NEW Stable Video Diffusion XT 1.1: Image2Video

All Your Tech AI
7 Feb 202407:53

TLDRStability AI has introduced Stable Video Diffusion 1.1, an image-to-video diffusion model available on Hugging Face. The model generates 25 frames of video at 124x576 resolution, aiming for 6 frames per second. Users need to download a 5GB safe tensor file and use Comfy UI for the workflow. The video demonstrates the model's ability to animate various images, showing smooth motion and some minor artifacts, highlighting its potential for creative applications despite limitations.

Takeaways

  • 🚀 Stability AI, creators of Stable Diffusion XL, have released Stable Video Diffusion XT 1.1 on Hugging Face.
  • 🔒 Access to the model is gated and requires users to log in and provide information on the intended use of the model.
  • 📈 The model generates video from a still image, producing 25 frames at a resolution of 124x576 with 6 frames per second.
  • 🎥 The default settings for the model include a motion bucket ID of 127 to enhance output consistency.
  • 📦 Users need to download a nearly 5GB Safe Tensor file named 'SVD XT 1.1' to use the model.
  • 🖥️ Comfy UI workflow is recommended for using the model, with an installation video provided for newcomers.
  • 🔄 After loading the JSON file in Comfy UI, users should check for and install any missing custom nodes.
  • 🌟 The 'Image to Conditioning' section requires parameters matching the Hugging Face and Stability AI recommendations.
  • 🖼️ Users can load an image into the 'Load Image' box, which will be animated by the model.
  • ⏱️ Rendering times may vary depending on the user's hardware; the video takes about 2 minutes on an RTX 3090 GPU.
  • 📸 The resulting videos show smooth motion and interesting effects, though some artifacts and inconsistencies may occur.

Q & A

  • What is the Stable Video Diffusion 1.1 model developed by Stability AI?

    -The Stable Video Diffusion 1.1 is an image-to-video diffusion model developed by Stability AI, the creators of Stable Diffusion XL. This model takes a still image as a conditioning frame and generates a video from it.

  • Where can the Stable Video Diffusion 1.1 model be found?

    -The Stable Video Diffusion 1.1 model can be found on Hugging Face, where users need to log in and agree to a couple of questions about the intended use of the model.

  • What are the default settings for the Stable Video Diffusion 1.1 model?

    -The default settings for the model include a resolution of 124 by 576, generating 25 frames of video, with a motion bucket ID of 127, resulting in 6 frames per second.

  • What is the file size of the SVD XT 1.1 safe tensor file?

    -The SVD XT 1.1 safe tensor file is almost 5 GB in size.

  • How does one use the Comfy UI workflow with Stable Video Diffusion 1.1?

    -To use the Comfy UI workflow, users need to install Comfy UI, load the JSON file specific to SVD, and adjust the parameters according to the recommendations from Hugging Face and Stability AI. Users then load their image and click the 'Q prompt' button to generate the video.

  • How long does it take to generate a 25-frame video at default settings using an RTX 3090 GPU?

    -It takes approximately 2 minutes to generate a 25-frame video at default settings with an RTX 3090 GPU.

  • What kind of results can be expected from the Stable Video Diffusion 1.1 model?

    -The results can range from smooth motion animations that almost appear Ray-traced, to artifacts and inconsistencies, depending on the complexity of the input image. Some images may not animate as expected, with issues like wobbly features or lack of proper motion for certain objects.

  • How can the output videos from the Stable Video Diffusion 1.1 model be improved?

    -Improvements can be made by adjusting the parameters, such as the motion bucket ID and frames per second, or by using different input images that may produce more consistent animations. Additionally, users can experiment with cropping images or using different images entirely to achieve desired results.

  • What is the significance of the Stable Video Diffusion 1.1 model being open source?

    -The open-source nature of the Stable Video Diffusion 1.1 model allows for widespread testing, experimentation, and improvement by the community. It enables users to contribute to the development of the model and find innovative uses for the technology.

  • How does the Stable Video Diffusion 1.1 model compare to other motion generation technologies like DALL-E's motion brush?

    -While the Stable Video Diffusion 1.1 model is a significant advancement, it is not on par with more advanced technologies like DALL-E's motion brush. However, it offers a unique and accessible way for users to experiment with image-to-video conversion.

Outlines

00:00

🎥 Introduction to Stable Video Diffusion 1.1

This paragraph introduces the Stable Video Diffusion 1.1, an image-to-video model developed by Stability AI, the creators of Stable Diffusion XL. The model is available on Hugging Face and requires users to log in and agree to certain terms. It generates video from a still image, with the ability to produce 25 frames at a resolution of 1280x576, at 6 frames per second using a motion bucket ID of 127. The default settings are provided, and users are guided to download a specific file, SVD XT 1.1 safe tensor file, which is nearly 5 GB in size. The paragraph also explains the process of using Comfy UI for model implementation, including the installation of custom nodes if necessary, and provides a step-by-step guide on how to load the model and generate video from an image. The video showcases the smooth motion and detail of the generated video, highlighting the model's capabilities and some minor issues with object animation.

05:00

🚀 Testing Various Images with Stable Video Diffusion 1.1

This paragraph details the testing of the Stable Video Diffusion 1.1 model with different images. The creator loads various images, including a robot, a depiction of sadness, a light bulb in a forest, and a futuristic car, to observe how the model animates them. The results range from impressive, such as the smooth motion of the robot and the panning effect on the background, to less successful, like the awkward movement of the wheels and the distortion of the light bulb's leaves. The creator also notes the model's inability to animate certain details accurately, such as the fingers typing on a keyboard or the consistency in rendering objects. The paragraph concludes with a call to action for viewers to share their creations and an acknowledgment of the model's open-source availability, despite its limitations compared to other technologies.

Mindmap

Keywords

💡Stable Video Diffusion

Stable Video Diffusion is a term referring to an AI model developed by Stability AI, which is capable of generating videos from single still images. In the context of the video, it is the main subject being discussed and demonstrated. The model takes a static image and creates a dynamic video sequence, showcasing the advancement in AI's capability to understand and manipulate visual content.

💡Image2Video

Image2Video is a process or technology that converts static images into video sequences. In the video, this term is used to describe the core functionality of the Stable Video Diffusion 1.1 model. It signifies the transformation of a single frame into a series of frames that create the illusion of motion, which is a significant advancement in the field of AI and machine learning.

💡Hugging Face

Hugging Face is a platform that provides a wide range of AI models, including the Stable Video Diffusion 1.1 discussed in the video. It is a marketplace where developers and researchers can share, discover, and utilize various AI models. In the context of the video, Hugging Face is the place where the Stable Video Diffusion model is released and made accessible to users.

💡Comfy UI

Comfy UI refers to a user interface that is designed to be intuitive and easy to use, providing a comfortable experience for users. In the video, it is the interface through which the Stable Video Diffusion model is operated. It is mentioned as a necessary tool for running the model and generating videos from images.

💡Safe Tensor File

A Safe Tensor File is a type of file used in the context of AI models like the Stable Video Diffusion, which contains the necessary data and parameters for the model to function. It is referred to as 'safe' to indicate that it is secure and reliable for use in the model. In the video, downloading this file is a crucial step in using the Stable Video Diffusion model.

💡Motion Bucket ID

Motion Bucket ID is a parameter used within the Stable Video Diffusion model to control the consistency and quality of the generated motion in the output video. It is a unique identifier that helps the model to maintain coherence in the animation. The video mentions a default Motion Bucket ID of 127, which is used to generate 6 frames per second for the 25-frame video.

💡Frames Per Second (FPS)

Frames Per Second (FPS) is a measurement used in video to indicate the number of individual images (frames) displayed per second. A higher FPS generally results in smoother motion in videos. In the context of the video, the Stable Video Diffusion model is set to generate videos at 6 FPS, which is achieved using a Motion Bucket ID of 127.

💡Upscaled

Upscaling in the context of video refers to the process of increasing the resolution of a video, often to improve its quality or to match a specific display requirement. In the video, the resulting video from the Stable Video Diffusion model is upsampled to 24 frames per second, which means the original 25 frames generated at 6 FPS are enhanced to play more smoothly.

💡Artifacting

Artifacting is a term used to describe unintended visual effects or distortions that occur in digital images or videos, often due to limitations in the rendering process. In the video, the term is used to point out areas where the Stable Video Diffusion model does not perfectly render certain elements, such as the spokes of the wheels on the robot image.

💡Parallax Effect

The Parallax Effect is a visual phenomenon where the position or motion of an object appears to differ when viewed from different angles or perspectives. In the context of the video, it refers to the depth or 3D effect created when the background of the generated video appears to move at a different speed than the foreground, enhancing the sense of depth and immersion.

Highlights

Stability AI, the creators of Stable Diffusion XL, have released Stable Video Diffusion 1.1 on Hugging Face.

Stable Video Diffusion 1.1 is an image-to-video diffusion model that generates video from a still image.

The model generates 25 frames of video at a resolution of 124x576, with 6 frames per second using a motion bucket ID of 127.

To use the model, one must download the nearly 5GB SVD XT 1.1 safe tensor file.

A Comfy UI workflow is used for this model, which requires installation and loading of a JSON file.

Parameters such as width, height, total video frames, motion bucket ID, and frames per second should match the defaults suggested by Hugging Face and Stability AI.

The image to be animated is loaded into the 'load image' box in the SVD image to conditioning section.

The generated video shows smooth motion and detailed animation, with some minor inconsistencies in object movement.

The model was tested with various images, including a robot, a depiction of sadness, a light bulb in a forest, and a futuristic car.

The animation of the robot resulted in a smooth, almost ray-traced motion with minor issues in spinning the wheels.

The animation of the sadness depiction produced bizarre, tree trunk-like tears crawling down the face.

The light bulb in the forest image resulted in a shaking leaf effect, with the light bulb possibly being interpreted as a flower.

The futuristic car image led to panning shots rather than motion within the car, with some abnormalities in the eyes.

An interior shot with a fireplace showed animated flames and wobbly furniture, adding an unexpected twist to the scene.

Stability AI's release of these models in an open-source manner allows for community testing and innovation.

While not on par with professional motion brush technologies, Stable Video Diffusion 1.1 offers a cool and accessible tool for experimentation.

Creators are encouraged to share their results and experiences in the comments to help refine the model's capabilities.