Upload README.md

README.md

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+---
+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
+    num_examples: 100000
+  - name: Eval
+    num_bytes: 78258893
+    num_examples: 10000
+  download_size: 27500759907
+  dataset_size: 27750274851.25
+configs:
+- config_name: default
+  data_files:
+  - split: Full
+    path: data/Full-*
+  - split: Subset
+    path: data/Subset-*
+  - split: Eval
+    path: data/Eval-*
+tags:
+- prompt
+- image-to-video
+- text-to-video
+- visual-generation
+- video-generation
+pretty_name: TIP-I2V
+---
+
+# Summary
+This is the dataset proposed in our paper **TIP-I2V: A Million-Scale Real Prompt-Gallery Dataset for Image-to-Video Diffusion Models**.
+
+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.
+
+<p align="center">
+  <img src="https://huggingface.co/datasets/TIP-I2V/TIP-I2V/resolve/main/assets/teasor.png" width="1000">
+</p>
+
+# Datapoint
+<p align="center">
+  <img src="https://huggingface.co/datasets/TIP-I2V/TIP-I2V/resolve/main/assets/datapoint.png" width="1000">
+</p>
+
+# Statistics
+<p align="center">
+  <img src="https://huggingface.co/datasets/TIP-I2V/TIP-I2V/resolve/main/assets/stat.png" width="1000">
+</p>
+
+# 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
+
+```python
+# Full (text and compressed image) prompts: ~13.4G
+from datasets import load_dataset
+ds = load_dataset("TIP-I2V/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("TIP-I2V/TIP-I2V", split='Subset', streaming=True)
+
+# Convert to Pandas format (it may be slow)
+import pandas as pd
+df = pd.DataFrame(ds)
+```
+
+```python
+# 10k TIP-Eval (text and compressed image) prompts: ~0.08G
+from datasets import load_dataset
+ds = load_dataset("TIP-I2V/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
+
+```python
+# Embeddings for full text prompts (~21G) and image prompts (~3.5G)
+from huggingface_hub import hf_hub_download
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="Embedding/Full_Text_Embedding.parquet", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="Embedding/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="TIP-I2V/TIP-I2V", filename="Embedding/Subset_Text_Embedding.parquet", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="Embedding/Subset_Image_Embedding.parquet", repo_type="dataset")
+```
+
+```python
+# 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="TIP-I2V/TIP-I2V", filename="Embedding/Eval_Text_Embedding.parquet", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="Embedding/Eval_Image_Embedding.parquet", repo_type="dataset")
+```
+
+## Download uncompressed image prompts
+
+```python
+# Full uncompressed image prompts: ~1T
+from huggingface_hub import hf_hub_download
+for i in range(1,52):
+    hf_hub_download(repo_id="TIP-I2V/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="TIP-I2V/TIP-I2V", filename="sub_image_prompt_tar/sub_image_prompt_%d.tar"%i, repo_type="dataset")
+```
+
+```python
+# 10k TIP-Eval uncompressed image prompts: ~6.5G
+from huggingface_hub import hf_hub_download
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="eval_image_prompt_tar/eval_image_prompt.tar", repo_type="dataset")
+```
+
+## Download generated videos
+
+```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="TIP-I2V/TIP-I2V", filename="pika_videos_tar/pika_videos_%d.tar"%i, repo_type="dataset")
+```
+
+```python
+# 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="TIP-I2V/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_1.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/pika_videos_subset_2.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/svd_videos_subset.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/opensora_videos_subset.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/i2vgenxl_videos_subset_1.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/i2vgenxl_videos_subset_2.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="subset_videos_tar/cog_videos_subset.tar", repo_type="dataset")
+```
+
+```python
+# 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="TIP-I2V/TIP-I2V", filename="eval_videos_tar/pika_videos_eval.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="eval_videos_tar/svd_videos_eval.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="eval_videos_tar/opensora_videos_eval.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="eval_videos_tar/i2vgenxl_videos_eval.tar", repo_type="dataset")
+hf_hub_download(repo_id="TIP-I2V/TIP-I2V", filename="eval_videos_tar/cog_videos_eval.tar", repo_type="dataset")
+```
+
+# Comparison with VidProM and DiffusionDB
+<p align="center">
+  <img src="https://huggingface.co/datasets/TIP-I2V/TIP-I2V/resolve/main/assets/table.png" width="1000">
+</p>
+<p align="center">
+  <img src="https://huggingface.co/datasets/TIP-I2V/TIP-I2V/resolve/main/assets/comparison.png" width="1000">
+</p>
+
+Click the [WizMap (TIP-I2V VS VidProM)](https://poloclub.github.io/wizmap/?dataURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FTIP-I2V%2FTIP-I2V%2Fresolve%2Fmain%2Ftip-i2v-visualize%2Fdata_tip-i2v_vidprom.ndjson&gridURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FTIP-I2V%2FTIP-I2V%2Fresolve%2Fmain%2Ftip-i2v-visualize%2Fgrid_tip-i2v_vidprom.json) and [WizMap (TIP-I2V VS DiffusionDB)](https://poloclub.github.io/wizmap/?dataURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FTIP-I2V%2FTIP-I2V%2Fresolve%2Fmain%2Ftip-i2v-visualize%2Fdata_tip-i2v_diffusiondb.ndjson&gridURL=https%3A%2F%2Fhuggingface.co%2Fdatasets%2FTIP-I2V%2FTIP-I2V%2Fresolve%2Fmain%2Ftip-i2v-visualize%2Fgrid_tip-i2v_diffusiondb.json)
+(wait for 5 seconds) for an interactive visualization of our 1.70 million prompts.
+
+
+# License
+
+The prompts and videos in our TIP-I2V are licensed under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). 
+