Krita AI Trick to Removing Objects With AI diffusion Plugin

Streamtabulous
12 Dec 202321:31

TLDRIn this informative video, the creator discusses a method for removing objects from images using the Krita AI diffusion plugin. The process involves manipulating AI diffusion by uploading a static image to the cloud and utilizing it within the Krita software. The creator shares a step-by-step guide on how to replace the unwanted object with more fitting elements, such as bushes and trees, and emphasizes the advantages of using open-source tools like Krita over paid platforms. The video also highlights the importance of selecting appropriate models for the task and provides tips for achieving better image blending and realistic renderings.

Takeaways

  • 🎨 The video discusses a method to remove objects from images using Krita's AI diffusion plugin.
  • 🔍 Krita lacks a dedicated AI background removal tool, but the tutorial explores a workaround using AI diffusion.
  • 📈 The presenter shares a downloadable static image file to aid in the AI manipulation process.
  • 🖌️ The use of AI diffusion involves creating a static base image that the AI builds upon to generate new images.
  • 💻 The presenter's system is an older GTX 1070, which limits the resolution they can work with for faster rendering.
  • 🧠 The presenter prefers Krita's AI diffusion due to the ability to select models and the live preview feature, which is great for kids and beginners.
  • 🚀 The presenter describes the process of uploading the static image to Krita's data folder and using it to influence AI rendering.
  • 🎉 The AI diffusion process is likened to 'magic eyes' where the AI reads the static image and creates a new render based on it.
  • 🌳 The video demonstrates the removal of a vehicle from an image using the AI diffusion technique and adjusting settings for better blending.
  • 🌐 The presenter suggests using different models in Krita depending on the art style and subject matter for optimal results.
  • 💬 The presenter encourages viewers to support open-source projects like Krita and its plugins, and to provide feedback to the creators.

Q & A

  • What is the main topic of the video?

    -The main topic of the video is a tutorial on how to use the AI diffusion plugin in Krita to remove objects from images.

  • What is the AI diffusion plugin used for in Krita?

    -The AI diffusion plugin is used to manipulate images by adding or removing elements, such as objects in the background, using artificial intelligence.

  • How does the AI diffusion plugin work in Krita?

    -The AI diffusion plugin works by creating a static image and using that as a base to build a unique image every time. It can generate new content based on the static pattern provided by the user.

  • What is the advantage of using the AI diffusion plugin over Adobe's tools?

    -The advantage of using the AI diffusion plugin over Adobe's tools is that it is free, open-source, and allows users to select different models and use a graphical user interface similar to Adobe or Corel.

  • What kind of objects can the AI diffusion plugin help to remove from an image?

    -The AI diffusion plugin can help to remove various objects, such as a vehicle in the background of an image, by generating new content that blends with the surrounding area.

  • How can users obtain the static diffusion pattern file mentioned in the video?

    -Users can obtain the static diffusion pattern file by downloading it from the provided link on the creator's cloud storage, which will then be placed in the Krita data folder.

  • What are some of the challenges faced when using the AI diffusion plugin?

    -Some challenges include the plugin not always accurately removing objects, the need for adjustments to settings like padding, and the potential for the AI to create unwanted elements in the image.

  • What are some tips for improving the results with the AI diffusion plugin?

    -Tips for improving results include adjusting the padding settings, selecting the right models for the task, using a lower resolution for faster rendering, and adjusting the saturation to better blend the generated content with the original image.

  • What is the future potential of the AI diffusion plugin?

    -The future potential of the AI diffusion plugin includes the development of new models trained on higher resolutions, better language understanding for more accurate object removal, and the possibility of additional tools and plugins created by the community.

  • How can viewers support the development of the AI diffusion plugin?

    -Viewers can support the development by using the plugin, providing positive feedback to the creator, and sharing the plugin with others to increase its user base and encourage further development.

Outlines

00:00

🎥 Introduction to AI Manipulation in Stream Tabulous

The speaker begins by welcoming viewers to Stream Tabulous and expresses an intention to explore AI manipulation techniques, specifically within the Cryer platform. The focus is on learning how to influence AI diffusion to perform certain tasks, such as adding or removing objects within an image. The speaker references a previous video on adding elements like a cat and intends to delve into background object removal, despite not having a dedicated AI removal tool. The introduction also includes a brief mention of the app's interface and the speaker's preference for Cryer diffusion due to its customizable model selection and live preview features.

05:01

🖼️ Adjusting Resolution and Removing Objects

In this segment, the speaker discusses the process of adjusting the image resolution to accommodate their older system's limitations. They explain the intention to remove a vehicle from the image and the challenges faced when using a 1.5 model on their system. The speaker then explores the use of 'Bush and trees' to replace the vehicle, but acknowledges the limitations of the AI in properly rendering the replacement. They delve into the concept of static diffusion, explaining how it works and how it can be utilized to influence AI-generated images. The speaker also discusses the importance of tool options and settings in achieving the desired outcome.

10:02

🌄 Fine-Tuning and Blending Elements

The speaker continues by discussing the fine-tuning process of the AI manipulation, particularly focusing on padding and blending aspects. They share an error made in a previous video and how resetting it can improve the blending of elements within the image. The speaker emphasizes the importance of leaving padding at its default setting for better blending with the surrounding information. They also touch on the variability of AI renderings depending on the model used, highlighting the benefits of selecting models suited to the artwork's style. The speaker concludes this section by demonstrating how well the AI has blended the manipulated elements into the image.

15:05

🌲 Working with Nature and Reflective Elements

In this part, the speaker explores the application of AI manipulation in creating and adjusting reflective water elements in a natural scene. They compare the capabilities of Adobe and Cryer in rendering reflective water, noting that Adobe was particularly adept at this task. The speaker expresses curiosity about the potential of using static colors in the AI diffusion process. They discuss the impact of workflow on the overall image and the use of comfy AI for reflective water. The speaker also shares their experiences with different models and the importance of selecting models that are best suited to the specific style of the artwork being created.

20:07

🔧 Final Thoughts and Encouragement for Open Source Support

The speaker concludes the video by sharing their thoughts on the potential of Cryer and AI diffusion, emphasizing the benefits of open source platforms. They express hope for wider adoption and improvement of Cryer, encouraging viewers to support the creators of useful plugins. The speaker also highlights the importance of positive feedback in motivating developers to enhance their tools. They end the video by encouraging viewers to like, share, and subscribe to help the YouTube channel grow and reach more people.

Mindmap

Keywords

💡Krita AI

Krita AI refers to the integration of artificial intelligence into the Krita software, which is a free and open-source digital painting application. In the context of the video, Krita AI is used to manipulate images, specifically to remove or add objects within a scene using AI diffusion plugins. This technology allows users to achieve complex image editing tasks that would otherwise require a high level of manual skill.

💡AI diffusion

AI diffusion is a process in which artificial intelligence algorithms create new images or modify existing ones by generating and manipulating static noise. This technique is used in the video to alter images within the Krita software, where the AI builds unique images every time based on the static input it receives. The process involves creating a static image that serves as a foundation for the AI to build upon, resulting in a new, often unpredictable visual outcome.

💡Background removal

Background removal is the process of eliminating the background elements from an image or a video, typically to isolate the subject or to replace the background with a new one. In the context of the video, the author discusses using Krita AI and AI diffusion techniques to remove unwanted objects from the background of an image, such as a vehicle, to achieve a cleaner or more desired composition.

💡Static image

A static image is a non-moving picture that does not involve any form of animation or change over time. In the context of the video, the static image is used as a base for the AI diffusion process. The AI uses this static image to generate a unique, dynamic image by building upon the initial static input. This concept is crucial in the video as it forms the foundation for the AI to create new content and manipulate existing images within Krita.

💡Cloud storage

Cloud storage refers to the practice of storing data or files on remote servers accessed via the internet, rather than on local hardware like a computer or a USB drive. In the video, the term is used to describe where the static diffusion file is uploaded, allowing viewers to download it for use in their own Krita AI projects. Cloud storage provides a convenient and accessible way to share and collaborate on files across different devices and locations.

💡Resolution

Resolution in the context of digital images refers to the dimensions of the image, typically measured in pixels. Higher resolution images have more pixels and therefore more detail. In the video, the creator discusses adjusting the resolution of the image to better suit their system's capabilities, as higher resolutions can require more processing power and result in longer rendering times.

💡Adobe

Adobe is a software company known for its creative cloud suite of applications, including Photoshop, which is widely used for image editing and manipulation. In the video, Adobe is mentioned as a comparison to Krita AI, highlighting the advantages and disadvantages of both platforms. The creator discusses the benefits of Adobe's AI model training and its language model, which provides a better understanding of user inputs like 'remove', but also expresses a preference for Krita due to its open-source nature and the ability to select different models.

💡Open source

Open source refers to a type of software licensing in which the source code is made publicly available for anyone to view, modify, and distribute. This philosophy encourages collaboration and community involvement in the development and improvement of software. In the video, the term is used to describe the nature of Krita and its AI diffusion plugins, emphasizing the benefits of having a community-driven, freely accessible software that can be enhanced by anyone.

💡Rendering

Rendering in the context of digital imaging refers to the process of generating a final image or sequence of images from a set of instructions, typically involving complex calculations to determine the appearance of objects, lighting, and other visual elements. In the video, rendering is discussed in relation to the time it takes for the AI to process and create new images based on the static input provided by the user.

💡AI model training

AI model training is the process of teaching an artificial intelligence system how to perform a specific task by providing it with large amounts of data and adjusting its parameters through algorithms. In the context of the video, the creator discusses the training of AI models for image editing, noting that different models are trained on different datasets, which can affect their performance and suitability for specific tasks, such as photo restoration or nature scenes.

💡Reflective water

Reflective water in digital imaging refers to the simulation or depiction of water surfaces that reflect the surroundings, such as objects, light, and colors. This effect is often used to enhance the realism of digital scenes. In the video, the creator expresses curiosity about whether the AI diffusion process can effectively render reflective water, as this would be a testament to the AI's ability to understand and replicate complex visual phenomena.

Highlights

The video demonstrates a method for removing objects from the background using Krita and AI diffusion.

Krita lacks a built-in AI background removal tool, so the video explores a workaround using AI diffusion.

A static diffusion pattern is used to manipulate the AI into creating a unique image from static.

The process involves uploading a static image file to the cloud and using it within Krita's AI diffusion tool.

The video discusses the limitations of Krita's AI model compared to Adobe's, particularly in rendering speed.

The presenter prefers Krita's AI diffusion for its live preview and customizable model selection.

A detailed guide on how to install and use the AI diffusion tool with Krita is provided.

The technique involves creating a new layer and flooding it with static colors to influence the AI's output.

The video shows how to adjust settings like padding and blending for better image results with AI diffusion.

The presenter discusses the importance of selecting the right AI model suited to the artwork's style.

The video provides a method to remove unwanted elements from a photo using AI diffusion in Krita.

The presenter shares a logical guess based on patterns observed during the use of stable diffusion.

A downloadable static pattern is mentioned to assist with the AI diffusion process in Krita.

The video explores the potential of open-source tools like Krita and the AI diffusion plugin for creative editing.

The presenter encourages viewers to provide feedback and support to the creators of open-source tools.

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