Make AMAZING AI Animation with AnimateLCM! // Civitai Vid2Vid Tutorial

Civitai
19 Feb 202425:59

TLDRTyler from cai.com presents a detailed guide on utilizing the animate LCM video to video workflow for creating stylized UI animations. The workflow allows for style transfer onto existing videos using prompts or reference images and offers features like face swapping. It requires at least 10 GB of VRAM and involves various nodes for video source, resolution, control nets, IP image adapter, and upscaling. Tyler emphasizes the importance of using the right models and settings for optimal results and shares resources for further learning. The tutorial is aimed at those familiar with comfy UI and animate diff basics, with links provided for additional guidance.

Takeaways

  • 🎥 The video script provides a walkthrough for an animate LCM video to video workflow, designed for stylizing existing videos using AI.
  • 💻 The workflow requires at least 10 GB of VRAM, and users with less should proceed with caution and possibly seek workarounds.
  • 🌐 The tutorial assumes prior installation of Comfy UI and familiarity with basic concepts of animate diff, offering links for further learning.
  • 🎨 The process involves uploading a video source, adjusting resolution settings, and selecting a model and checkpoint for rendering.
  • 🔄 The script emphasizes the use of control nets like line art, soft edge, depth, and open pose for refining the output.
  • 🖼️ The IP (Image Prompt) adapter allows users to input reference images to guide the style of the animation.
  • 📸 Users can utilize the 'Prepare Image for Clip Vision' node to crop and focus on specific parts of the input images.
  • 🎬 Prompt traveling is introduced as a method to change the style or elements of the animation at specific frames.
  • 🔢 The script details the importance of configuring the right balance of steps, CFG, and sampler settings for the LCM workflow.
  • 🔄 The 'Highres Fix' or upscaler is used to improve the resolution of the output video, with specific settings provided for optimal results.
  • 👤 The Reactor Face Swapper is an optional tool for changing the subject's face in the animation, though it may require additional setup effort.
  • 📹 The final output is combined into a video, with the option to preview and iterate versions using the 'Preview Gallery'.

Q & A

  • What is the main purpose of the workflow described in the video?

    -The main purpose of the workflow is to allow users to perform a style transfer on an existing video using either text prompts or reference images from the IP adapter, with the help of Animate Diff and Comfy UI.

  • What are the minimum system requirements for this workflow?

    -The workflow requires at least 10 GB of VRAM. Users with less than that should use it at their own risk and might need to find workarounds.

  • What is the role of the 'video Source SL' group in the workflow?

    -The 'video Source SL' group is where users load their video, set the resolution, aspect ratio, and choose the Laura stacker for processing the video.

  • How can users select the model and checkpoint for rendering in the workflow?

    -Users select the model and checkpoint for rendering in the 'model SL animate diff loader' group, where they also choose the V and set the animate diff options.

  • What are control nets and how are they used in this workflow?

    -Control nets are additional models that help to guide the style and output of the animation. They are used in the 'control Nets' group, where users can enable or disable different control nets like line art, soft edge, depth, and open pose.

  • How does the IP (Image Prompt) adapter function in the workflow?

    -The IP adapter takes reference images provided by the user and uses them to influence the style and appearance of the animation. Users can upload images or select areas of the images to focus on using the 'prepare image for clip Vision' node.

  • What is the syntax for prompt traveling in the workflow?

    -The syntax for prompt traveling is to use quotation marks for the frame number, a semicolon, a space, and then quotation marks around the prompt text. Multiple prompts are separated by commas.

  • How does the 'highres fix' or upscaler work in the workflow?

    -The 'highres fix' script is used to upscale the low-resolution video output to a higher resolution. It processes the video through a series of upscaling techniques to achieve a smoother and more detailed final output.

  • What is the reactor face swapper used for in the workflow?

    -The reactor face swapper is used to replace the face of the subject in the video with an image of another face. This can be used to maintain the original subject's face or to add someone else's face to the animation.

  • How can users share their creations made with this workflow?

    -Users are encouraged to share their creations on social media and tag 'hello Civi' so the community can view and share their videos.

  • Where can users find the Animate LCM vidto vid workflow for download?

    -The Animate LCM vidto vid workflow can be downloaded from the speaker's profile on cai.com, with the link provided in the video description.

Outlines

00:00

🎬 Introduction to Animate LCM Video to Video Workflow

This paragraph introduces the video tutorial by Tyler from cai.com, focusing on the Animate LCM (Latent Conditioned Mesh) video to video workflow. The workflow allows users to perform style transfer on existing videos using either text prompts or reference images from the IP adapter. It is mentioned that the process requires at least 10GB of VRAM and provides a warning for users with less. Tyler also gives a shoutout to community members Sir Spence and PES Flows for their contributions and provides Instagram handles for further exploration.

05:01

🛠️ Understanding the Video Upload Node and Settings

In this section, Tyler explains the video upload node, emphasizing the importance of the frame load cap, skip first frames, and select every settings. Frame load cap determines the number of frames to be rendered, skip first frames allows skipping a certain number of frames at the start, and select every dictates the rendering frequency. He also discusses the aspect ratio and resolution settings, recommending a vertical format for social media optimization. The paragraph concludes with an introduction to the Laura stacker, including model strength and clip strength settings.

10:02

🚀 Navigating the Model and Control Net Settings

This paragraph delves into the model loader settings for the animate diff motion model and the VRAM usage. Tyler highlights the need for the animate LCM motion model and provides a link for downloading it. He also discusses the use of a photon LCM specific model trained by a community member, Machine Delusions. The paragraph further explains the control net settings, including line art, soft edge, depth, and open pose options, and the necessity of having the control net models installed for their use.

15:05

🖼️ Utilizing the IP Adapter for Style Transfer

Tyler introduces the IP (Image Prompt) adapter, which uses reference images to guide the animation style. Users can upload images or select them from the browser, and the system will attempt to incorporate the style into the animation. The paragraph explains the crop position selector and weight settings for the IP adapter, allowing users to focus on specific parts of the image for style transfer. It also mentions the need for the IP adapter plus stable diffusion 1.5 bin file and the sd15 pytorch model bin for the process to work.

20:06

✍️ Crafting Prompts and Negative Prompts for Video Stylization

This section covers the use of positive and negative prompts to guide the video's content and style. Tyler explains the syntax for prompt traveling, where specific prompts can be applied at different frames of the video. The paragraph details the use of the batch prompt scheduler, where the pretext and batch prompt boxes dictate the order of descriptors. It also touches on the use of embeddings and textual inversions for negative prompts to exclude unwanted elements from the render.

25:07

🎨 Fine-Tuning the Sampler and Upscaling for High-Quality Output

Tyler discusses the K sampler settings, emphasizing the need for low steps and CFG values in the LCM workflow. The paragraph explains the importance of the sampler being set to LCM and the scheduler set to sgm uniform for optimal results. The highres fix script, or upscaler, is introduced, with specific settings provided for upscaling the video to a higher resolution. The paragraph also mentions the reactor face swapper, but advises that it may be problematic to install and suggests skipping it if issues arise.

📹 Reviewing and Iterating the Workflow with the Preview Gallery

The final paragraph focuses on the output stage of the workflow, where Tyler explains the video combine node and its settings. He demonstrates the successful application of the workflow using a dancer girl video and reference images, achieving a looped video with the desired style. The paragraph concludes with a mention of the preview gallery, where users can compare different versions of their videos during the testing and iterating process. Tyler encourages viewers to share their creations and provides a link to his cai.com profile for downloading the workflow.

Mindmap

Keywords

💡animate LCM

The term 'animate LCM' refers to a specific workflow within the video editing and animation field that utilizes the Latent Diffusion (LCM) model for generating animated content. This technique is showcased in the video as a way to take existing footage and apply style transfers to it, creating a new, stylized video output. The video explains that this workflow is different from traditional animate Diffusion models and requires specific settings and models to function correctly, such as the 'sd15 t2v beta' model mentioned in the script.

💡style transfer

Style transfer is a process in computer vision and image editing where the style of one image is applied to another, transforming the content to match the artistic characteristics of the reference image. In the context of the video, style transfer is used to take an existing video and apply a new visual aesthetic to it, such as making it look like a painting or a specific artistic style. This is done through the use of AI models and control nets, which analyze and replicate the style onto the video frames.

💡control nets

Control nets are a set of AI models used in the animation and video editing process to guide and influence the output based on specific characteristics or features. They act as a reference for the AI to understand what aspects of the input it should focus on and replicate. In the video, control nets like 'line art', 'soft edge', 'depth', and 'open pose' are mentioned as tools that can be toggled on or off to achieve different visual effects in the style transfer process.

💡IP adapter

The IP (Image Prompt) adapter is a tool used in AI-based animation workflows to feed reference images into the system, which the AI then uses to build and inform the animation. It allows users to guide the AI's output by providing specific visual examples of the desired style or subject matter. The IP adapter helps the AI understand the elements within the images and apply those elements to the animation, creating a more accurate and stylized representation.

💡highres fix

Highres fix, also known as an upscaler, is a technique or tool used to increase the resolution of an image or video while maintaining or improving its quality. In the context of the video, the highres fix is part of the workflow to upscale the low-resolution output from the animation process to a higher resolution, resulting in a more detailed and crisp final video. This is particularly important for achieving a high-quality output suitable for various display platforms.

💡face swapper

Face swapper is a tool or technique used in video editing to replace or modify the facial features of a subject in a video with another image or video. This can be used for various purposes, such as changing the appearance of a character or integrating a different person's face into the animation. In the video, the face swapper is mentioned as an optional feature within the workflow, allowing users to change the face of their subject if desired.

💡prompt traveling

Prompt traveling is a technique used in AI-based content creation where specific prompts or instructions are applied to certain frames or sections of a video. This allows for dynamic changes in the content, such as altering the style, introducing new elements, or changing the narrative at specific points in the video. In the context of the video, prompt traveling is used to make targeted adjustments to the animation, such as changing the prop to a cat at a specific frame.

💡VRAM

Video RAM (VRAM) is the dedicated memory used by graphics processing units (GPUs) to store image data that the GPU uses to render graphics. In the context of the video, VRAM is crucial for handling the computationally intensive tasks of AI-based animation and style transfer. The workflow requires a minimum of 10 GB of VRAM, indicating the high computational demands of the processes involved.

💡Comfy UI

Comfy UI is a user interface for certain AI-based animation and video editing tools that provides a streamlined and user-friendly experience for creating content. In the video, Comfy UI is mentioned as a prerequisite for using the animate LCM workflow, suggesting that it serves as a platform or environment where users can implement the workflow and access the necessary tools and settings.

💡社区成员

在视频中提到的'社区成员'是指那些在特定领域或技术社区中积极贡献和分享知识、资源的个人。他们通常是该领域的专家或爱好者，通过分享经验、教程、模型等资源，帮助他人学习和进步。在本视频中，提到了几位社区成员，如Sir Spence和PES Flows，他们通过提供反馈和帮助改进工作流程，对视频内容的制作有所贡献。

💡AI模型

AI模型（人工智能模型）是指用于模拟人类智能行为的算法和数学模型的集合。在视频制作和动画领域，AI模型可以用于生成、编辑和转换图像或视频内容。在本视频中，AI模型被用于执行风格转换、面部交换等任务，以创造出新的视频内容。

Highlights

Introducing the animate LCM videot to tide workflow for animate diff and comfy UI.

The workflow enables style transfer to existing videos using either prompting or reference images.

High res fix and face swapper features are included for upscaling and changing subject's face.

At least 10 GB of VRAM is required for this workflow.

The tutorial assumes prior installation of comfy UI and basic knowledge of animate diff.

The workflow is designed to be simple and straightforward, with color-coded and numbered groups.

Group one involves video source, resolution, aspect ratio, and Laura settings.

Group two focuses on the animate diff motion model loader and V settings.

Control Nets, including line art, soft edge, depth, and open pose, are detailed in group three.

The IP image adapter in group four uses reference images to influence the animation style.

Prompt green box allows for positive prompting and syntax explanation.

The K sampler and highres fix (upcaler) are discussed in group six.

Group seven covers the reactor face swapper for changing subject's face in the video.

The video combine node in group eight provides the final output.

A preview gallery is used for comparing different versions of the video.

The entire workflow will be available for download on the presenter's cai.com profile.

The tutorial is a comprehensive guide for creating stylized videos for social media or other purposes.