Update dataset

.gitattributes

@@ -58,3 +58,6 @@ 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
+*.csv filter=lfs diff=lfs merge=lfs -text
+annotations/*.json filter=lfs diff=lfs merge=lfs -text
+samples/annotations/*.json filter=lfs diff=lfs merge=lfs -text

LICENSE

@@ -0,0 +1,95 @@
+MEV Dataset License
+
+MEV is released as a source-aware open research dataset. The goal of this
+license is to make the dataset directly usable for research, evaluation, and
+model training while preserving the provenance and original terms of any
+third-party source videos.
+
+1. MEV-created annotations and metadata
+
+The annotations, labels, splits, timestamps, prompts, evaluation metadata,
+and other original metadata created by the MEV authors are
+released under the Creative Commons Attribution 4.0 International License
+(CC BY 4.0), unless a file explicitly states otherwise.
+
+Users may use, share, adapt, redistribute, and build upon these MEV-created
+materials, including for research, evaluation, and model training, provided
+that they give appropriate credit, provide a link to the license, and indicate
+if changes were made.
+
+CC BY 4.0:
+https://creativecommons.org/licenses/by/4.0/
+
+2. Released video package
+
+Video files included in the official MEV public release are provided together
+with MEV annotations and dataset-level source information as part of the MEV
+research data package. These released video files are intended to be directly
+downloadable and usable for research, evaluation, and model training, subject
+to the applicable source license or platform terms.
+
+MEV does not impose additional restrictions on the released video files beyond
+the applicable source terms and the responsible-use requirements described in
+this notice. Users do not need to re-crawl the original source websites to
+reproduce experiments on videos that are included in the official MEV video
+package.
+
+The MEV authors do not claim ownership of third-party video assets. Copyright
+and other rights in those videos remain with their original rights holders.
+Source attribution, source identifiers, and license/provenance metadata should
+be preserved when redistributing or adapting the dataset package.
+
+3. Source-specific terms
+
+MixKit videos included in MEV remain governed by the applicable MixKit stock
+video license and MixKit User Terms. MixKit provides item-type-specific stock
+video licenses, including free and restricted licenses.
+
+YouTube-hosted source videos remain subject to YouTube's Terms of Service and
+any rights or license terms associated with each video. When a video is included
+in the official MEV release package, MEV provides it as part of the dataset
+package with the corresponding MEV annotations. When a source video cannot
+be redistributed, MEV may release only annotations, timestamps, prompts, source
+URLs or identifiers, and other metadata where permitted.
+
+Only a small subset of optional 4K source versions may be premium, paid,
+restricted, or otherwise separately licensed, and this does not affect the
+released MEV video package. Such optional source versions are not automatically
+covered by the MEV public release. Users who obtain them directly from the
+original source are responsible for following the corresponding source license
+and terms.
+
+4. Responsible use
+
+MEV is intended for research and development in long-take multi-event video
+generation, event-level video understanding, dataset auditing, and related
+tasks. Users should comply with applicable copyright, privacy, data protection,
+and research ethics laws, and should not use the dataset to create misleading,
+harmful, privacy-invasive, or otherwise unlawful content.
+
+Users should not remove source attribution, copyright notices, license labels,
+or provenance metadata from redistributed video files or annotations. Users
+should also avoid using MEV to identify people, infer sensitive personal
+attributes, or target individuals depicted in source videos.
+
+5. No warranty
+
+MEV is provided on an "AS IS" basis. The MEV authors make no warranties
+regarding ownership of third-party video assets, availability of linked source
+videos, accuracy of annotations, suitability for any particular purpose, or
+compliance of users' downstream uses.
+
+6. Takedown and updates
+
+If a rights holder requests removal of a video file, video reference,
+annotation, or related metadata, or if legal, ethical, privacy, or security
+concerns arise, the MEV authors may remove or modify the affected materials.
+Affected video files will be removed from subsequent public packages when
+appropriate. Deprecated entries may be retained only as non-distributive
+provenance records when this is needed for reproducibility and is permitted by
+the applicable source terms.
+
+7. Legal notice
+
+This license notice is provided for informational purposes and is not legal
+advice.

README.md

@@ -0,0 +1,202 @@
+---
+license: other
+license_name: mixed-third-party-licenses
+license_link: LICENSE
+configs:
+  - config_name: events
+    default: true
+    data_files:
+      - split: events
+        path: metadata/events.parquet
+      - split: sample_events
+        path: samples/metadata/events.parquet
+  - config_name: videos
+    data_files:
+      - split: videos
+        path: metadata/videos.parquet
+      - split: sample_videos
+        path: samples/metadata/videos.parquet
+---
+
+# MEV Dataset
+
+MEV is a multi-event video annotation dataset. The canonical nested annotation
+file is `annotations/mev.json`. The primary machine-readable table is
+`metadata/events.parquet`, where each row corresponds to one event segment.
+
+## Repository Layout
+
+- `annotations/mev.json`: canonical full annotation file.
+- `metadata/events.parquet`: full event-level table.
+- `metadata/events.csv` and `mev.csv`: CSV mirrors for inspection.
+- `metadata/videos.parquet`: UUID-level index.
+- `raw/720p/raw-*.tar`: 8,016 original videos, stored as `<uuid>.mp4`.
+- `raw/1080p/raw-*.tar`: 1,896 optional higher-resolution originals.
+- `videos/mev-*.tar`: full video segment tar shards. Tar members preserve the original mp4 filenames.
+- `samples/`: reviewer-friendly sample subset with matching annotation, metadata, and tar shard(s).
+
+## Loading Metadata
+
+```python
+from datasets import load_dataset
+
+events = load_dataset("MultiEventVideo/MEV", split="events")
+videos = load_dataset("MultiEventVideo/MEV", "videos", split="videos")
+sample_events = load_dataset("MultiEventVideo/MEV", split="sample_events")
+```
+
+The default `events` configuration contains the `events` and `sample_events`
+splits. The `videos` configuration contains `videos` and `sample_videos`.
+These are table and inspection-subset names, not experimental train/test splits.
+
+Each event row includes `shard_path`, `tar_member`, and `media_ref`. For example:
+
+```text
+videos/mev-000000.tar::<original-segment-filename>.mp4
+```
+
+`has_cooking` is a boolean indicating food or beverage preparation, or active
+cooking/heating, during at least part of the event.
+
+## Download and Extract Videos
+
+Loading the metadata with `load_dataset` does not download the video archives.
+The following commands use a macOS or Linux shell.
+
+### Download the dataset
+
+Install the [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/guides/cli)
+and download the repository to a local `MEV` directory:
+
+```bash
+python -m pip install -U huggingface_hub
+hf download MultiEventVideo/MEV --repo-type dataset --local-dir ./MEV
+cd MEV
+```
+
+The complete download is approximately 227 GB. Run the commands below from this
+`MEV` directory. Individual archives can also be downloaded from the repository's
+Files tab, preserving the same directory layout.
+
+### Extract the original and event videos
+
+The `.tar` archives contain MP4 files and have no additional gzip compression.
+Create an `extracted/` subdirectory within each archive directory and extract the
+videos there. The tar files remain in their existing locations:
+
+```bash
+for directory in raw/720p raw/1080p videos; do
+  mkdir -p "$directory/extracted"
+  for archive in "$directory"/*.tar; do
+    tar -xf "$archive" -C "$directory/extracted"
+  done
+done
+```
+
+After running these commands, the directories contain:
+
+```text
+raw/720p/
+  raw-*.tar
+  extracted/<uuid>.mp4                  # 8,016 primary original videos
+raw/1080p/
+  raw-*.tar
+  extracted/<uuid>.mp4                  # 1,896 available alternate originals
+videos/
+  mev-*.tar
+  extracted/<original-event-filename>.mp4 # 25,262 event videos
+```
+
+Here, `raw/` holds original videos, while `videos/` holds Event videos.
+
+Open the extracted MP4 files in a video player. Original filenames are preserved:
+match raw videos by `uuid` and event videos by each annotation's `filename`.
+The 1080p directory contains alternate originals, not additional dataset UUIDs.
+Keeping the archives and all extracted full-data videos uses approximately 450 GB.
+
+To inspect a single archive before extracting it:
+
+```bash
+tar -tf videos/mev-000000.tar
+```
+
+Videos can also be read directly from their tar archives using the Python example
+under **Original video access**, without extracting the complete archives.
+
+## Sample Subset
+
+The `samples/` directory contains a smaller subset intended for reviewer
+inspection. It is drawn from the full MEV release at the UUID level; all events
+from selected UUIDs are preserved.
+
+Selection includes all videos with saved human-review records from the web
+annotation interface that are present in this release: 226 original
+videos and 721 events. Annotations are copied from the current full
+dataset. Selection is at the video level; it does not imply that every field was
+individually reviewed. `samples/uuids.txt` records the exact membership.
+`samples/raw/720p/` contains the original videos, and `samples/videos/` contains
+their event videos. This is an inspection subset, not a random population sample
+or the experimental train/test split.
+
+## License
+
+This repository uses `mixed-third-party-licenses`.
+
+Original Mixkit, YouTube, and other third-party videos remain subject to their respective platform terms and rights-holder licenses. The dataset authors do not claim ownership of third-party video assets and do not re-license them under CC BY, MIT, Apache, or any other open-source license.
+
+The official released video package is directly downloadable for research,
+evaluation, and model training, subject to applicable source-specific terms
+described in `LICENSE`. Optional restricted or premium source variants are not
+automatically part of the public package. Preserve available source attribution
+and provenance. The repository's existing `LICENSE` is authoritative.
+
+Annotations, labels, splits, benchmark metadata, and other author-created materials are released under the Creative Commons Attribution 4.0 International License, CC BY 4.0.
+
+See the `LICENSE` file for full details.
+
+## Original video access
+
+The dataset contains 8,016 original videos and 25,262 events.
+
+The Global table (`metadata/videos.parquet`) includes `raw_720p_shard_path`,
+`raw_720p_tar_member`, `raw_720p_media_ref`, `raw_720p_bytes`, and `raw_720p_sha256`.
+The full table also links available alternate originals with the corresponding
+`raw_1080p_*` columns. Empty alternative references indicate that the table does
+not provide that variant. The sample supplies the primary original videos.
+Resolution directory names preserve the source storage groups; actual media
+dimensions can vary. Every tar preserves the original MP4 bytes and filenames.
+
+All archives are uncompressed tar shards, each at most 5 GiB. To read an
+original video and its first event directly from the downloaded archives,
+install the table-reading dependencies:
+
+```bash
+python -m pip install pandas pyarrow
+```
+
+Then run this Python example from the downloaded `MEV` directory:
+
+```python
+from pathlib import Path
+import tarfile
+import pandas as pd
+
+root = Path(".")
+videos = pd.read_parquet(root / "metadata/videos.parquet")
+events = pd.read_parquet(root / "metadata/events.parquet")
+video = videos.iloc[0]
+event = events[events.uuid == video.uuid].iloc[0]
+
+def read_media(reference):
+    archive, member = reference.split("::", 1)
+    with tarfile.open(root / archive) as tar:
+        return tar.extractfile(member).read()
+
+raw_bytes = read_media(video.raw_720p_media_ref)
+event_bytes = read_media(event.media_ref)
+```
+
+Join the Global and Event tables on `uuid`. Each Event row stores its original
+video timestamps, an event ID starting at 1, its tar reference, byte size, and
+SHA-256. The HF table split names identify data views, not experimental train/test
+assignments.

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samples/README.md

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+# MEV inspection sample
+
+This subset includes all videos with saved human-review records from the web annotation interface that are present in this release. Their annotations are taken from the current full dataset, retaining all events of each selected video. Selection is at the video level; it does not imply that every field was individually reviewed.
+
+It contains 226 original videos and 721 events. The exact membership is in `annotations/sample_mev.json` and `uuids.txt`. The sample original videos are in `raw/720p/`, and the event videos are in `videos/`. Both use tar archives with unchanged MP4 bytes. This is an inspection subset, not a random population sample or the experimental train/test split.

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