|
--- |
|
language: |
|
- en |
|
license: cc-by-nc-4.0 |
|
size_categories: |
|
- 1M<n<10M |
|
task_categories: |
|
- image-to-video |
|
- text-to-video |
|
dataset_info: |
|
features: |
|
- name: UUID |
|
dtype: string |
|
- name: Text_Prompt |
|
dtype: string |
|
- name: Image_Prompt |
|
dtype: image |
|
- name: Subject |
|
dtype: string |
|
- name: Timestamp |
|
dtype: string |
|
- name: Text_NSFW |
|
dtype: float32 |
|
- name: Image_NSFW |
|
dtype: string |
|
splits: |
|
- name: Full |
|
num_bytes: 13440652664.125 |
|
num_examples: 1701935 |
|
- name: Subset |
|
num_bytes: 790710630.0 |
|
num_examples: 100000 |
|
download_size: 27346257675 |
|
dataset_size: 27672015958.25 |
|
configs: |
|
- config_name: default |
|
data_files: |
|
- split: Full |
|
path: data/Full-* |
|
- split: Subset |
|
path: data/Subset-* |
|
tags: |
|
- prompt |
|
- image-to-video |
|
- text-to-video |
|
--- |
|
|
|
```python |
|
# Full (text and compressed image) prompts: ~13.4G |
|
from datasets import load_dataset |
|
ds = load_dataset("WenhaoWang/TIP-I2V", split='Full', streaming=True) |
|
|
|
# Convert to Pandas format (it may be slow) |
|
import pandas as pd |
|
df = pd.DataFrame(ds) |
|
``` |
|
|
|
|
|
```python |
|
# 100k subset (text and compressed image) prompts: ~0.8G |
|
from datasets import load_dataset |
|
ds = load_dataset("WenhaoWang/TIP-I2V", split='Subset', streaming=True) |
|
|
|
# Convert to Pandas format (it may be slow) |
|
import pandas as pd |
|
df = pd.DataFrame(ds) |
|
``` |
|
|
|
```python |
|
# Embeddings for full text prompts (~21G) and image prompts (~3.5G) |
|
from huggingface_hub import hf_hub_download |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="Full_Text_Embedding.parquet", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="Full_Image_Embedding.parquet", repo_type="dataset") |
|
``` |
|
|
|
```python |
|
# 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="WenhaoWang/TIP-I2V", filename="Subset_Text_Embedding.parquet", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="Subset_Image_Embedding.parquet", repo_type="dataset") |
|
``` |
|
|
|
|
|
```python |
|
# Full uncompressed image prompts: ~1T |
|
from huggingface_hub import hf_hub_download |
|
for i in range(1,52): |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="image_prompt_tar/image_prompt_%d.tar"%i, repo_type="dataset") |
|
``` |
|
|
|
```python |
|
# 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="WenhaoWang/TIP-I2V", filename="sub_image_prompt_tar/sub_image_prompt_%d.tar"%i, repo_type="dataset") |
|
``` |
|
|
|
```python |
|
# Full videos generated by Pika: ~1T |
|
from huggingface_hub import hf_hub_download |
|
for i in range(1,52): |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="pika_videos_tar/pika_videos_%d.tar"%i, repo_type="dataset") |
|
``` |
|
|
|
```python |
|
# 100k subset videos generated by Pika (~xxG), Stable Video Diffusion (~xxG), Open-Sora (~xxG), I2VGen-XL (~xxG), and CogVideoX-5B (~xxG) |
|
from huggingface_hub import hf_hub_download |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_1.tar", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_2.tar", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/svd_videos_subset.tar", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/opensora_videos_subset.tar", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/i2vgenxl_videos_subset.tar", repo_type="dataset") |
|
hf_hub_download(repo_id="WenhaoWang/TIP-I2V", filename="subset_videos_tar/cog_videos_subset.tar", repo_type="dataset") |
|
``` |
|
|
|
|
|
|
