Ai Animation in Stable Diffusion

In this video, Sebastian Tus introduces viewers to the exciting world of AI animation using Stable Diffusion. He demonstrates how to create animations with personal footage by applying LCM lures and utilizing the Venture Resolve tool. Sebastian guides through the process of setting up the prompt, adjusting settings like sampling steps and resolution, and emphasizes the importance of occlusion to avoid misinterpretation by the AI. He showcases the generation of a realistic image and an animated look, mentioning the need for specific models and techniques to achieve the desired effects. The video also covers dealing with flickering in animations and suggests using Blender for more consistent results. Sebastian concludes by encouraging viewers to explore the potential of AI animation for live-action projects and invites feedback in the comments.

Takeaways

• 🎬 Sebastian Tus introduces a new method for creating animations using LCM lures with Stable Diffusion.
• 🚀 The technique has been eagerly awaited for a year and promises to enhance the capabilities of automatic 1111.
• 📸 Sebastian demonstrates the process using a picture made with Blender's human generator.
• ⚙️ The settings for the Stable Diffusion process include using the LCM model, adjusting sampling steps, and focusing on specific image portions.
• 🧩 To avoid occlusion issues, it's crucial to include all relevant parts of the image in the prompt.
• 🖼️ The resolution of the image is set to 1920x1401 to accommodate the larger size needed for the animation.
• 🔍 Control net settings are crucial, with options like Pixel Perfect and temporal net adjustments being made for better results.
• ⏱️ Large image generation takes longer, but the process is significantly faster for smaller images.
• 🎭 Sebastian shows how to create an animated look using the eal dark Gold Max model and additional techniques to enhance colors.
• 💻 For better quality, it's suggested to render at a higher resolution and then upscale, rather than starting with smaller images.
• 🧹 Flicker issues can be addressed in DaVinci Resolve, but this feature may not be available in the free version.
• 🔄 A fusion clip is created to combine different elements of the animation for a more consistent and cinematic look.
• 📚 Sebastian emphasizes the importance of working in layers and using Stable Diffusion to generate the necessary layers for the final image.

Q & A

What is the main topic of Sebastian's video?

The main topic of Sebastian's video is about using LCM lures to create animations with personal footage in Stable Diffusion.

What software does Sebastian use to create the initial image?

Sebastian uses Blender, specifically the human generator, to create the initial image.

What is the LCM that Sebastian mentions?

LCM, or Latent Concept Modifiers, is a tool that Sebastian installed to enhance the Stable Diffusion process. It does not come stock with Automatic1111.

What is the significance of reducing the sampling steps to eight?

Reducing the sampling steps to eight allows for faster image generation, which is beneficial when working with the type of image Sebastian has.

Why does Sebastian change the resolution of the image?

Sebastian changes the resolution to 1920 by 1401 to focus on a specific portion of the image and to address occlusion issues in Stable Diffusion.

What is the role of the control net in the process?

The control net is crucial for enabling pixel-perfect results and for applying temporal effects in the generation process.

What is the eal dark Gold Max model mentioned in the second example?

The eal dark Gold Max model is a model used for creating animated looks in the video, but it is no longer available on CID AI. A link to find it is provided in the video description.

Why does Sebastian recommend using a larger image resolution for animations?

Using a larger image resolution, such as 1920 x 1080, provides better quality results, especially when working with 3D applications like Blender.

How does Sebastian address flickering in the white suit?

Sebastian suggests that flickering in the white suit might be due to the shiny texture and not having trained a model with the character yet. He also mentions using DaVinci Resolve to deflicker the animations.

What is the advantage of rendering animations without the helmet in Blender?

Rendering animations without the helmet in Blender allows for a more consistent face appearance, as the face is less likely to be glitched or destroyed during the animation process.

How does Sebastian use fusion clips in post-processing?

Sebastian uses fusion clips to combine different elements of the animation, such as the helmet and the face, to create a seamless and cinematic look.

What does Sebastian suggest for viewers who are interested in exploring Stable Diffusion further?

Sebastian encourages viewers to subscribe to his channel for more in-depth exploration and tutorials on using Stable Diffusion for various applications.

Outlines

00:00

🎨 Introduction to LCM Lures for Animation

Sebastian introduces the audience to his tutorial on using LCM (Learned Conditional Model) lures to create animations with personal footage. He mentions the anticipation for a year for this animation technique and teases an upcoming demonstration on enhancing stable diffusion capabilities with Venture Resolve. The process involves adding a prompt with a woman's name and an already applied LCM Laura. Sebastian discusses using Blender's human generator to create an image, adjusting settings like sampling steps for faster generation, and addressing occlusion issues in stable diffusion. He also covers changing resolution and CFG scale, and using control nets for pixel-perfect results. The video concludes with a real-time generation example and a brief mention of batch processing.

05:02

🚀 Creating Animated Effects with Stable Diffusion

The second paragraph focuses on generating an animated look for a character, using a specific model no longer available on CID AI but accessible through a provided link. Sebastian emphasizes the use of moist mix vae for enhancing colors and clip skip for the process. He details the importance of the prompt and additional statements to achieve a cartoony, flat look. Settings adjustments are made for LCM sampling steps, resolution, and denoising. The tutorial then moves on to address the flickering issue in the white suit, suggesting rendering without the helmet for more consistency. Sebastian also discusses creating a fusion clip in Blender to stabilize the character's face and helmet, and the potential of using stable diffusion for layering in visual effects. He concludes by inviting feedback and expressing excitement about exploring live-action applications of the technique in future videos.

Keywords

LCM lures

LCM lures refer to a specific tool or method used in the context of the video to enhance animations. They are integral to the process of creating animations with personal footage as described by Sebastian, the speaker. The term is used to denote a technique that allows for the generation of animations more efficiently and effectively.

Stable Diffusion

Stable Diffusion is a technology or software mentioned in the video that is used for creating animations. It is highlighted as having undergone advancements that make it possible to create animations without a long waiting period. The video is focused on demonstrating how to use Stable Diffusion to animate footage.

Venture Resolve

Venture Resolve is a tool or software application that is used in the process of refining animations created with Stable Diffusion. It is mentioned as a way to level up the quality of animations, suggesting that it offers advanced features for post-processing or enhancing the final output.

Prompt

In the context of the video, a 'prompt' is an input or a set of instructions given to the Stable Diffusion software to guide the creation of the animation. It is a critical part of the process as it helps define the characteristics and elements that the final animation should include, such as the name of a woman or specific attributes.

Oil Array

The Oil Array is one of the settings or parameters within the Stable Diffusion software that can be adjusted to affect the output of the animations. It is mentioned as a choice that the user can make during the animation creation process, potentially influencing the style or quality of the generated images.

Sampling Steps

Sampling Steps refer to a process or setting within the Stable Diffusion software that determines the number of iterations or steps taken to generate an animation. Reducing the sampling steps, as mentioned in the video, can speed up the generation process but may affect the detail and quality of the final output.

Resolution

Resolution in the video pertains to the dimensions of the animation being created. The speaker adjusts the resolution to match the specific requirements of the animation, which can impact the level of detail and the time it takes to generate the image. It is a crucial aspect when dealing with high-quality or large-scale animations.

Control Net

A Control Net is a feature within the Stable Diffusion software that allows for more precise control over the generation of the animation. It is used to fine-tune the process, ensuring that certain aspects of the animation, such as the character's hands, are generated correctly and not misinterpreted by the software.

Pixel Perfect

Pixel Perfect is a term used to describe the quality of the generated images, indicating that they are of high resolution and clarity. In the context of the video, enabling Pixel Perfect in the Control Net settings is a way to ensure that the animations are sharp and detailed.

Temporal Net

Temporal Net is a feature or setting within the Stable Diffusion software that is used to create animations with a sense of motion or change over time. It is mentioned as a part of the process for generating animated sequences, suggesting that it helps to add a dynamic element to the still images.

Fusion Clip

A Fusion Clip is a technique or tool used in post-processing the animations created with Stable Diffusion. It involves combining different elements or layers from the animation to create a final, seamless output. In the video, the speaker uses Fusion to address issues like flickering and to achieve a more polished and consistent result.

Highlights

Sebastian Tus introduces a new method for creating animations using LCM lures in Stable Diffusion.

The process involves using a prompt with a woman's name and applying LCM Laura to it.

A picture made with Blender's human generator is used as a starting point.

The LCM (Local Configuration Module) is not included by default in Automatic 1111 and needs to be installed.

Sampling steps are reduced to eight for faster generation times.

Occlusion is a significant challenge in Stable Diffusion, which can misinterpret image elements.

The image resolution is adjusted to 1920 by 1401 to focus on the desired image portion.

CFG scale and D noising strength are fine-tuned for image quality.

Control net settings are crucial for achieving pixel-perfect results.

A real-time generation example is shown, with a large image taking longer to process.

The generated image quality is praised for its skin and hair details.

An animated look is created using the eal dark Gold Max model and moist mix vae for enhanced colors.

The process includes using CLIP skip and adjusting LCM and sampling steps for animation.

Different seeds are used to ensure unique results in each generation.

The generated animation is faster due to less detail, despite the high resolution.

The character's face is manually repainted in some frames to fix glitches.

Blender is used to render animations without a helmet for more consistent results.

Fusion is employed to combine different renders and reduce flickering.

The final image is created using layers, with Stable Diffusion providing necessary layers.

The method is still in early stages, offering much to explore in future applications.

Live-action looking stuff is where Sebastian sees the most potential for this technique.