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Datasets:
tipi2v
/
TIP-I2V

Tasks:
Image-to-Video
Text-to-Video
Text-to-Image
Modalities:
Image
Text
Formats:
parquet
Languages:
English
Size:
1M - 10M
Tags:
prompt
image-to-video
visual-generation
video-generation
Libraries:
Datasets
Dask
License:
Dataset card Data Studio Files Community
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metadata
language:
  - en
license: cc-by-nc-4.0
size_categories:
  - 1M<n<10M
task_categories:
  - image-to-video
  - text-to-video
  - text-to-image
  - image-to-image
pretty_name: TIP-I2V
tags:
  - prompt
  - image-to-video
  - visual-generation
  - video-generation
dataset_info:
  features:
    - name: UUID
      dtype: string
    - name: UserID
      dtype: string
    - name: Text_Prompt
      dtype: string
    - name: Image_Prompt
      dtype: image
    - name: Subject
      dtype: string
    - name: Direction
      dtype: string
    - name: Timestamp
      dtype: string
    - name: Text_NSFW
      dtype: float32
    - name: Image_NSFW
      dtype: string
  splits:
    - name: Full
      num_bytes: 13538959055.45
      num_examples: 1701935
    - name: Subset
      num_bytes: 796512047
      num_examples: 100000
    - name: Eval
      num_bytes: 78836541
      num_examples: 10000
  download_size: 14247800861
  dataset_size: 14414307643.45
configs:
  - config_name: default
    data_files:
      - split: Full
        path: data/Full-*
      - split: Subset
        path: data/Subset-*
      - split: Eval
        path: data/Eval-*

News

🌟 Downloaded 10,000+ times on Hugging Face after one month of release.

✨ Ranked Top 1 in the Hugging Face Dataset Trending List for the visual generation community (image-to-video, text-to-video, text-to-image, and image-to-image) on November 10, 2024.

Summary

This is the dataset proposed in our paper TIP-I2V: A Million-Scale Real Text and Image Prompt Dataset for Image-to-Video Generation.

TIP-I2V is the first dataset comprising over 1.70 million unique user-provided text and image prompts. Besides the prompts, TIP-I2V also includes videos generated by five state-of-the-art image-to-video models (Pika, Stable Video Diffusion, Open-Sora, I2VGen-XL, and CogVideoX-5B). The TIP-I2V contributes to the development of better and safer image-to-video models.

Datapoint

Statistics

Examples

Download

For users in mainland China, try setting export HF_ENDPOINT=https://hf-mirror.com to successfully download the weights.

Download the text and (compressed) image prompts with related information 

# Full (text and compressed image) prompts: ~13.4G
from datasets import load_dataset
ds = load_dataset("tipi2v/TIP-I2V", split='Full', streaming=True)

# Convert to Pandas format (it may be slow)
import pandas as pd
df = pd.DataFrame(ds)

# 100k subset (text and compressed image) prompts: ~0.8G
from datasets import load_dataset
ds = load_dataset("tipi2v/TIP-I2V", split='Subset', streaming=True)

# Convert to Pandas format (it may be slow)
import pandas as pd
df = pd.DataFrame(ds)

# 10k TIP-Eval (text and compressed image) prompts: ~0.08G
from datasets import load_dataset
ds = load_dataset("tipi2v/TIP-I2V", split='Eval', streaming=True)

# Convert to Pandas format (it may be slow)
import pandas as pd
df = pd.DataFrame(ds)

Download the embeddings for text and image prompts 

# Embeddings for full text prompts (~21G) and image prompts (~3.5G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Full_Text_Embedding.parquet", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Full_Image_Embedding.parquet", repo_type="dataset")

# Embeddings for 100k subset text prompts (~1.2G) and image prompts (~0.2G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Subset_Text_Embedding.parquet", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Subset_Image_Embedding.parquet", repo_type="dataset")

# Embeddings for 10k TIP-Eval text prompts (~0.1G) and image prompts (~0.02G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Eval_Text_Embedding.parquet", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="Embedding/Eval_Image_Embedding.parquet", repo_type="dataset")

Download uncompressed image prompts 

# Full uncompressed image prompts: ~1T
from huggingface_hub import hf_hub_download
for i in range(1,52):
    hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="image_prompt_tar/image_prompt_%d.tar"%i, repo_type="dataset")

# 100k subset uncompressed image prompts: ~69.6G
from huggingface_hub import hf_hub_download
for i in range(1,3):
    hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="sub_image_prompt_tar/sub_image_prompt_%d.tar"%i, repo_type="dataset")

# 10k TIP-Eval uncompressed image prompts: ~6.5G
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_image_prompt_tar/eval_image_prompt.tar", repo_type="dataset")

Download generated videos 

# Full videos generated by Pika: ~1T
from huggingface_hub import hf_hub_download
for i in range(1,52):
    hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="pika_videos_tar/pika_videos_%d.tar"%i, repo_type="dataset")

# 100k subset videos generated by Pika (~57.6G), Stable Video Diffusion (~38.9G), Open-Sora (~47.2G), I2VGen-XL (~54.4G), and CogVideoX-5B (~36.7G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_1.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_2.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/svd_videos_subset.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/opensora_videos_subset.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/i2vgenxl_videos_subset_1.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/i2vgenxl_videos_subset_2.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="subset_videos_tar/cog_videos_subset.tar", repo_type="dataset")

# 10k TIP-Eval videos generated by Pika (~5.8G), Stable Video Diffusion (~3.9G), Open-Sora (~4.7G), I2VGen-XL (~5.4G), and CogVideoX-5B (~3.6G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_videos_tar/pika_videos_eval.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_videos_tar/svd_videos_eval.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_videos_tar/opensora_videos_eval.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_videos_tar/i2vgenxl_videos_eval.tar", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="eval_videos_tar/cog_videos_eval.tar", repo_type="dataset")

Download original HTML files 

# 10 files (~32G)
from huggingface_hub import hf_hub_download
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-1 [1123665843365093487].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-2 [1126318113038798948].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-3 [1129173119609876580].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-4 [1129173161527750727].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-5 [1129173449592553564].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-6 [1134375192890712074].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-7 [1134375328442224690].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-8 [1134375370590802051].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-9 [1134375412189908992].html", repo_type="dataset")
hf_hub_download(repo_id="tipi2v/TIP-I2V", filename="raw_html/Pika - Creations - generate-10 [1134375457236725770].html", repo_type="dataset")

Comparison with VidProM and DiffusionDB

Click the WizMap (TIP-I2V VS VidProM) and WizMap (TIP-I2V VS DiffusionDB) (wait for 5 seconds) for an interactive visualization of our 1.70 million prompts. (The WizMap visualization website is maintained by its official team rather than by us, ensuring that the anonymity requirement is not violated.)

License

The prompts and videos in our TIP-I2V are licensed under the CC BY-NC 4.0 license.