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π¬ SceneSense Dataset
The dataset contains visual features obtained from a wide range of movies (full-length), their shots, and free trailers. It can be used in recommendation, information retrieval, classification, etc.
π Table of Content
π 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 |
Total | - | 214,505 | ~103.8 GB |
ποΈ Files Structure
Level I. Primary Categories
The dataset contains three main folders and a stats.json
file. The folders keep the 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.
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)
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.
Level IV. Packets
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]
> ...
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"
]
},
...
]
π How to Use?
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.
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