (POV) video recordings of everyday cooking and chopping activities | captured for computer vision | action recognition |
null | --- | null | null |
null | ## 📌 Overview | null | null |
null | This dataset contains **11 egocentric video clips** (~102 minutes total) filmed from the wearer's perspective while performing cooking-related tasks in real kitchen environments. It is designed for training and benchmarking machine learning models on fine-grained human activity understanding. | null | null |
null | | Metric | Value | | null | null |
null | |---|---| | null | null |
null | | Total clips | 11 | | null | null |
null | | Total duration | ~102 minutes | | null | null |
null | | Total size | ~6 GB | | null | null |
null | | Main classes | 2 (Cooking | Chopping) | | null |
null | | Sub-activity classes | 4 | | null | null |
null | | View type | Egocentric (first-person) | | null | null |
null | | Video format | MP4 | | null | null |
null | | Frame rate | 30 fps | | null | null |
null | | Resolution | 720p – 1080p | | null | null |
null | --- | null | null |
null | ## 🎯 Use Cases | null | null |
null | - **Action recognition** in kitchen environments | null | null |
null | - **Hand-object interaction** detection | null | null |
null | - **Fine-grained cooking step** segmentation | null | null |
null | - **Recipe understanding** and procedural learning | null | null |
null | - **Assistive robotics** — training robots for kitchen tasks | null | null |
null | - **Benchmarking** egocentric video models (EPIC-KITCHENS-style tasks) | null | null |
null | - **Temporal action localization** | null | null |
null | - **Video summarization** for cooking tutorials | null | null |
null | --- | null | null |
null | ## 📂 Folder Structure | null | null |
null | ``` | null | null |
null | cooking-chopping-egocentric/ | null | null |
null | ├── videos/ | null | null |
null | │ ├── chopping/ | null | null |
null | │ │ ├── chopping1.mp4 | null | null |
null | │ │ ├── chopping2.mp4 | null | null |
null | │ │ └── chopping3.mp4 | null | null |
null | │ └── cooking/ | null | null |
null | │ ├── Cooking1.mp4 | null | null |
null | │ ├── Cooking2.mp4 | null | null |
null | │ ├── Cooking3.mp4 | null | null |
null | │ ├── Cooking5.mp4 | null | null |
null | │ ├── Cooking6.mp4 | null | null |
null | │ ├── Cooking7.mp4 | null | null |
null | │ ├── Cooking8.mp4 | null | null |
null | │ └── Cooking9.mp4 | null | null |
null | ├── annotations.csv | null | null |
null | └── README.md | null | null |
null | ``` | null | null |
null | > **Note:** There is no `Cooking4.mp4` — file numbering is intentionally non-sequential. | null | null |
null | --- | null | null |
null | ## 📊 Dataset Composition | null | null |
null | ### Chopping Activities (3 clips • ~11 min) | null | null |
null | | Clip ID | File | Duration | Size | | null | null |
null | |---|---|---|---| | null | null |
null | | CHP_001 | chopping1.mp4 | 00:01:45 | 130 MB | | null | null |
null | | CHP_002 | chopping2.mp4 | 00:06:56 | 512 MB | | null | null |
null | | CHP_003 | chopping3.mp4 | 00:02:37 | 157 MB | | null | null |
null | ### Cooking Activities (8 clips • ~91 min) | null | null |
null | | Clip ID | File | Sub-activity | Duration | Size | | null | null |
null | |---|---|---|---|---| | null | null |
null | | COK_001 | Cooking1.mp4 | general_cooking | 00:11:55 | 51 MB | | null | null |
null | | COK_002 | Cooking2.mp4 | general_cooking | 00:31:28 | 110 MB | | null | null |
null | | COK_003 | Cooking3.mp4 | general_cooking | 00:00:30 | 14 MB | | null | null |
null | | COK_004 | Cooking5.mp4 | general_cooking | 00:20:49 | 1.99 GB | | null | null |
null | | COK_005 | Cooking6.mp4 | general_cooking | 00:11:42 | 1.43 GB | | null | null |
null | | COK_006 | Cooking7.mp4 | egg_preparation | 00:04:58 | 189 MB | | null | null |
null | | COK_007 | Cooking8.mp4 | burger_preparation | 00:06:12 | 877 MB | | null | null |
null | | COK_008 | Cooking9.mp4 | general_cooking | 00:02:52 | 415 MB | | null | null |
null | --- | null | null |
null | ## 🏷️ Annotation Schema | null | null |
null | The `annotations.csv` file contains the following columns: | null | null |
null | | Column | Type | Description | | null | null |
null | |---|---|---| | null | null |
null | | `clip_id` | string | Unique identifier (e.g. | `CHP_001` | `COK_001`) | |
null | | `filename` | string | Original video filename | | null | null |
null | | `activity` | string | Main class: `cooking` or `chopping` | | null | null |
null | | `sub_activity` | string | Fine-grained label (e.g. | `egg_preparation`) | | null |
null | | `duration` | string | Human-readable duration (HH:MM:SS) | | null | null |
null | | `duration_seconds` | integer | Duration in seconds | | null | null |
null | | `file_size_mb` | float | File size in megabytes | | null | null |
null | | `recording_date` | date | Recording date (YYYY-MM-DD) | | null | null |
null | | `resolution` | string | Video resolution (e.g. | `1080p`) | | null |
null | | `fps` | integer | Frames per second | | null | null |
null | | `view_type` | string | Camera view type (`egocentric`) | | null | null |
null | | `notes` | string | Additional context | | null | null |
null | --- | null | null |
null | ## 🚀 Quick Start | null | null |
null | ### Load annotations with Pandas | null | null |
null | ```python | null | null |
null | import pandas as pd | null | null |
null | df = pd.read_csv("annotations.csv") | null | null |
null | print(df.head()) | null | null |
null | print(f"Total clips: {len(df)}") | null | null |
null | print(f"Activities: {df['activity'].value_counts()}") | null | null |
null | ``` | null | null |
null | ### Load a video with OpenCV | null | null |
null | ```python | null | null |
null | import cv2 | null | null |
null | cap = cv2.VideoCapture("videos/cooking/Cooking7.mp4") | null | null |
null | ret | frame = cap.read() | null |
null | if ret: | null | null |
null | cv2.imwrite("first_frame.jpg" | frame) | null |
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