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---
language:
- en
pretty_name: Movie Gen Video Benchmark
dataset_info:
features:
- name: prompt
dtype: string
- name: video
dtype: binary
splits:
- name: test_with_generations
num_bytes: 16029316444
num_examples: 1003
- name: test
num_bytes: 113706
num_examples: 1003
download_size: 16029724908
dataset_size: 16029430150
configs:
- config_name: default
data_files:
- split: test_with_generations
path: data/test_with_generations-*
- split: test
path: data/test-*
---
# Dataset Card for the Movie Gen Benchmark
[Movie Gen](https://ai.meta.com/research/movie-gen/) is a cast of foundation models that generates high-quality, 1080p HD videos with different aspect ratios and synchronized audio.
Here, we introduce our evaluation benchmark "Movie Gen Bench Video Bench", as detailed in the [Movie Gen technical report](https://ai.meta.com/static-resource/movie-gen-research-paper) (Section 3.5.2).
To enable fair and easy comparison to Movie Gen for future works on these evaluation benchmarks, we additionally release the non cherry-picked generated videos from Movie Gen on Movie Gen Video Bench.
## Dataset Summary
Movie Gen Video Bench consists of 1003 prompts that cover all the different testing aspects/concepts:
1. human activity (limb and mouth motion, emotions, etc.)
2. animals
3. nature and scenery
4. physics (fluid dynamics, gravity, acceleration, collisions, explosions, etc.)
5. unusual subjects and unusual activities.
Besides a comprehensive coverage of different key testing aspects, the prompts also have a good coverage of high/medium/low motion levels at the same time.
## Dataset Splits
We are releasing two versions of the benchmark:
1. Test (test): This version includes only the prompts, making it easier to download and use the benchmark.
2. Test with Generations (test_with_generations): This version includes both the prompts and the Movie Gen model’s outputs, allowing for comparative evaluation against the Movie Gen model.
## Usage
```python
from datasets import load_dataset
# to download only the prompts
dataset = load_dataset("facebook/moviegen_video", split="test")
print(dataset[0])
# to download the prompts and movie gen generations
dataset = load_dataset("facebook/moviegen_video", split="test")
print(dataset[0])
# to display a video and a prompt on jupyter notebook
import mediapy
example = dataset[0]
with open("tmp.mp4", "wb") as f:
f.write(example["video"])
video = mediapy.read_video("tmp.mp4")
print(example["prompt"])
mediapy.show_video(video)
```
## Licensing Information
Licensed with [CC-BY-NC](https://github.com/facebookresearch/MovieGenBench/blob/main/LICENSE) License. |