---
license: gpl-3.0
task_categories:
  - feature-extraction
  - image-classification
  - video-classification
  - image-feature-extraction
language:
  - en
pretty_name: MovieFeats_Visual
size_categories:
  - n>100G
---

# 🎬 SceneSense Dataset

The 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. **SceneSense** can be used in recommendation, information retrieval, classification, _etc_ tasks.

## 📃 Table of Content

- [Dataset Stats](#stats)
- [Files Structure](#structure)
- [How to Use](#usage)

## 📊 Dataset Stats <a id="stats"></a>

### 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](https://grouplens.org/datasets/movielens/25m/)))

| 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** |

## 🗄️ Files Structure <a id="structure"></a>

### 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)](https://www.cv-foundation.org/openaccess/content_cvpr_2016/html/Szegedy_Rethinking_the_Inception_CVPR_2016_paper.html) and [VGG-19](https://doi.org/10.48550/arXiv.1409.1556), 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](https://grouplens.org/datasets/movielens/25m/)) 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](https://grouplens.org/datasets/movielens/25m/)) 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:

```bash
> [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](https://grouplens.org/datasets/movielens/25m/)).

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

## 🚀 How to Use? <a id="usage"></a>

In order to use, exploit, and generate this dataset, a framework titled `SceneSense` is implemented. You can read more about it [on the GitHub repository](https://github.com/RecSys-lab/SceneSense).