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## πŸŽ₯ Latest Demo +More samples are available in our [gallery](https://hpcaitech.github.io/Open-Sora/). -| **2s 240Γ—426** | **2s 240Γ—426** | -| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2) | -| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/f7ce4aaa-528f-40a8-be7a-72e61eaacbbd) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/5d58d71e-1fda-4d90-9ad3-5f2f7b75c6a9) | +| **2s 240Γ—426** | **2s 240Γ—426** | +| ----------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c31ebc52-de39-4a4e-9b1e-9211d45e05b2) | +| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/f7ce4aaa-528f-40a8-be7a-72e61eaacbbd) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/5d58d71e-1fda-4d90-9ad3-5f2f7b75c6a9) | -| **2s 426Γ—240** | **2s 426Γ—240** | **4s 480Γ—854** | -| ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/34ecb4a0-4eef-4286-ad4c-8e3a87e5a9fd) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/3e892ad2-9543-4049-b005-643a4c1bf3bf) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c1619333-25d7-42ba-a91c-18dbc1870b18) | +| **2s 426Γ—240** | **2s 426Γ—240** | **4s 480Γ—854** | +| ---------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | +| [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/34ecb4a0-4eef-4286-ad4c-8e3a87e5a9fd) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/3e892ad2-9543-4049-b005-643a4c1bf3bf) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/c1619333-25d7-42ba-a91c-18dbc1870b18) |

@@ -63,8 +64,6 @@ see [here](/assets/texts/t2v_samples.txt) for full prompts.
-More samples are available in our [gallery](https://hpcaitech.github.io/Open-Sora/). - ## πŸ”† New Features/Updates * πŸ“ **Open-Sora 1.1** released. Model weights are available [here](). It is trained on **0s~15s, 144p to 720p, various aspect ratios** videos. See our **[report 1.1](docs/report_02.md)** for more discussions. @@ -176,11 +175,10 @@ pip install -v . ### Open-Sora 1.1 Model Weights -| Resolution | Data | #iterations | Batch Size | URL | -| ---------- | --------------------- | ----------- | ---------- | --------------------------------------------------------------------------------------------- | -| dynamic | 10M videos + 2M images | 100 | dynamic | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage2) | -| dynamic | 20K HQ | 4k | dynamic | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage3) | - +| Resolution | Data | #iterations | Batch Size | URL | +| ------------------ | -------------------------- | ----------- | ------------------------------------------------- | -------------------------------------------------------------------- | +| mainly 144p & 240p | 10M videos + 2M images | 100k | [dynamic](/configs/opensora-v1-1/train/stage2.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage2) | +| 144p to 720p | 500K HQ videos + 1M images | 4k | [dynamic](/configs/opensora-v1-1/train/stage3.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage3) | ### Open-Sora 1.0 Model Weights @@ -223,12 +221,12 @@ This will launch a Gradio application on your localhost. If you want to know mor Since Open-Sora 1.1 supports inference with dynamic input size, you can pass the input size as an argument. ```bash -# video sampling +# text to video python scripts/inference.py configs/opensora-v1-1/inference/sample.py \ --ckpt-path CKPT_PATH --prompt "A beautiful sunset over the city" --num-frames 32 --image-size 480 854 ``` -See [here](docs/commands.md#inference-with-open-sora-11) for more instructions. +See [here](docs/commands.md#inference-with-open-sora-11) for more instructions including text-to-image, image-to-video, video-to-video, and infinite time generation. ### Open-Sora 1.0 Command Line Inference diff --git a/docs/report_02.md b/docs/report_02.md index 9d2c1eb8..ec54853d 100644 --- a/docs/report_02.md +++ b/docs/report_02.md @@ -106,7 +106,7 @@ To summarize, the training of Open-Sora 1.1 requires approximately **9 days** on As we get one step closer to the replication of Sora, we find many limitations for the current model, and these limitations point to the future work. -- **Generation Failure**: we fine many cases (especially when the total token number is large or the content is complex), our model fails to generate the scene. There may be a collapse in the temporal attention and we have identified a potential bug in our code. We are working hard to fix it. +- **Generation Failure**: we fine many cases (especially when the total token number is large or the content is complex), our model fails to generate the scene. There may be a collapse in the temporal attention and we have identified a potential bug in our code. We are working hard to fix it. Besides, we will increase our model size and training data to improve the generation quality in the next version. - **Noisy generation and influency**: we find the generated model is sometimes noisy and not fluent, especially for long videos. We think the problem is due to not using a temporal VAE. As [Pixart-Sigma](https://arxiv.org/abs/2403.04692) finds that adapting to a new VAE is simple, we plan to develop a temporal VAE for the model in the next version. - **Lack of time consistency**: we find the model cannot generate videos with high time consistency. We think the problem is due to the lack of training FLOPs. We plan to collect more data and continue training the model to improve the time consistency. - **Bad human generation**: We find the model cannot generate high-quality human videos. We think the problem is due to the lack of human data. We plan to collect more human data and continue training the model to improve the human generation. From 5c1af71213454210a622871192b5ba9a8675b606 Mon Sep 17 00:00:00 2001 From: Zangwei Zheng Date: Thu, 25 Apr 2024 19:21:35 +0800 Subject: [PATCH 3/3] update readme --- README.md | 56 ++++++++++++++++++------------------------------ docs/datasets.md | 38 +++++++++++++++++++++----------- 2 files changed, 47 insertions(+), 47 deletions(-) diff --git a/README.md b/README.md index 2f43cfc9..3b9af882 100644 --- a/README.md +++ b/README.md @@ -20,9 +20,7 @@ Open-Sora not only democratizes access to advanced video generation techniques, streamlined and user-friendly platform that simplifies the complexities of video production. With Open-Sora, we aim to inspire innovation, creativity, and inclusivity in the realm of content creation. -[[δΈ­ζ–‡ζ–‡ζ‘£]](/docs/zh_CN/README.md) - -[ζ½žζ™¨δΊ‘ιƒ¨η½²Open-Sora保姆级视钑教程](https://www.bilibili.com/video/BV141421R7Ag) +[[δΈ­ζ–‡ζ–‡ζ‘£]](/docs/zh_CN/README.md) [[ζ½žζ™¨δΊ‘ιƒ¨η½²θ§†ι’‘ζ•™η¨‹]](https://www.bilibili.com/video/BV141421R7Ag)

Open-Sora is still at an early stage and under active development.

@@ -41,9 +39,7 @@ With Open-Sora, we aim to inspire innovation, creativity, and inclusivity in the ## πŸŽ₯ Latest Demo -πŸ”₯ You can experinece Open-Sora on our [πŸ€— Gradio application on Hugging Face](https://huggingface.co/spaces/hpcai-tech/open-sora) - -More samples are available in our [gallery](https://hpcaitech.github.io/Open-Sora/). +πŸ”₯ You can experinece Open-Sora on our [πŸ€— Gradio application on Hugging Face](https://huggingface.co/spaces/hpcai-tech/open-sora). More samples are available in our [Gallery](https://hpcaitech.github.io/Open-Sora/). | **2s 240Γ—426** | **2s 240Γ—426** | | ----------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------- | @@ -57,6 +53,10 @@ More samples are available in our [gallery](https://hpcaitech.github.io/Open-Sor | **16s 320Γ—320** | **16s 224Γ—448** | **2s 426Γ—240** | | ------------------------------------------------------------------------------------------------------------------------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------ | --------------------------------------------------------------------------------------------------------------------------------------------------------- | | [](https://github.com/hpcaitech/Open-Sora/assets/99191637/3cab536e-9b43-4b33-8da8-a0f9cf842ff2) | [](https://github.com/hpcaitech/Open-Sora/assets/99191637/9fb0b9e0-c6f4-4935-b29e-4cac10b373c4) | [](https://github.com/hpcaitech/Open-Sora-dev/assets/99191637/3e892ad2-9543-4049-b005-643a4c1bf3bf) | +<<<<<<< Updated upstream +======= + +>>>>>>> Stashed changes
OpenSora 1.0 Demo @@ -114,8 +114,8 @@ see [here](/assets/texts/t2v_samples.txt) for full prompts. ### TODO list sorted by priority * [ ] Training Video-VAE and adapt our model to new VAE. **[WIP]** -* [ ] Incoporate a better scheduler, e.g., rectified flow in SD3. -* [ ] Scaling model parameters and dataset size. +* [ ] Scaling model parameters and dataset size. **[WIP]** +* [ ] Incoporate a better scheduler, e.g., rectified flow in SD3. **[WIP]**
View more @@ -184,21 +184,25 @@ pip install -v . ### Open-Sora 1.1 Model Weights -| Resolution | Data | #iterations | Batch Size | URL | -| ------------------ | -------------------------- | ----------- | ------------------------------------------------- | -------------------------------------------------------------------- | -| mainly 144p & 240p | 10M videos + 2M images | 100k | [dynamic](/configs/opensora-v1-1/train/stage2.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage2) | -| 144p to 720p | 500K HQ videos + 1M images | 4k | [dynamic](/configs/opensora-v1-1/train/stage3.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage3) | +| Resolution | Model Size | Data | #iterations | Batch Size | URL | +| ------------------ | ---------- | -------------------------- | ----------- | ------------------------------------------------- | -------------------------------------------------------------------- | +| mainly 144p & 240p | 700M | 10M videos + 2M images | 100k | [dynamic](/configs/opensora-v1-1/train/stage2.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage2) | +| 144p to 720p | 700M | 500K HQ videos + 1M images | 4k | [dynamic](/configs/opensora-v1-1/train/stage3.py) | [:link:](https://huggingface.co/hpcai-tech/OpenSora-STDiT-v2-stage3) | + +See our **[report 1.1](docs/report_02.md)** for more infomation. + +:warning: **LIMITATION**: This version contains known issues which we are going to fix in the next version (as we save computation resource for the next release). In addition, the video generation may fail for long duration, and high resolution will have noisy results due to this problem. ### Open-Sora 1.0 Model Weights
View more -| Resolution | Data | #iterations | Batch Size | GPU days (H800) | URL | -| ---------- | ------ | ----------- | ---------- | --------------- | --------------------------------------------------------------------------------------------- | -| 16Γ—512Γ—512 | 20K HQ | 20k | 2Γ—64 | 35 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x512x512.pth) | -| 16Γ—256Γ—256 | 20K HQ | 24k | 8Γ—64 | 45 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x256x256.pth) | -| 16Γ—256Γ—256 | 366K | 80k | 8Γ—64 | 117 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-16x256x256.pth) | +| Resolution | Model Size | Data | #iterations | Batch Size | GPU days (H800) | URL | +| ---------- | ---------- | ------ | ----------- | ---------- | --------------- | +| 16Γ—512Γ—512 | 700M | 20K HQ | 20k | 2Γ—64 | 35 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x512x512.pth) | +| 16Γ—256Γ—256 | 700M | 20K HQ | 24k | 8Γ—64 | 45 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-HQ-16x256x256.pth) | +| 16Γ—256Γ—256 | 700M | 366K | 80k | 8Γ—64 | 117 | [:link:](https://huggingface.co/hpcai-tech/Open-Sora/blob/main/OpenSora-v1-16x256x256.pth) | Training orders: 16x256x256 $\rightarrow$ 16x256x256 HQ $\rightarrow$ 16x512x512 HQ. @@ -328,24 +332,6 @@ following [all-contributors](https://github.com/all-contributors/all-contributor - - - - - - - - - - - - - - - - - -
zhengzangw
zhengzangw

πŸ’» πŸ“– πŸ€” πŸ“Ή 🚧
ver217
ver217

πŸ’» πŸ€” πŸ“– πŸ›
FrankLeeeee
FrankLeeeee

πŸ’» πŸš‡ πŸ”§
xyupeng
xyupeng

πŸ’» πŸ“– 🎨
Yanjia0
Yanjia0

πŸ“–
binmakeswell
binmakeswell

πŸ“–
eltociear
eltociear

πŸ“–
ganeshkrishnan1
ganeshkrishnan1

πŸ“–
fastalgo
fastalgo

πŸ“–
powerzbt
powerzbt

πŸ“–
diff --git a/docs/datasets.md b/docs/datasets.md index bdf54713..ca096357 100644 --- a/docs/datasets.md +++ b/docs/datasets.md @@ -3,36 +3,50 @@ For Open-Sora 1.1, we conduct mixed training with both images and videos. The main datasets we use are listed below. Please refer to [README](/README.md#data-processing) for data processing. -## Panda-70M +## Video + +### Panda-70M + [Panda-70M](https://github.com/snap-research/Panda-70M) is a large-scale dataset with 70M video-caption pairs. -We use the [training-10M subset](https://github.com/snap-research/Panda-70M/tree/main/dataset_dataloading) for training, +We use the [training-10M subset](https://github.com/snap-research/Panda-70M/tree/main/dataset_dataloading) for training, which contains ~10M videos of better quality. -## Pexels -[Pexels](https://www.pexels.com/) is a popular online platform that provides high-quality stock photos, videos, and music for free. +### Pexels + +[Pexels](https://www.pexels.com/) is a popular online platform that provides high-quality stock photos, videos, and music for free. Most videos from this website are of high quality. Thus, we use them for both pre-training and HQ fine-tuning. We really appreciate the great platform and the contributors! -## Inter4K +### Inter4K + [Inter4K](https://github.com/alexandrosstergiou/Inter4K) is a dataset containing 1K video clips with 4K resolution. The dataset is proposed for super-resolution tasks. We use the dataset for HQ fine-tuning. +### HD-VG-130M -## HD-VG-130M -[HD-VG-130M](https://github.com/daooshee/HD-VG-130M?tab=readme-ov-file) comprises 130M text-video pairs. -The caption is generated by BLIP-2. +[HD-VG-130M](https://github.com/daooshee/HD-VG-130M?tab=readme-ov-file) comprises 130M text-video pairs. +The caption is generated by BLIP-2. We find the scene and the text quality are relatively poor. For OpenSora 1.0, we only use ~350K samples from this dataset. -## Midjourney-v5-1.7M +## Image + +### Midjourney-v5-1.7M + [Midjourney-v5-1.7M](https://huggingface.co/datasets/wanng/midjourney-v5-202304-clean) includes 1.7M image-text pairs. In detail, this dataset introduces two subsets: original and upscale. This dataset is proposed for exploring the relationship of prompts and high-quality images. -## Midjourney-kaggle-clean +### Midjourney-kaggle-clean + [Midjourney-kaggle-clean](https://huggingface.co/datasets/wanng/midjourney-kaggle-clean) is a reconstructed version of [Midjourney User Prompts & Generated Images (250k)](https://www.kaggle.com/datasets/succinctlyai/midjourney-texttoimage?select=general-01_2022_06_20.json%5D), which is cleaned by rules. Moreover, this dataset is divided into two subsets: original and upscale. This dataset is proposed for enabling research on text-to-image model prompting. -## upsplash-lite -The [Unsplash-lite](https://github.com/unsplash/datasets) Dataset comprises 25k nature-themed Unsplash photos, 25k keywords, and 1M searches. +### upsplash-lite + +The [Unsplash-lite](https://github.com/unsplash/datasets) Dataset comprises 25k nature-themed Unsplash photos, 25k keywords, and 1M searches. This dataset covers a vast range of uses and contexts. Its extensive scope in intent and semantics opens new avenues for research and learning. + +### LAION-AESTHETICS 6.5+ + +LAION aesthetic 6.5+ dataset is a subset of the LAION dataset, which contains 625K high-quality images with aesthetic scores > 6.5. However, as LAION is currently not publicly available, we use this 168k [subset](https://huggingface.co/datasets/bhargavsdesai/laion_improved_aesthetics_6.5plus_with_images).