Stable Video Diffusion: The Future of AI Video Generation

You can use Stable Video Diffusion (SVD) to generate a video of a few seconds based on the original image. Try it out!

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What is Stable Video Diffusion?

Stable Video Diffusion Example 1 Stable Video Diffusion (SVD) Image-to-Video is a diffusion model designed to utilize a static image as a conditioning frame, enabling the generation of a video based on this single image input. It is one member of Stability AI's diverse family of open-source models. Looking at it now, their products span across various modalities such as images, language, audio, 3D, and code. This dedication to enhancing AI stands as a testament to their commitment to excellence.

What is Stable Video Diffusion Used For?

Stable Video Diffusion Example 2 Stable Video Diffusion stands at the forefront of cutting-edge AI technology, offering a powerful platform for video generation and synthesis. This innovative model is designed to transform still images into dynamic, high-quality videos with impressive flexibility and customization.

Utilizing a diffusion model architecture, Stable Video Diffusion takes a single image as input and employs advanced algorithms to generate seamless, lifelike videos. Whether it's creating captivating visual content for marketing campaigns, producing realistic scenes for entertainment purposes, or enabling researchers to explore new frontiers in AI, the applications of Stable Video Diffusion are diverse and promising.

Who Can Benefit from Using Stable Video Diffusion?

Stable Video Diffusion Example 3 Content Creators and Marketers: Stable Video Diffusion empowers content creators and marketers to elevate their visual storytelling. It enables the creation of engaging video content from still images, enhancing brand narratives and captivating audiences.

Entertainment Industry Professionals: For filmmakers, animators, and video game developers, Stable Video Diffusion offers a groundbreaking tool for generating realistic scenes and enhancing visual effects. It streamlines the process of converting static images into dynamic, lifelike videos.

AI Researchers and Developers: Researchers exploring the realms of artificial intelligence can leverage Stable Video Diffusion to delve into the complexities of video synthesis. Its adaptability to various tasks allows for experimentation and innovation in AI.

Interested Users: While not universally accessible yet, Stable Video Diffusion has opened registration for interested users. Those eager to explore its capabilities and harness its potential can join the waiting list for future access and utilization.

Key Features of Stable Video Diffusion

Stable Video Diffusion Example 34

Getting Started with Stable Video Diffusion

At the moment, not everyone can access it yet. Stable Video Diffusion has opened registration for a waiting list for users contact. But the code is available on GitHub and HuggingFace: SVD-XT and SVD, you can try it out for yourself.

How to Create an AI Video Using Stable Video Diffusion on Colab

Stable Video Diffusion using Colab Currently, it's recommended to use Colab for cloud deployment to run Stable Video Diffusion. Below is the specific process. After becoming a member, the speed to generate a 4-second video using an A100 graphics card is 53 seconds, while with a T4 graphics card, it's 7 minutes. This information is provided for reference.

First, open the Colab notebook link: Stable Video Diffusion Colab. Then, click on the play icon sequentially to run different cells and configure the environment and model.

  1. Cell 1: Setup Running this cell might show an error, but it doesn't affect the generation. Look for a green checkmark beside the play button to confirm completion.

  2. Cell 2: Colab hack for SVD

  3. Cell 3: Download weights

  4. Cell 4: Load Model

  5. Cell 5: Sampling function

  6. Cell 6: Do the Run! This is the final cell. Upon successful execution, you'll see an address. Clicking this address opens a webpage where you can upload images for generation.

Adjusting advanced options is generally unnecessary. Setting values too high may cause memory issues. Remember, only PNG format is supported. Convert images in other formats to PNG. The generated resolution is 1024x576. Images not in this aspect ratio can be compressed or automatically adjusted to fit this size.

After generating the video, the interface will display the video. Remember to download and save the video.

How to Install Stable Video Diffusion on Your Computer

1. Cloning the Official Repository

Start by cloning the official repository of Stability AI's generative models. Use the following commands in your terminal to clone and navigate into the generative-models directory:

git clone [email protected]:Stability-AI/generative-models.git
cd generative-models

2. Setting Up the Virtual Environment

After successfully cloning the repository and moving into the generative-models root directory, you'll need to set up a virtual environment. This step is crucial for maintaining dependencies and project-specific configurations separate from your global Python setup.

Important Note: The instructions provided are specifically tested and confirmed to work under python3.10. If you are using a different version of Python, you may encounter compatibility issues or version conflicts.

Here's how to set up the virtual environment for PyTorch 2.0:

# Create and activate the virtual environment
python3 -m venv .pt2
source .pt2/bin/activate

# Install required packages from PyPI
pip3 install -r requirements/pt2.txt

3. Installing sgm

The next step involves the installation of sgm. While in your virtual environment, run the following command:

pip3 install .

This command installs the sgm package which is essential for the functioning of the generative models.

4. Installing sdata for Training

For training purposes, you need to install sdata. This package is vital for managing and processing data in the context of Stability AI's data pipelines. Use the following command to install sdata:

pip3 install -e git+

This command ensures that you have the latest version of sdata directly from the Stability AI's GitHub repository.

Stable Video Diffusion Alternatives

In the rapidly evolving world of AI video generation, Stable Video Diffusion stands out for its capabilities and open-source nature. However, for those looking to explore different options, here's a look at some noteworthy alternatives:

AI Moonvalley

Stable Video Diffusion Alternative: AI Moonvalley AI Moonvalley’s video generator is a powerful AI model that can generate high-quality cinematic videos from text prompts. The model uses advanced machine learning techniques to understand and visualize text, producing stunning and lively video clips in various styles such as hyperrealism, anime, and fantasy. The generated videos are of HD quality and have a 16:9 aspect ratio. The model is currently in beta and is free to use. It is available on Discord, a popular communication platform.

Runway Gen-2

Stable Video Diffusion Alternative: Runway Gen-2 Runway Gen-2 is a powerful AI tool that enables users to generate unique videos from text prompts or just using pen tool to modify video. It uses advanced machine learning techniques to create high-quality videos in various styles such as hyperrealism, anime, and fantasy.

Other Alternatives:

  1. DeepArt: Focused more on artistic style transfer, DeepArt uses neural networks to apply artistic effects to videos. It's great for creators looking to infuse their videos with a unique, artistic touch.

  2. RunwayML: An excellent tool for beginners and professionals alike, RunwayML offers a user-friendly interface to create AI-powered videos. It provides a wide range of models and functionalities, making it a versatile choice for various creative needs.

  3. Artbreeder: Known for its capability to blend and mutate images using AI, Artbreeder also offers some video manipulation features. It's particularly well-suited for experimental visual projects where blending and evolving images are central.

  4. Synthesia: Synthesia excels in creating AI videos, especially for business use-cases like training videos, presentations, and explainer videos. It allows users to create videos from text, using AI avatars as presenters.

  5. Descript: This tool is more than just a video editor; it uses AI to transcribe, edit, and polish videos. Descript is ideal for podcasters, marketers, and educators who want to create professional-grade videos with minimal effort.

  6. Pictory: Pictory leverages AI to transform scripts into engaging videos. It's particularly useful for marketing and social media content, where quick, eye-catching videos are needed.

  7. Ebsynth: For those interested in frame-by-frame video synthesis, Ebsynth offers a unique approach. It's especially useful for animators and artists who want to apply consistent styles across video frames.

  8. Motionbox: This tool is designed for creating animated videos with ease. It provides AI-driven features to automate parts of the video creation process, saving time and effort for content creators.

  9. Lumen5: Lumen5 uses AI to assist in creating engaging video content from text sources like blog posts. It's an excellent tool for content marketers looking to repurpose written content into video format.

  10. Videvo: While not a direct AI video generation tool, Videvo offers a vast library of stock video footage that can be incorporated into AI-generated videos for added depth and variety.

Frequently Asked Questions

Is Stable Video Diffusion free to use?

Yes, Stable Video Diffusion operates under an open-source model, allowing users to access and utilize its features without any direct cost. This accessibility makes it a valuable tool for various professionals and enthusiasts interested in advanced video synthesis without financial constraints.

Is Stable Video Diffusion worth it?

The worth of Stable Video Diffusion depends on individual needs. For content creators, marketers, entertainment industry professionals, and AI researchers seeking advanced video synthesis capabilities, Stable Video Diffusion presents a compelling tool. Its ability to generate high-quality videos from single images, adapt to various downstream tasks, and offer customization options makes it a valuable asset in the field of AI-driven video generation.

How to create AI video for free?

Creating AI-generated videos for free often involves leveraging open-source platforms or services that offer limited free access. Stable Video Diffusion, while not universally accessible for free at the moment, offers potential access through a waiting list. Alternatively, exploring other AI-driven video generation tools and platforms that provide free trials or limited access could be a way to create AI videos without immediate cost. Open-source resources and community-driven projects also offer avenues for experimenting with AI video creation without direct expenses.

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