Bring Images to LIFE with Stable Video Diffusion | A.I Video Tutorial

14 Dec 202308:15

TLDRThe video introduces Stability AI's new video model that animates images using text prompts. Two methods are discussed: a free, technical approach requiring software installation and a cloud-based solution, Think Diffusion, offering pre-installed models and high-end resources. The tutorial guides users through setting up Think Diffusion, customizing workflows, and creating animated videos. Tips on optimizing settings for motion and quality are provided, along with suggestions for enhancing video resolution using AI upscalers.


  • πŸš€ Stability AI has launched a video model that can animate images and create videos from text prompts.
  • πŸ’» There are two primary methods to run Stable Video Diffusion: a free, technical approach and a user-friendly cloud-based solution.
  • πŸ”§ The first method requires installing Compy UI and Compy Manager on your computer, along with the video diffusion model from Hugging Face.
  • 🌐 The cloud-based option, Think Diffusion, offers pre-installed models, extensions, and access to high-end computational resources.
  • πŸ”„ To update Compy UI and Manager, use the 'update all' feature and restart Compy UI after installation.
  • πŸ–ΌοΈ The video model works best with 16x9 images, and users can generate images using Midjourney or import their own.
  • πŸŽ₯ Key settings to adjust in the workflow include motion bucket ID, augmentation level, steps, and CFG for video quality.
  • πŸ“ˆ Experiment with different values for motion bucket ID and augmentation level to achieve desired video motion and camera movement effects.
  • 🎞️ The output videos are limited to 25 frames, but AI upscaling tools like Topaz Video AI can enhance and increase resolution.
  • πŸ“ When using the model with text prompts, it generates an image first, which is then animated by the video workflow.
  • πŸ’‘ Remember to stop the cloud-based machine when finished to avoid unnecessary charges.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is about how to use Stability AI's newly released video model to bring images to life and create videos from text prompts.

  • What are the two ways mentioned to run Stable Video Diffusion?

    -The two ways to run Stable Video Diffusion mentioned in the video are a free method that requires technical knowledge and computational resources, and a cloud-based solution called Think Diffusion which is easier to use.

  • What software components are needed for the free method of running Stable Video Diffusion?

    -For the free method, you need to install two main software components: Comfy UI and Comfy Manager.

  • How can one obtain the Stable Video Diffusion image to video model?

    -To obtain the Stable Video Diffusion image to video model, one needs to visit the Hugging Face page, find the SVD XD file, and save it to the correct path in the Comfy UI folder.

  • What are the benefits of using Think Diffusion?

    -Think Diffusion offers pre-installed models and extensions, access to high-end GPUs and memory resources, and allows running Stable Diffusion from almost any device with fewer clicks.

  • How does one launch a machine on Think Diffusion?

    -To launch a machine on Think Diffusion, you choose the 'confi' option, select the available machine that suits your needs, set a session limit if desired, and click 'launch'.

  • What is the purpose of the 'motion bucket ID' and 'augmentation level' settings in the workflow?

    -The 'motion bucket ID' controls the amount of motion in the video, with 150 being a good starting point. The 'augmentation level' affects how much the video resembles the original image, with higher levels resulting in less similarity and more motion.

  • What is the recommended setting for the 'steps' and 'CFG' in the workflow?

    -The recommended setting for the 'steps' is 25 for better overall quality, and for the 'CFG' is set to 3.

  • How can one enhance the quality of the video outputs?

    -One can use an AI upscaler like Topaz Video AI to enhance the video and increase its resolution. Doubling the video dimensions and increasing the frame rate to 25 can result in smoother playback.

  • How can the generated image from text prompts be consistent for video creation?

    -To keep using the same image for your videos, you can set the 'seed' in the workflow to a fixed value.

  • What should one do after finishing with Think Diffusion?

    -After finishing with Think Diffusion, it's important to stop the machine to avoid unnecessary charges.



πŸš€ Introduction to Stable Video Diffusion

This paragraph introduces the release of Stability AI's video model that enables users to animate images and create videos from text prompts. Two methods of running Stable Video Diffusion are discussed: a free, technical approach involving the installation of Confy UI and Confy Manager, and a cloud-based solution called Think Diffusion that requires fewer technical skills. The paragraph provides a link to a tutorial video for installation guidance and explains the process of downloading and installing the video diffusion model through Hugging Face. It also mentions the sponsorship of Think Diffusion and encourages viewers to watch another video to assess its value.


πŸŽ₯ Using Think Diffusion for Video Creation

This paragraph delves into the process of using Think Diffusion, a cloud-based solution, to create videos. It explains how to select the appropriate machine based on available resources, set session limits, and access the Comfy UI interface. The paragraph then describes how to replace the default workflow with a new one designed for image-to-video conversion, including the installation of custom nodes if necessary. It provides a detailed walkthrough of the settings and options available for animating an image, such as motion bucket ID and augmentation level, and concludes with instructions on how to export the final video in various formats.



πŸ’‘Stability AI

Stability AI refers to the company that has developed a video model enabling users to animate images and create videos from text prompts. This is the central focus of the video, showcasing the capabilities of this AI technology and how it can be utilized to bring static images to life.

πŸ’‘Video Diffusion

Video Diffusion is a process that involves using AI to generate videos from still images or text prompts. It is a key concept in the video, illustrating the advancement of AI in video creation and animation without the need for complex animation techniques.

πŸ’‘Computational Resources

Computational resources refer to the hardware and software capabilities required to run complex AI models, such as video diffusion. In the context of the video, it highlights the need for a certain level of technical knowledge and access to specific computer resources to utilize the video model effectively.

πŸ’‘Hugging Face

Hugging Face is a platform that provides AI models and tools for developers and researchers. In the video, it is the place where users can download the table video diffusion image to video model, which is essential for the video animation process.

πŸ’‘Cloud-Based Solution

A cloud-based solution refers to software or services that are hosted remotely and accessible over the internet. In the video, Think Diffusion is introduced as a cloud-based solution that simplifies the process of running stable video diffusion by providing pre-installed models and extensions, as well as high-end computational resources.


A workflow in the context of the video is a set of procedures or steps that are followed to accomplish a specific task, such as animating an image or creating a video from a text prompt. Workflows are essential for guiding users through the process of using the AI video model effectively.

πŸ’‘Motion Bucket ID

Motion Bucket ID is a parameter within the AI video model that controls the amount of motion in the generated video. It is a key setting that users can adjust to increase or decrease the level of movement in the animated content.

πŸ’‘Augmentation Level

Augmentation Level is a setting that affects how the AI model manipulates the original image to create the video. A higher augmentation level results in a video that is less similar to the original image, allowing for more creative and dynamic animations.

πŸ’‘AI Upscaler

An AI upscaler is a tool that uses artificial intelligence to enhance the quality, resolution, and other aspects of digital media, such as videos. In the video, it is suggested as a way to improve the quality of the AI-generated videos, which are initially limited to 25 frames.

πŸ’‘Text Prompts

Text prompts are inputs provided to AI models to guide the generation of specific content. In the context of the video, text prompts are used to create videos from scratch based on descriptive text, showcasing the versatility of AI in content creation.


Stability AI has released a video model that can bring images to life and create videos from text prompts.

There are two main ways to run stable video diffusion, one is free but requires technical knowledge and computational resources.

To use the free method, one must install Confy UI and Confy Manager on their computer.

A tutorial video is available for guidance on the installation process of the required software.

The Hugging Face page is where users can download the table video diffusion image to video model.

Think Diffusion is a cloud-based solution that offers an easier way to use stable video diffusion with fewer clicks.

Think Diffusion provides access to high-end GPUs and memory resources, allowing stable diffusion to run from almost any device.

The video tutorial demonstrates how to use Think Diffusion for creating an image to video workflow.

Different resources are available with Think Diffusion's machine options, allowing users to choose what works best for them.

The tutorial shows how to set a time limit for the session and launch a turbo machine for faster processing.

The file structure in Think Diffusion is similar to the local version, and users can replace the default workflow with a different one.

The tutorial provides a link to a modified workflow in JSON format for users to download and use.

The video demonstrates how to use the workflow to animate an image with the stable video diffusion model.

The tutorial explains how to adjust settings like motion bucket ID and augmentation level for different effects.

Users can experiment with different values for motion and camera movement, and use AI upscalers like Topaz Video AI to enhance video quality.

The video also covers how to create videos from text prompts using the stable video diffusion model.

The generated image may change each time, but users can set a seed for consistency in their videos.

The video concludes with a reminder to stop the machine in Think Diffusion to avoid unnecessary charges.