New Image2Video. Stable Video Diffusion 1.1 Tutorial.

This tutorial explores the new Stable Video Diffusion 1.1 by Stability AI, an upgrade from the previous 1.0 model. The video demonstrates how to use the model to convert images into videos, showcasing the process through a workflow in Comfy UI and a fork of Automatic1111. The host compares the results of the new model with the old one using various images, highlighting the improvements in consistency and detail, especially in moving objects and scenes. The tutorial also provides technical details such as the model's default settings and frame rates. Despite some inconsistencies with certain images, like the stars in the rocket launch scene, the new model generally performs better. The video concludes with an invitation to join the host's Discord community for AI art and generative AI enthusiasts.

Takeaways

• 📈 Stable Video Diffusion 1.1 is an upgrade from the previous 1.0 model by Stability AI, offering improved image to video conversion.
• 📹 The model generates videos at a resolution of 1024x576 with 25 frames, using a fixed conditioning at 6 frames per second.
• 🔗 The tutorial provides instructions on how to run the model using both Comfy UI and a fork of Automatic1111.
• 💻 Users are advised not to change the default settings for motion bucket ID and frames per second to avoid breaking the stable diffusion.
• 📥 To use the model in Comfy UI, one needs to download and add the SVD xd11 save tensors model into the checkpoints.
• 🔄 For the Automatic1111 fork, the workflow is added to the Stable Fusion web UI under models, stable diffusion.
• 🆕 The new model demonstrates better consistency and detail, especially noticeable in moving objects like cars and tail lights.
• 🔴 In some cases, such as with a static hamburger image, the old model performed better with more consistent results.
• 🎨 The video also includes a comparison of how both models handle different types of images, including a floating market and a cherry blossom tree.
• 🚀 For complex scenes like a rocket launch, the new model generally maintains better consistency, although the stars in the sky are not well handled in the test.
• 🔧 Users are encouraged to use different seeds or re-generate if the output from Stable Video Diffusion 1.1 does not meet expectations.
• 🌟 The presenter also mentions a Discord community for AI art and generative AI enthusiasts, with weekly challenges and submissions.

Q & A

What is the main topic of the video tutorial?

The main topic of the video tutorial is the introduction and comparison of Stability AI's Stable Video Diffusion 1.1, an upgrade from their previous 1.0 model, which converts images into videos.

How can viewers support the creator of the tutorial?

Viewers can support the creator by checking out the Patreon links provided in the video description, which is the main source of income for creating these videos.

What is the resolution that the Stable Video Diffusion 1.1 model was trained to generate?

The Stable Video Diffusion 1.1 model was trained to generate videos at a resolution of 1024 by 576.

What is the frame rate at which the model performs fine shooting?

The model performs fine shooting at a fixed conditioning of 6 frames per second.

How can users obtain the Stable Video Diffusion 1.1 model?

Users can obtain the Stable Video Diffusion 1.1 model by visiting the provided link in the description and downloading the necessary files.

What is the difference between using Comfy UI and a fork of Automatic 1111 for running Stable Video Diffusion?

The main difference is where the model is loaded. In Comfy UI, it's loaded into the models checkpoints, whereas in a fork of Automatic 1111, it's loaded into the Stable Fusion web UI models stable diffusion.

What is the advantage of the new Stable Video Diffusion 1.1 model over the previous one, as demonstrated in the video?

The new Stable Video Diffusion 1.1 model demonstrates better consistency and quality in the generated videos, especially noticeable in the handling of moving objects like a car and its tail lights.

In which example does the old model perform better according to the video?

In the example with the hamburger, the old model performs better as it shows a more consistent rotation of the burger and maintains the details of the fries in the background.

What is the creator's suggestion for users when the model does not perform as expected?

The creator suggests using a different seed or generating a new output if the model does not perform as expected.

How does the video tutorial compare the new and old models of Stable Video Diffusion?

The video tutorial compares the new and old models by running several images through both models and showing side-by-side comparisons of the output videos.

What is the creator's final verdict on Stable Video Diffusion 1.1?

The creator concludes that Stable Video Diffusion 1.1 generally performs better than the previous model, except in the specific case of the hamburger example.

How can viewers participate in the weekly AI art challenge mentioned in the video?

Viewers can join the creator's Discord community, where they can participate in the weekly AI art challenge and share their creations.

Outlines

00:00

🎥 Introduction to Stable Video Diffusion 1.1

The video begins with an introduction to the latest update of the stable video diffusion model by Stability AI, version 1.1. The host explains that this model is a fine-tune of the previous 1.0 and demonstrates the process of inputting an image to generate video results. The host also promotes their Patreon for support, mentions extra content available there, and humorously notes the incorrect spelling of 'incorrectly' in the dictionary. The workflow for using the model is detailed, including the need to input an image through specific nodes in a k-sampler to produce the video output. A comparison between the new and old models is shown, highlighting improvements in consistency and detail, especially noticeable in moving objects like a car's tail lights.

05:01

🍔 Testing Stable Video Diffusion 1.1 with Various Images

The host proceeds to test the Stable Video Diffusion 1.1 model using different images, including a hamburger, a floating market, and a cherry blossom tree, to evaluate its performance. In each case, the new model is compared side by side with the old model. The results vary, with the new model showing better consistency in some cases, while the old model performs better in the case of the hamburger due to less unwanted rotation. The host also notes that the new model tends to have slower movements, which helps in maintaining consistency. The stars in a rocket launch image do not render well in either model, which is a slight disappointment as previous tests showed better results for the new model. The host invites viewers to join their Discord community for AI art and generative AI discussions and challenges.

10:04

📊 Conclusion on Stable Video Diffusion 1.1 Performance

In conclusion, the host summarizes the performance of Stable Video Diffusion 1.1, stating it is generally better than the previous model, except in the case of the hamburger image. They suggest that in most cases, version 1.1 should be used, and if the results are not as expected, one should try a different seed for a new generation. The host thanks the viewers for watching, encourages them to like and subscribe for more content, and ends the video on a positive note.

Keywords

Image to Video

Image to video refers to the process of converting a static image into a video format. In the context of the video, this technology is used to create dynamic visual content from a single image input. The video discusses advancements in this technology with the introduction of Stable Video Diffusion 1.1, which is an improvement over the previous model, demonstrating better consistency and quality in the output videos.

Stable Video Diffusion 1.1

Stable Video Diffusion 1.1 is an updated model developed by Stability AI that fine-tunes the previous version for generating videos from images. It is mentioned as an improvement over version 1.0, with the ability to produce more consistent and higher quality video results. The video tutorial compares the performance of this model with its predecessor.

Patreon

Patreon is a crowdfunding platform where creators can receive financial support from their audience, or patrons, for the content they produce. In the video, the creator encourages viewers to check out the Patreon links provided, which is their main source of income and helps them continue to create videos like the one being watched.

Comfy UI

Comfy UI refers to a user interface designed for comfort and ease of use. In the context of the video, it is mentioned as a platform where the Stable Video Diffusion model is utilized. The creator demonstrates how to implement the model within the Comfy UI to generate videos from images.

Resolution

Resolution in the context of digital media refers to the number of pixels in a video or image, which determines its clarity and detail. The video specifies that the Stable Video Diffusion model was trained to generate videos at a resolution of 1024 by 576 pixels, which is a standard for high-definition content.

Frames per Second (FPS)

Frames per second (FPS) is a measure of how many individual frames are displayed in one second of video. It affects the smoothness of the video's motion. The video mentions that the Stable Video Diffusion model operates with a fixed conditioning at 6 FPS, which is a standard for smooth video playback.

Motion Bucket ID

Motion Bucket ID is a parameter in the Stable Video Diffusion model that influences the generation of motion in the output video. The video specifies a Motion Bucket ID of 127, which is set by default and should not be altered unless the user is intentionally experimenting with different settings.

Stable Diffusion

Stable Diffusion is a term used to describe the process by which the Stable Video Diffusion model creates videos from images, maintaining a stable and coherent transition between frames. The video explores the consistency and quality of the generated videos, particularly how the new model handles motion and maintains the shape and details of objects within the scene.

Model Comparison

Model comparison involves evaluating the performance of different versions of a model, in this case, the Stable Video Diffusion 1.1 versus the previous version. The video script includes several comparisons where the new model is tested against the old one using various images to determine which performs better in terms of video quality and consistency.

Automatic 1111 Fork

An Automatic 1111 Fork refers to a modified or customized version of the original Automatic 1111 software. The video mentions using a fork of this software to run the Stable Video Diffusion model, which suggests that the fork may have been adapted to better suit the needs of the video generation process.

Discord

Discord is a communication platform that allows for text, voice, and video conversations. In the video, the creator invites viewers to join their Discord community where they can interact with over 7,000 like-minded individuals interested in AI art and generative AI. The community also hosts weekly AI art challenges, which adds a social and collaborative aspect to the video's content.

Cyberpunk

Cyberpunk is a genre of science fiction that features advanced technological and scientific achievements, juxtaposed with a degree of breakdown or radical change in the social order. The video mentions a weekly AI art challenge with a Cyberpunk theme, indicating that participants are encouraged to create art that fits within this genre, showcasing the creative applications of AI in generating content with specific thematic elements.

Highlights

Stability AI has released Stable Video Diffusion 1.1, an improved version of their previous 1.0 model.

The new model takes an input image and generates video results.

The tutorial compares the performance of the new model with the old one.

The model was trained to generate 25 frames at a resolution of 1024 by 576.

Fixed shooting was performed at 6 frames per second with a motion bucket ID of 127.

The workflow for using the model is available in the video description.

The video demonstrates how to get the model running using Comfy UI and an Automatic 1111 Fork.

The new model shows better consistency, especially noticeable in the example with a car and tail lights.

In the burger example, the old model performs better, showing a rotation and consistency.

The floating market image is challenging for both models, with the new model maintaining better consistency.

Stable Video Diffusion 1.1 has slower movements, which helps in maintaining consistency.

The cherry blossom tree example shows the new model keeping the scene more consistent than the old one.

In the rocket launch example, the new model handles the rocket and smoke better, but both struggle with the stars.

The video suggests using Stable Video Diffusion 1.1 in most cases, but also recommends using a different seed for better results.

The presenter has a Discord community with over 7,000 members interested in AI art and generative AI.

There is a weekly AI art challenge on the Discord, with this week's theme being 'Cyberpunk Adventures'.

The video concludes by noting that Stable Video Diffusion 1.1 generally performs better, except in specific cases like the burger example.

The presenter encourages viewers to like, subscribe, and join the Discord community for more AI art challenges and discussions.