Dataset Viewer
	The dataset viewer is not available for this subset.
Cannot get the split names for the config 'default' of the dataset.
				Exception:    SplitsNotFoundError
Message:      The split names could not be parsed from the dataset config.
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 289, in get_dataset_config_info
                  for split_generator in builder._split_generators(
                                         ^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/packaged_modules/folder_based_builder/folder_based_builder.py", line 185, in _split_generators
                  raise ValueError(f"Found metadata files with different extensions: {list(metadata_ext)}")
              ValueError: Found metadata files with different extensions: ['.csv', '.parquet']
              
              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/split_names.py", line 65, in compute_split_names_from_streaming_response
                  for split in get_dataset_split_names(
                               ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 343, in get_dataset_split_names
                  info = get_dataset_config_info(
                         ^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.12/site-packages/datasets/inspect.py", line 294, in get_dataset_config_info
                  raise SplitsNotFoundError("The split names could not be parsed from the dataset config.") from err
              datasets.inspect.SplitsNotFoundError: The split names could not be parsed from the dataset config.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.
Japanese TV Commercial Video Dataset
Dataset Description
This dataset contains Japanese TV commercial (CM) videos with hierarchical scene detection annotations.
Dataset Summary
- Total Videos: 100
 - Total Duration: 39.5 minutes (2370 seconds)
 - Total Scenes: 2,320
 - Average Duration per Video: 23.7s
 - Average Scenes per Video: 23.2
 
Languages
Commercial videos contain a mix of:
- Japanese (primary)
 - English (secondary)
 
Dataset Structure
dataset/
├── videos/              # Video files (.mp4)
│   ├── CM_000.mp4
│   ├── CM_001.mp4
│   └── ...
├── thumbnails/          # Representative thumbnails for each video
│   ├── CM_000.jpg
│   ├── CM_001.jpg
│   └── ...
├── scenes/              # Scene detection results
│   ├── CM_000/
│   │   ├── scenes.json  # Scene boundaries and metadata
│   │   └── scene_*.jpg  # Thumbnails for each scene
│   └── ...
├── metadata.parquet     # Dataset metadata (recommended)
└── metadata.csv         # Human-readable metadata
Data Fields
metadata.parquet / metadata.csv:
video_id: Unique identifier (e.g., "CM_000")video_path: Path to video filethumbnail: Path to representative thumbnail imageduration: Video duration in secondsnum_scenes: Total number of detected scenesnum_groups: Number of scene groupsscenes_json_path: Path to scenes.json filescene_thumbnails_dir: Directory containing scene thumbnailslevel1_count,level2_count,level3_count: Scene counts per detection levellevel1_threshold,level2_threshold,level3_threshold: Detection thresholds used
scenes.json (per video):
{
  "video_name": "CM_000",
  "video_duration": 29.66,
  "total_scenes": 15,
  "scenes": [
    {
      "scene_number": 1,
      "start_time": 0.0,
      "end_time": 2.102,
      "duration": 2.102,
      "start_timecode": "00:00:00.000",
      "end_timecode": "00:00:02.102",
      "thumbnail": "scene_001.jpg",
      "level": 1,
      "threshold": 5.0
    }
  ]
}
Scene Detection Methodology
Scenes are detected using hierarchical scene detection with PySceneDetect:
- Level 1 (threshold: 5.0): Major scene changes (coarse)
 - Level 2 (threshold: 3.0): Medium scene changes
 - Level 3 (threshold: 1.0): Subtle scene changes (fine)
 
Each scene includes:
- Precise start/end timestamps
 - Duration
 - Detection level (indicating cut intensity)
 - Thumbnail image
 
Usage
Load with Hugging Face Datasets
from datasets import load_dataset
# Load metadata
dataset = load_dataset("your-username/tv-commercial-videos")
# Access first video
sample = dataset["train"][0]
print(f"Video: {sample['video_path']}")
print(f"Duration: {sample['duration']}s")
print(f"Scenes: {sample['num_scenes']}")
Load with Pandas
import pandas as pd
# Load metadata
df = pd.read_parquet("metadata.parquet")
# Load scene data for specific video
import json
with open(df.iloc[0]['scenes_json_path'], 'r') as f:
    scenes = json.load(f)
Use Cases
This dataset is suitable for:
- Video segmentation: Scene boundary detection
 - Content analysis: Commercial structure analysis
 - Computer vision: Object detection in commercial contexts
 - Temporal analysis: Shot duration patterns
 - Multi-modal learning: Video + audio + text
 - Advertisement research: Creative patterns in commercials
 
Limitations
- Videos are sourced from Japanese TV commercials (specific domain)
 - Scene detection is automated and may have occasional errors
 - No manual verification of scene boundaries
 - No semantic labels (e.g., product categories, themes)
 
Citation
If you use this dataset, please cite:
@dataset{tv_commercial_videos_2024,
  title={Japanese TV Commercial Video Dataset with Scene Detection},
  author={Your Name},
  year={2024},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/your-username/tv-commercial-videos}
}
License
This dataset is released under CC-BY-4.0 license.
Contact
For questions or issues, please open an issue on the dataset repository.
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