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README.md

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+# Open-Sora-Dataset
+
+[[Project Page]](https://pku-yuangroup.github.io/Open-Sora-Plan/) [[中文主页]](https://pku-yuangroup.github.io/Open-Sora-Plan/blog_cn.html)
+
+:bulb:  Welcome to the Open-Sora-DataSet project! As part of the [Open-Sora-Plan](https://pku-yuangroup.github.io/Open-Sora-Plan/) project, we specifically talk about the collection and processing of data sets. To build a high-quality video dataset for the open-source world, we started this project. 💪 
+
+We warmly welcome you to join us! Let's contribute to the open-source world together! Thank you for your support and contribution. :heart:  
+
+:bulb:  欢迎来到Open-Sora-DataSet项目！我们作为Open-Sora—Plan项目的一部分，详细阐述数据集的收集和处理。为给开源世界构建一个高质量的视频数据，我们发起了这个项目。💪 
+
+我们非常欢迎您的加入！让我们共同为开源的世界贡献力量！感谢您的支持和贡献。 :heart: 
+
+
+## Data Construction for Open-Sora-Plan v1.0.0
+### Data distribution
+we crawled 40258 videos from open-source websites under the CC0 license. All videos are of high quality without watermarks and All videos are of high quality without watermarks, and about 60% of them are landscape data. The total duration is about **274h 05m 13s**The main sources of data are divided into three parts：
+1. [mixkit](https://mixkit.co/):The total number of videos we collected is **1234**, the total duration is about **6h 19m 32s**, and the total number of frames is **570815**. The resolution and aspect ratio distribution histogram of the video is as follows (the ones that account for less than 1% are not listed)：
+
+<img src="assets/v1.0.0_mixkit_resolution_plot.png" width="400" /> <img src="assets/v1.0.0_mixkit_aspect_ratio_plot.png" width="400" />
+
+2. [pexels](https://www.pexels.com/zh-cn/):The total number of videos we collected is **7408** the total duration is about **48h 49m 24s** and the total number of frames is **5038641**. The resolution and aspect ratio distribution histogram of the video is as follows (the ones that account for less than 1% are not listed)：
+
+<img src="assets/v1.0.0_pexels_resolution_plot.png" height="300" /> <img src="assets/v1.0.0_pexels_aspect_ratio_plot.png" height="300" />  
+
+
+3. [pixabay](https://pixabay.com/):The total number of videos we collected is **31616** the total duration is about **218h 56m 17s** and the total number of frames is **23508970**. The resolution and aspect ratio distribution histogram of the video is as follows (the ones that account for less than 1% are not listed):
+
+<img src="assets/v1.0.0_pixabay_resolution_plot.png" height="300" /> <img src="assets/v1.0.0_pixabay_aspect_ratio_plot.png" height="300" />  
+
+
+### Dense captions
+it is challenging to directly crawl a large quantity of high-quality dense captions from the internet. Therefore, we utilize a mature Image-captioner model to obtain high-quality dense captions. We conducted ablation experiments on two multimodal large models: [ShareGPT4V-Captioner-7B](https://github.com/InternLM/InternLM-XComposer/blob/main/projects/ShareGPT4V/README.md) and [LLaVA-1.6-34B](https://github.com/haotian-liu/LLaVA). The former is specifically designed for caption generation, while the latter is a general-purpose multimodal large model. After conducting our ablation experiments, we found that they are comparable in performance. However, there is a significant difference in their inference speed on the A800 GPU: 40s/it of batch size of 12 for ShareGPT4V-Captioner-7B, 15s/it of batch size of 1 for LLaVA-1.6-34B. We open-source all annotations [here](https://huggingface.co/datasets/LanguageBind/Open-Sora-Plan-v1.0.0). We show some statistics here, and we set the maximum length of the model to 300, which covers almost 99% of the samples.
+
+| Name | Avg length | Max | Std |
+|---|---|---|---|
+| ShareGPT4V-Captioner-7B | 170.0827524529121 |  467 | 53.689967539537776 | 
+| LLaVA-1.6-34B | 141.75851073472666 |  472 | 48.52492072346965 | 
+
+
+
+## Video split
+### Video with transitions
+Use [panda-70m](https://github.com/snap-research/Panda-70M/tree/main/splitting) to split transition video
+
+### Video without transitions
+1. Clone this repository and navigate to Open-Sora-Plan folder
+```
+git clone https://github.com/PKU-YuanGroup/Open-Sora-Plan
+cd Open-Sora-Plan
+```
+2. Install the required packages
+```
+conda create -n opensora python=3.8 -y
+conda activate opensora
+pip install -e .
+```
+3. Split video script
+```
+git clone https://github.com/shaodong233/open-sora-Dataset.git
+python split/no_transition.py --video_json_file /path/to/your_video /path/to/save
+```
+
+
+If you want to know more, check out [Requirements and Installation](https://github.com/PKU-YuanGroup/Open-Sora-Plan?tab=readme-ov-file#%EF%B8%8F-requirements-and-installation)
+
+## Acknowledgement 👍
+Qingdao Weiyi Network Technology Co., Ltd.: Thank you very much for providing us with valuable data