2D Image Rotation - NEW stable-zero123 Model from Stability AI

Olivio Sarikas
20 Dec 202305:56

TLDRIn this tutorial, the presenter introduces a method to rotate 2D images using Stability AI's new model. The process involves downloading the model from Hugging Face, utilizing the community-driven platform Comi, and following a workflow created by Mato for incremental rotation. The video demonstrates two methods: creating a single rotated image and generating a video from multiple images. The presenter also recommends using remove.bg for background removal and provides tips on model settings, sampling methods, and video combining. The result is a visually engaging demonstration of 3D rotation effects on 2D images.

Takeaways

  • 🚀 Stability AI has released a new model for 3D rotation of 2D images.
  • 🔗 Download the model 'stable-0123' from Hugging Face.
  • 📚 Use Comi, a community-driven platform, to utilize the new technology.
  • 👥 Shout out to Mato for contributing a note that enables incremental rotation.
  • 📸 Load the workflow for 3D rotation and install missing notes in Comi Manager.
  • 🖼️ Two methods are presented: creating a single rotated image or a video from multiple images.
  • 🎨 Background removal for images can be done using the website 'remove.bg'.
  • 🔄 Use the Mato's note to create incremental images with varying rotations.
  • 📈 Set parameters like batch size, resolution, base elevation, and asimuth for the rotation.
  • 🎥 Combine images into a video using video combine for a dynamic 3D effect.
  • 🔄 Be aware of potential shape mutations when rotating complex images.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is how to perform 3D rotation of 2D images using a new model released by Stability AI.

  • Where can one download the Stability AI model mentioned in the video?

    -The Stability AI model, named stable-0123, can be downloaded from Hugging Face.

  • What is the purpose of the Comi platform in this process?

    -Comi is used to start using the new technologies, as it allows users to create and use notes created by the community, including the ones needed for the 3D rotation process.

  • Who helped the creator with the technical details of the 3D rotation process?

    -Mato helped the creator with the technical details of the 3D rotation process.

  • How can one remove the background of an image for this project?

    -The creator suggests using the website remove.bg to remove the background of an image.

  • What is the recommended resolution for the images used in the 3D rotation process?

    -The recommended resolution is 256x256 pixels, as that is what the model is trained on.

  • What is the purpose of the 'case sampler' in the 3D rotation process?

    -The case sampler is used to render the images with different rotations, and the creator found that 'uler' works well for this purpose due to its fast rendering speed.

  • How can the output of the 3D rotation process be used?

    -The output can be used to create a single image with a rotated view or combined into a video using video combine.

  • What is the 'pingpong' option in the video, and what effect does it have?

    -The 'pingpong' option, when set to true, creates a back-and-forth rotation effect in the final GIF file.

  • How can the viewer access the workflow and notes created by Mato?

    -The viewer can access Mato's workflow and notes by visiting the creator's profile on OpenArt AI and downloading the workflow from there.

  • What is the significance of the VAE (Variational Autoencoder) in the process?

    -The VAE is used to decode the output of the model, which is essential for generating the final rotated images or video frames.

Outlines

00:00

🌐 Introducing 2D Image Rotation with AI

The video introduces a new model from Stability AI that enables the rotation of 2D images. The host thanks Mato for technical assistance and guides viewers through the process of downloading the model from Hugging Face and using it on comi, a community-driven platform. The video demonstrates two methods: creating a single rotated image and generating a video from multiple rotated images. The process involves background removal, using the model's output, and adjusting rotation parameters. The video also suggests using remove.bg for background removal and highlights the importance of the Clip Vision output for the workflow.

05:00

📸 Customizing Rotation and Viewing Options

This paragraph continues the tutorial by detailing the settings for image rotation, including elevation and asimuth adjustments. It explains the use of the cas sampler and the importance of the Uler rendering method for efficiency. The host provides tips on using different sampling methods and configuring the workflow for optimal results. The video also addresses potential mutations in the rotated images, especially with complex shapes, and demonstrates how to create a GIF or other video formats using the VA decode and video combine options.

Mindmap

Keywords

💡3D rotation

3D rotation refers to the process of transforming a two-dimensional image to give it the appearance of being three-dimensional by rotating it around an axis. In the context of the video, this technique is used to create a more dynamic and realistic visual effect, as seen when the Frog image is rotated to different positions.

💡2D images

Two-dimensional images are flat visual representations that only have width and height, without depth. The video's focus is on enhancing these 2D images by applying 3D rotation, which is a technique to simulate depth and movement.

💡Stability AI

Stability AI is the company that has released a new model for 3D rotation of 2D images. This model is likely a machine learning algorithm that enables the transformation of 2D images into 3D-like visuals.

💡Hugging Face

Hugging Face is a platform where developers can find and download various machine learning models, including the one released by Stability AI. It serves as a hub for AI enthusiasts and professionals to access and utilize these models.

💡Comi

Comi appears to be a software or platform where the 3D rotation process is carried out. It allows users to load workflows and manage notes, which are likely scripts or instructions for the AI to follow.

💡Incremental rotation

Incremental rotation refers to the gradual and step-by-step change in the rotation angle of an object. In the video, this concept is used to create a sequence of images with different rotation angles, which can then be combined into a video.

💡Video combine

Video combine is the process of merging multiple images or video clips into a single video file. This technique is used in the video to create a dynamic visual effect from the series of rotated 2D images.

💡Remove BG

Remove BG is a website service that automatically removes the background from an image, leaving only the foreground object. This is useful for creating images that can be easily manipulated in various ways, such as rotation.

💡Clip Vision

Clip Vision is likely a feature or output of the Stability AI model that is used in the 3D rotation process. It may refer to the visual output that the AI generates after processing the input image.

💡Base elevation and base asimuth

Base elevation and base asimuth are terms related to the rotation angles in 3D space. Elevation typically refers to the vertical rotation, while asimuth refers to the horizontal rotation around an object. In the video, these terms are used to define the initial rotation angles for the 2D image.

💡Uler

Uler might be a rendering or sampling method used within the Comi platform to generate the rotated images. It is mentioned as a fast and effective method for rendering in the context of the video.

Highlights

Stability AI has released a new model for rotating 2D images.

The tutorial is hosted on Hugging Face and uses the stable-0123 model.

Comi is recommended as a platform for utilizing new technologies with community-created notes.

Mato's note allows for incremental rotation around an object.

The workflow can be downloaded from the OpenArt AI profile.

Two methods are presented: creating a single rotated image and creating a video from multiple images.

The image's background can be removed using the remove.bg website.

The image checkpoint loader is crucial for the model's output.

Mato's note is used to create increments for rotation.

The base elevation and base azimuth settings control the object's rotation.

The uler sampling method is recommended for its fast rendering.

The VAE decode and video combine notes are used to create a video output.

Rotation can cause shape mutations, especially in complex images.

The pingpong option creates a back-and-forth rotation effect.

The output format can be changed to other options as desired.

The second process demonstrates a single image rotation with different settings.

The video concludes with a call to action for viewers to like and share the content.

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