The dataset viewer is not available for this dataset.
Cannot get the config names for the dataset.
Error code:   RetryableConfigNamesError
Exception:    HfHubHTTPError
Message:      504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/alitourani/MoViFex_Dataset/tree/82304281499bd53229d70fa9348887034c71a6a6?recursive=True&expand=False

<html>
<head><title>504 Gateway Time-out</title></head>
<body>
<center><h1>504 Gateway Time-out</h1></center>
</body>
</html>
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 164, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1729, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1686, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1064, in get_module
                  patterns = get_data_patterns(base_path, download_config=self.download_config)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 501, in get_data_patterns
                  return _get_data_files_patterns(resolver)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 295, in _get_data_files_patterns
                  data_files = pattern_resolver(pattern)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/data_files.py", line 388, in resolve_pattern
                  for filepath, info in fs.glob(pattern, detail=True, **glob_kwargs).items()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 409, in glob
                  return super().glob(path, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/fsspec/spec.py", line 604, in glob
                  allpaths = self.find(root, maxdepth=depth, withdirs=True, detail=True, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 429, in find
                  out = self._ls_tree(path, recursive=True, refresh=refresh, revision=resolved_path.revision, **kwargs)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 358, in _ls_tree
                  self._ls_tree(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_file_system.py", line 375, in _ls_tree
                  for path_info in tree:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/hf_api.py", line 3006, in list_repo_tree
                  for path_info in paginate(path=tree_url, headers=headers, params={"recursive": recursive, "expand": expand}):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_pagination.py", line 37, in paginate
                  hf_raise_for_status(r)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/huggingface_hub/utils/_http.py", line 477, in hf_raise_for_status
                  raise _format(HfHubHTTPError, str(e), response) from e
              huggingface_hub.errors.HfHubHTTPError: 504 Server Error: Gateway Time-out for url: https://huggingface.co/api/datasets/alitourani/MoViFex_Dataset/tree/82304281499bd53229d70fa9348887034c71a6a6?recursive=True&expand=False
              
              <html>
              <head><title>504 Gateway Time-out</title></head>
              <body>
              <center><h1>504 Gateway Time-out</h1></center>
              </body>
              </html>

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.

🎬 MoViFex Dataset

The Movies Visual Features Extracted (MoViFex) dataset contains visual features obtained from a wide range of movies (full-length), their shots, and free trailers. It contains frame-level extracted visual features and aggregated version of them. MoViFex can be used in recommendation, information retrieval, classification, etc tasks.

πŸ“ƒ Table of Content

πŸš€ How to Use?

The Dataset Web-Page

Check the detailed information about the dataset in its web-page presented in the link in https://recsys-lab.github.io/movifex_dataset/.

The Designed Framework for Benchmarking

In order to use, exploit, and generate this dataset, a framework titled MoViFex is implemented. You can read more about it on the GitHub repository.

πŸ“Š Dataset Stats

General

Aspect Value
Total number of movies 274
Average frames extracted per movie 7,732
Total number of frames (or feature vectors) 2,118,647

Hybrid (combined with MovieLenz 25M (link))

Aspect Value
Accumulative number of genres: 723
Average movie ratings: 3.88/5
Total number of users: 158,146
Accumulative number of interactions: 2,869,024

Required Capacity

Data Model Total Files Size on Disk
Full Movies incp3 84,872 35.8 GB
Full Movies vgg19 84,872 46.1 GB
Movie Shots incp3 16,713 7.01 GB
Movie Shots vgg19 24,598 13.3 GB
Trailers incp3 1,725 681 MB
Trailers vgg19 1,725 885 MB
Aggregated Full Movies incp3 84,872 10 MB
Aggregated Full Movies vgg19 84,872 19 MB
Aggregated Movie Shots incp3 16,713 10 MB
Aggregated Movie Shots vgg19 24,598 19 MB
Aggregated Trailers incp3 1,725 10 MB
Aggregated Trailers vgg19 1,725 19 MB
Total - 214,505 ~103.9 GB

πŸ—„οΈ Files Structure

Level I. Primary Categories

The dataset contains six main folders and a stats.json file. The stats.json file contains the meta-data for the sources. Folders 'full_movies', 'movie_shots', and 'movie_trailers' keep the atomic visual features extracted from various sources, including full_movies for frame-level visual features extracted from full-length movie videos, movie_shots for the shot-level (i.e., important frames) visual features extracted from full-length movie videos, and movie_trailers for frame-level visual features extracted from movie trailers videos. Folders 'full_movies_agg', 'movie_shots_agg', and 'movie_trailers_agg' keep the aggregated (non-atomic) versions of the described items.

Level II. Visual Feature Extractors

Inside each of the mentioned folders, there are two folders titled incp3 and vgg19, referring to the feature extractor used to generate the visual features, which are Inception-v3 (GoogleNet) and VGG-19, respectively.

Level III. Contents (Movies & Trailers)

A: Atomic Features (folders full_movies, movie_shots, and movie_trailers)

Inside each feature extractor folder (e.g., full_movies/incp3 or movie_trailers/vgg19) you can find a set of folders with unique title (e.g., 0000000778) indicating the ID of the movie in MovieLenz 25M (link) dataset. Accordingly, you have access to the visual features extracted from the movie 0000000778, using Inception-v3 and VGG-19 extractors, in full-length frame, full-length shot, and trailer levels.

B: Aggregated Features (folders full_movies_agg, movie_shots_agg, and movie_trailers_agg)

Inside each feature extractor folder (e.g., full_movies_agg/incp3 or movie_trailers_agg/vgg19) you can find a set of json files with unique title (e.g., 0000000778.json) indicating the ID of the movie in MovieLenz 25M (link) dataset. Accordingly, you have access to the aggregated visual features extracted from the movie 0000000778 (and available on the atomic features folders), using Inception-v3 and VGG-19 extractors, in full-length frame, full-length shot, and trailer levels.

Level IV. Packets (Atomic Feature Folders Only)

To better organize visual features, each movie folder (e.g., 0000000778) has a set of packets named as packet0001.json to packet000N.json saved as json files. Each packet contains a set of objects with frameId and features attributes, keeping the equivalent frame-ID and visual feature, respectively. In general, every 25 object (frameId-features pair) form a packet, except the last packet that can have less objects.

The described structure is presented below in brief:

> [full_movies]    ## visual features of frame-level full-length movie videos
  > [incp3]        ## visual features extracted using Inception-v3
    > [movie-1]
      > [packet-1]
      > [packet-2]
      ...
      > [packet-m]
    > [movie-2]
    ...
    > [movie-n]
  > [vgg19]        ## visual features extracted using VGG-19
    > [movie-1]
    ...
    > [movie-n]
> [movie_shots]    ## visual features of shot-level full-length movie videos
  > [incp3]
    > ...
  > [vgg19]
    > ...
> [movie_trailers] ## visual features of frame-level movie trailer videos
  > [incp3]
    > ...
  > [vgg19]
    > ...
> [full_movies_agg] ## aggregated visual features of frame-level full-length movie videos
  > [incp3]         ## aggregated visual features extracted using Inception-v3
    > [movie-1-json]
    > [movie-2]
    ...
    > [movie-n]
  > [vgg19]         ## aggregated visual features extracted using VGG-19
    > [movie-1]
    ...
    > [movie-n]
> [movie_shots_agg] ## aggregated visual features of shot-level full-length movie videos
> [movie_trailers_agg]    ## aggregated visual features of frame-level movie trailer videos

stats.json File

The stats.json file placed in the root contains valuable information about the characteristics of each of the movies, fetched from MovieLenz 25M (link).

[
  {
        "id": "0000000006",
        "title": "Heat",
        "year": 1995,
        "genres": [
            "Action",
            "Crime",
            "Thriller"
        ]
    },
    ...
]
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