Civitai AI Video & Animation // Making Depth Maps for Animation // 3.28.24

In this engaging live stream, Tyler from Civitai AI Video & Animation dives into the world of depth map generation and animation using Comfy UI and Anime Diff. The session is designed to be accessible, allowing viewers to follow along and learn how to create their own depth map animations. Tyler demonstrates the process of generating black and white depth maps using a model by Phil, known as Machine Delusions, and then stylizing these maps using Anime Diff for endless creative possibilities. The stream is interactive, with prompts from the audience being used to create unique animations. Tyler also discusses the technical aspects, such as the importance of randomizing seeds for variations and the use of different motion models to achieve distinct animation effects. The session is not only informative but also inspiring, encouraging viewers to experiment with AI animation tools and share their creations on the Civitai platform.

Takeaways

• 🎉 Tyler, the host, is excited to introduce a new topic for the Civitai AI video and animation stream, focusing on generating depth map animations.
• 📁 The workflow for creating depth map animations is available for download, and it involves two separate workflows that should be used in sequence.
• 🖼️ The first workflow generates a black and white depth map, while the second workflow stylizes the depth map animation using Anime Diff.
• 🚀 A special AI model called 'depth map 64' created by Phil (Machine Delusions) is used to generate the depth maps from text prompts.
• 💡 Viewers are encouraged to submit prompts via chat for the creation of depth map animations, which will be compiled into a final animation.
• 🎥 The process is designed to be accessible and not too VRAM intensive, making it possible for users with limited hardware resources to participate.
• 🌟 The potential applications for these depth map animations are vast, including music visualizations, art pieces, and more.
• 🔄 The use of an IP adapter allows for the application of specific styles onto the depth maps, creating unique and varied outputs.
• ⚙️ The stream demonstrates the use of various settings and nodes within the workflow, such as the control net for smoothing animations and the color correction node for adjusting the depth map's contrast and saturation.
• 📉 The host discusses the importance of experimenting with different prompts and adjusting the workflow's settings to achieve desired results.
• ⏰ The stream concludes with a reminder about the upcoming guest creator stream with Sir Spence, who will be demonstrating advanced techniques combining Comfy UI with other tools.

Q & A

What is the main topic of the video and animation stream presented by Tyler?

The main topic of the stream is generating depth map animations using Comfy UI and Anime Diff, and stylizing them for creative projects.

Who is the creator of the depth map model used in the workflow?

The depth map model was created by Phil, also known as Machine Delusions.

What are the two workflows used in the process and what is their order of utilization?

The first workflow generates a black, white, and gray image known as the depth map. The second workflow takes that depth map and stylizes it using Anime Diff. They are used in this order.

What is the purpose of using the batch prompt scheduler in the workflow?

The batch prompt scheduler is used to create a prompt traveling depth map, allowing for the generation of depth maps for multiple prompts sequentially.

How does the motion of the depth map animation affect the final output?

The motion of the depth map animation can influence the final output's style and appearance. Different motion models, like the shatter motion model, can be used to achieve various effects.

What is the role of the IP adapter in the workflow?

The IP adapter is used to push a specific image into the depth map, allowing for the styling of the depth map with a specific image or texture.

Why is the resolution of the depth map set to 512 by 896 in the stream?

Tyler sets the resolution to 512 by 896 because he works in a vertical format, and this resolution is suitable for his needs and helps maintain a balance between quality and performance.

What is the significance of randomizing the seed when generating depth maps?

Randomizing the seed leads to different outcomes in the generated depth maps, as the seeds significantly affect the final result. This allows for a wider range of possibilities and creative exploration.

How does the control net, specifically the control GIF, contribute to the animation process?

The control GIF is used to smooth out the animations, making them more fluid and visually appealing in the final stylized output.

What is the recommended way to deal with VRAM limitations when running the workflows?

To deal with VRAM limitations, one can reduce the resolution of the animation, turn off the upscaler, or remove certain nodes that are more resource-intensive, such as the film vfi node for interpolation.

What is the potential application of the generated depth maps and stylized animations?

The generated depth maps and stylized animations can be used for various creative applications, such as music visualizations, video content, wallpapers, and other visual art projects.

Outlines

00:00

🎉 Introduction to Depth Map Animations

Tyler welcomes viewers to the video and animation stream, expressing excitement about the day's focus on generating depth map animations using Comfy UI and Anime Diff. He discusses the plan to create animations from depth maps and stylize them for endless creative possibilities. Tyler also mentions the need for downloading a specific workflow and a model called 'Laura,' created by Phil, a friend of the channel.

05:01

📁 Workflow Overview and User Friendliness

The video provides an overview of the two workflows that will be used in the session. Tyler emphasizes the simplicity and user-friendliness of the workflows, particularly for Daz who is known to encounter issues when opening complex workflows. The discussion also covers the importance of VRAM usage and the potential for prompts from viewers to influence the creation of depth map animations.

10:02

🎨 Customizing Depth Maps with Anime Diff

Tyler explains the process of using the first workflow to generate a depth map and the second workflow to stylize it using Anime Diff. He details the settings and nodes used in the process, including the use of a color correction node to ensure the depth map is free of color. The segment also includes examples of generated depth maps and the initiation of the process using a prompt from a viewer.

15:03

🚀 Generating Animations and Addressing Motion

The host attempts to generate an animation based on a viewer's prompt, making adjustments to the motion of the wizard character. He discusses the use of interpolation to smooth out animations and the potential for the animations to be used in various creative applications. Tyler also addresses the limitations of the motion model and the possibility of using different models to achieve the desired effect.

20:06

🧙‍♂️ Wizard Prompt and Stylization Process

Tyler uses a wizard prompt to demonstrate the animation and stylization process. He explains the use of the depth control net and the control GIF to smooth out animations. The segment also includes a discussion about the potential for using negative prompts and the successful running of the workflow without issues.

25:08

🖼️ Exploring Creative Depths with IP Adapter

The video explores the use of the IP adapter to apply different styles to the depth maps, allowing for creative reskinning of the animations. Tyler discusses the potential applications of the generated animations, such as music visualizations or loops. He also interacts with viewers by requesting prompts and images to further customize the animations.

30:30

🌟 Showcasing Results and Encouraging Exploration

Tyler showcases the results of the depth map generation and stylization, emphasizing the cool outcomes despite the abstract nature of the process. He encourages viewers to experiment with the workflows and share their creations. The segment also includes a discussion about the potential for using the generated content in various projects and the excitement for future possibilities.

35:37

🤔 Troubleshooting and Prompt Refinement

The host discusses the need for trial and error when generating depth maps, as they may not always make sense or adhere closely to the prompt. He suggests keeping the CFG low for faster results and using the second half of the workflow to refine the output. Tyler also addresses a viewer's question about rendering without affecting the image product.

40:39

🧬 Combining Images for Unique Animations

Tyler experiments with combining different images using the IP adapter to create unique animations. He discusses the potential for using various prompts to generate distinct styles and the use of different models to achieve different effects. The segment also includes a discussion about the importance of randomization in the seed for generating depth maps.

45:40

🎉 Final Prompts and Closing Remarks

In the final part of the stream, Tyler takes on more prompts from viewers, experimenting with creating creepy and abstract animations. He emphasizes the endless possibilities of the workflows and encourages viewers to explore and share their creations. Tyler also provides information about the next stream featuring a guest creator and expresses excitement about the upcoming demonstration.

50:42

📚 Workflow Assistance and Community Support

The video concludes with Tyler offering help for any questions regarding the workflow and directing viewers to the discussion section on the workflow page for community support. He thanks everyone for joining the stream and looks forward to future sessions, promising more exciting content and exploration of new techniques.

Keywords

💡Depth Maps

Depth maps are digital images that represent the distance of objects from the viewer in a visual scene. They are used in 3D computer graphics to simulate the effect of light and shadow, contributing to a more realistic rendering. In the video, depth maps are generated from text prompts and are a central theme, as they are used to create animations and stylized visuals.

💡Animation

Animation refers to the process of creating a sequence of images that simulate movement when played in order. It is a key element in the video, where the host discusses creating animations using depth maps and AI tools, showcasing how these animations can be stylized and manipulated.

💡AI Video and Animation Stream

This term refers to the live streaming session where the host, Tyler, shares his process and techniques for creating videos and animations using AI tools. It is the context within which the entire discussion and demonstration take place.

💡Comfy UI

Comfy UI is a user interface for interacting with AI models, specifically for tasks like image and video generation. In the video, it is the platform used to generate depth map animations and stylize them with different effects.

💡Animate Diff

Animate Diff is a tool or process mentioned in the script that is used to stylize animations. It is a part of the workflow for taking depth map animations and applying various visual styles to them, enhancing their appearance.

💡Workflow

A workflow in this context refers to a specific series of steps or processes that are followed to complete a task or project. The video discusses two different workflows that are used in sequence to generate and stylize depth map animations.

💡LCM (Latent Convolutional Mapper)

LCM is a term that refers to a type of AI model used for generating images from textual descriptions. In the video, an LCM model is used to create depth maps from text prompts, which are then used to create animations.

💡Prompt Travel

Prompt travel is a technique where a series of text prompts are used to guide the generation of images or animations in a sequence, creating a narrative or thematic progression. Tyler discusses creating a prompt travel animation using the best prompts from the chat.

💡VRAM (Video Random-Access Memory)

VRAM is the memory used by graphics processing units (GPUs) to store image data for rendering or manipulation. The script mentions considerations for VRAM usage when running the workflows, indicating the importance of managing resources when working with graphics-intensive tasks.

💡Interpolation

Interpolation is a mathematical technique that estimates values between known data points. In the context of the video, interpolation is used to smooth out animations by effectively doubling the frame rate, creating a more fluid motion.

💡IP Adapter

An IP (Image Processing) Adapter is a tool used to influence the style or content of an AI-generated image based on a specific input image. In the video, the host uses an IP Adapter to apply different styles onto the generated depth maps.

Highlights

Tyler introduces a new workflow for creating depth map animations using comfy UI and anime diff.

The stream focuses on generating depth maps and stylizing them with anime diff, offering increased accessibility for various users.

A new Laura model by Machine Delusions is used to create depth maps, offering a high potential for creative applications.

The depth maps are not always photorealistic but provide a unique and stylized aesthetic for animation.

The stream demonstrates how to use prompts to generate depth maps, allowing users to participate and contribute ideas.

The depth map animations can be stylized with endless possibilities, offering a new dimension for creative expression.

The use of an IP adapter image allows for the addition of specific visual elements into the depth map.

The stream showcases the use of different LCM models to achieve varied depth map results.

Tyler discusses the importance of randomizing the seed for depth map generation to achieve different outcomes.

The stream highlights the potential of using AI-generated depth maps for music visualizations and creative loops.

The workflow is designed to be fast and efficient, utilizing 1.5 LCM for quick generation.

Tyler provides a link to download the necessary workflow and Laura model for users to experiment with on their own.

The stream emphasizes the community aspect of sharing and refining AI-generated content.

The potential for combining depth maps with motion models, such as those trained on ant movements, is explored.

The stream concludes with a demonstration of how depth maps can be mashed together with various虫 images to create unique animations.

Tyler invites users to share their creations using the new workflow and to join future streams for more AI video and animation exploration.