README.md

---
license: cc-by-nc-4.0
task_categories:
- text-to-video
language:
- en
size_categories:
- 1M<n<10M
tags:
- prompts
- text-to-video
---

<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/teasor.png">

# Summary
This is the dataset proposed in our paper "VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models"

VidProM is the first dataset featuring 1.67 million unique text-to-video prompts and 6.69 million videos generated from 4 different state-of-the-art diffusion models.
It inspires many exciting new research areas, such as Text-to-Video Prompt Engineering, Efficient Video Generation, Fake Video Detection, and Video Copy Detection for Diffusion Models.

# Directory
```
*DATA_PATH
	*original_files
		*generate_1_ori.html
		*generate_2_ori.html
        ...
	*pika_videos
		*pika_videos_1.tar
		*pika_videos_2.tar
		...
    *vc2_videos
        *vc2_videos_1.tar
		*vc2_videos_2.tar
		...
    *t2vz_videos
        *t2vz_videos_1.tar
		*t2vz_videos_2.tar
		...
    *ms_videos
        *ms_videos_1.tar
		*ms_videos_2.tar
		...
    *VidProM_unique.csv
    *VidProM_semantic_unique.csv
    *VidProM_embed.hdf5

```

# Download 

### Automatically
Install the [datasets](https://huggingface.co/docs/datasets/v1.15.1/installation.html) library first, by:
```
pip install datasets
```
Then it can be downloaded automatically with
```
import numpy as np
from datasets import load_dataset
dataset = load_dataset('WenhaoWang/VidProM')
```

### Manual

You can download each file by ```wget```, for instance:
```
wget https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/VidProM_unique.csv
```

# Explanation

# Datapoint

<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/datapoint.png">

# Comparison with DiffusionDB

<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_table.png">

<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_visual.png">

# Citation