|
--- |
|
license: cc-by-nc-4.0 |
|
task_categories: |
|
- text-to-video |
|
- text-to-image |
|
language: |
|
- en |
|
pretty_name: VidProM |
|
size_categories: |
|
- 1M<n<10M |
|
source_datasets: |
|
- original |
|
tags: |
|
- prompts |
|
- text-to-video |
|
- text-to-image |
|
- Pika |
|
- VideoCraft2 |
|
- Text2Video-Zero |
|
- ModelScope |
|
- Video Generative Model Evaluation |
|
- Text-to-Video Diffusion Model Development |
|
- Text-to-Video Prompt Engineering |
|
- Efficient Video Generation |
|
- Fake Video Detection |
|
- Video Copy Detection for Diffusion Models |
|
configs: |
|
- config_name: VidProM_unique |
|
data_files: VidProM_unique.csv |
|
--- |
|
|
|
|
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/teasor.png" width="800"> |
|
</p> |
|
|
|
|
|
# Summary |
|
This is the dataset proposed in our paper "[**VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models**](https://arxiv.org/abs/2403.06098)" |
|
|
|
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 |
|
*VidProM_unique.csv |
|
*VidProM_semantic_unique.csv |
|
*VidProM_embed.hdf5 |
|
*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 |
|
... |
|
*example |
|
|
|
``` |
|
|
|
|
|
# Download |
|
|
|
### Automatical |
|
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 also download each file by ```wget```, for instance: |
|
``` |
|
wget https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/VidProM_unique.csv |
|
``` |
|
|
|
### Users from China |
|
|
|
For users from China, we cooperate with [Wisemodel](https://wisemodel.cn/home), and you can download them faster from [here](https://wisemodel.cn/datasets/WenhaoWang/VidProM). |
|
|
|
|
|
# Explanation |
|
|
|
``VidProM_unique.csv`` contains the UUID, prompt, time, and 6 NSFW probabilities. |
|
|
|
It can easily be read by |
|
|
|
``` |
|
import pandas |
|
df = pd.read_csv("VidProM_unique.csv") |
|
``` |
|
|
|
Below are three rows from ``VidProM_unique.csv``: |
|
| uuid | prompt | time | toxicity | obscene | identity_attack | insult | threat | sexual_explicit | |
|
|--------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------|----------|---------|-----------------|---------|---------|-----------------| |
|
| 6a83eb92-faa0-572b-9e1f-67dec99b711d | Flying among clouds and stars, kitten Max discovered a world full of winged friends. Returning home, he shared his stories and everyone smiled as they imagined flying together in their dreams. | Sun Sep 3 12:27:44 2023 | 0.00129 | 0.00016 | 7e-05 | 0.00064 | 2e-05 | 2e-05 | |
|
| 3ba1adf3-5254-59fb-a13e-57e6aa161626 | Use a clean and modern font for the text "Relate Reality 101." Add a small, stylized heart icon or a thought bubble above or beside the text to represent emotions and thoughts. Consider using a color scheme that includes warm, inviting colors like deep reds, soft blues, or soothing purples to evoke feelings of connection and intrigue. | Wed Sep 13 18:15:30 2023 | 0.00038 | 0.00013 | 8e-05 | 0.00018 | 3e-05 | 3e-05 | |
|
| 62e5a2a0-4994-5c75-9976-2416420526f7 | zoomed out, sideview of an Grey Alien sitting at a computer desk | Tue Oct 24 20:24:21 2023 | 0.01777 | 0.00029 | 0.00336 | 0.00256 | 0.00017 | 5e-05 | |
|
|
|
|
|
``VidProM_semantic_unique.csv`` is a semantically unique version of ``VidProM_unique.csv``. |
|
|
|
``VidProM_embed.hdf5`` is the 3072-dim embeddings of our prompts. They are embedded by text-embedding-3-large, which is the latest text embedding model of OpenAI. |
|
|
|
It can easily be read by |
|
|
|
``` |
|
import numpy as np |
|
import h5py |
|
def read_descriptors(filename): |
|
hh = h5py.File(filename, "r") |
|
descs = np.array(hh["embeddings"]) |
|
names = np.array(hh["uuid"][:], dtype=object).astype(str).tolist() |
|
return names, descs |
|
|
|
uuid, features = read_descriptors('VidProM_embed.hdf5') |
|
``` |
|
|
|
``original_files`` are the HTML files from [official Pika Discord](https://discord.com/invite/pika) collected by [DiscordChatExporter](https://github.com/Tyrrrz/DiscordChatExporter). You can do whatever you want with it under [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). |
|
|
|
``pika_videos``, ``vc2_videos``, ``t2vz_videos``, and ``ms_videos`` are the generated videos by 4 state-of-the-art text-to-video diffusion models. Each contains 30 tar files. |
|
|
|
``example`` is a subfolder which contains 10,000 datapoints. |
|
|
|
|
|
# Datapoint |
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/datapoint.png" width="800"> |
|
</p> |
|
|
|
# Visualization |
|
|
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/WizMap.png" width="800"> |
|
</p> |
|
|
|
Click the [WizMap](https://poloclub.github.io/wizmap/?dataURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FWenhaoWang%2FVidProM%2Fresolve%2Fmain%2Fdata_gpu13.ndjson&gridURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FWenhaoWang%2FVidProM%2Fresolve%2Fmain%2Fgrid_gpu13.json) |
|
(and wait for 5 seconds) for an interactive visualization of our 1.67 million prompts. Above is a thumbnail. |
|
|
|
# Comparison with DiffusionDB |
|
|
|
|
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_table.png" width="800"> |
|
</p> |
|
|
|
<p align="center"> |
|
<img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_visual.png" width="800"> |
|
</p> |
|
|
|
Please check our paper for a detailed comparison. |
|
|
|
# Curators |
|
VidProM is created by [Wenhao Wang](https://wangwenhao0716.github.io/) and Professor [Yi Yang](https://scholar.google.com/citations?user=RMSuNFwAAAAJ&hl=zh-CN) from [the ReLER Lab](https://reler.net/). |
|
|
|
# License |
|
|
|
The prompts and videos generated by [Pika](https://discord.com/invite/pika) in our VidProM are licensed under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). Additionally, similar to their original repositories, the videos from [VideoCraft2](https://github.com/AILab-CVC/VideoCrafter), [Text2Video-Zero](https://github.com/Picsart-AI-Research/Text2Video-Zero), and [ModelScope](https://huggingface.co/ali-vilab/modelscope-damo-text-to-video-synthesis) are released under the [Apache license](https://www.apache.org/licenses/LICENSE-2.0), the [CreativeML Open RAIL-M license](https://github.com/Picsart-AI-Research/Text2Video-Zero/blob/main/LICENSE), and the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en), respectively. Our code is released under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). |
|
|
|
|
|
# Citation |
|
``` |
|
@article{wang2024vidprom, |
|
title={VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models}, |
|
author={Wang, Wenhao and Yang, Yi}, |
|
journal={arXiv preprint arXiv:2403.06098}, |
|
year={2024} |
|
} |
|
``` |
|
|
|
# Contact |
|
|
|
If you have any questions, feel free to contact Wenhao Wang (wangwenhao0716@gmail.com). |
|
|
