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Archviz with Blender and Stable Diffusion

4.9 Filled star Filled star Filled star Filled star Half star
Based on 19 ratings
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Alvaro Celis

Using blender to load a project scene, we will learn how to prototype a basic image and enhance it generating different variants through the use of StableDiffusion AI.

First we will install basic software requirements like Python and GIT to be able to clone the projects' repositories and compile them automatically

Next we will install Blender and practice with an existing project to become familiar with the workflow and generate a basic image to work with AI.

Read more

Using blender to load a project scene, we will learn how to prototype a basic image and enhance it generating different variants through the use of StableDiffusion AI.

First we will install basic software requirements like Python and GIT to be able to clone the projects' repositories and compile them automatically

Next we will install Blender and practice with an existing project to become familiar with the workflow and generate a basic image to work with AI.

After that, we will install Krita and the plugin krita_ai_diffusion to load the image generated in Blender and start creating AI images based on our render.

Once we are familiar with the basic concepts we will dive a little deeper and install Webui Forge and ComfyUI, two of the most renown and versatile StableDiffusion interfaces.

We will install the required controlnet models to take advantage of them in Archviz.

We will learn how to render images both in Webui Forge and ComfyUI and compare the results between both interfaces.

Workflows for ComfyUI will be provided to help rendering the images with the different models.

Finally, we will install the AI-Render plugin for Blender to learn how to render directly from the 3d program

No advanced skills or knowledge required, the basic usage of each program will be explained and demonstrated in the course.

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What's inside

Learning objectives

  • Use a blender project to create a basic output image for ai rendering.
  • Learn how to install krita and ai-diffusion plugin
  • Learn how to install and use stablediffusion's webui forge and comfyui interfaces
  • Understand and use different controlnet models to generate archviz images.
  • Render image variants directly from blender with ai-render plugin.

Syllabus

Become familiar with the course structure and download the practice Blender file.

Using blender to load a project scene, we will learn how to prototype a basic image and enhance it generating different variants through the use of StableDiffusion AI.

First we will install basic software requirements like Python and GIT to be able to clone the projects' repositories and compile them automatically

Next we will install Blender and practice with an existing project to become familiar with the workflow and generate a basic image to work with AI.

After that, we will install Krita and the plugin krita_ai_diffusion to load the image generated in Blender and start creating AI images based on our render.

Once we are familiar with the basic concepts we will dive a little deeper and install Webui Forge and ComfyUI, two of the most renown and versatile StableDiffusion interfaces.

We will install the required controlnet models to take advantage of them in Archviz.

We will learn how to render images both in Webui Forge and ComfyUI and compare the results between both interfaces.

Workflows for ComfyUI will be provided to help rendering the images with the different models.

Finally, we will install the AI-Render plugin for Blender to learn how to render directly from the 3d program

No advanced skills or knowledge required, the basic usage of each program will be explained and demonstrated in the course.


Read more

We will download and install the first 3 programs we require to get started: Python, GIT and Blender.
In the end we will be able to verify we have a working Python/GIT environment.

In this lesson we will load the practice scene, learn  some Blender basics and how to generate a mist pass render.

In this lesson we will download Krita and the AI-Diffusion plugin, install a working ComfyUI environment and finally load the mist pass image, turn it into a depth image and generate our first AI Archviz image.

In this lesson we will learn how to install WebUI Forge in Windows using the 1-click installer, load the interface and become familiar with image generation.

In this lesson we will learn how to install WebUI Forge in Linux, load the interface and become familiar with image generation.

In this lesson we will learn how to install ComfyUI in Windows using the 1-click installer, load the interface and become familiar with image generation using ComfyUI's node-based interface.

In this lesson we will learn how to install ComfyUI in Linux, load the interface and become familiar with image generation using ComfyUI's node-based interface.

In this lesson we will learn how to generate archviz images using WebUI Forge and Controlnet using the 5 most common preprocessors for architecture: DEPTH, CANNY, LINEART, MLSD, and SEG.

In this lesson we will learn how to generate archviz images using ComfyUI and Controlnet using the 5 most common preprocessors for architecture: DEPTH, CANNY, LINEART, MLSD, and SEG and in the process, learn how to use workflows.

In this lesson we will learn how to render archviz images directrly from Blender by installing the AI-Render plugin. We will apply all the concepts learned so far in WebUI Forge and ComfyUI directly in the Blender interface and we'll also learn how to install and use the blenderkit addon to insert assets directly into our 3d scene.

In this lesson we will summarize what we learned throughout the course, as well as review the terms we learned. Then we will migrate out Krita's ComfyUI installation into our local ComfyUI and verify it's connected and working properly. Finally we will see other uses of Krita and Blender for AI image generation.

In this lesson we will learn how to generate the following render passes in Blender: Depth, Lineart, Normal and Segment. Then we will use them to generate ArchViz Images in ComfyUI and Krita/AI Diffusion.

In this lesson we will learn how to keep our programs and files updated. We will learn how to update Blender, Krita, Krita's AI Diffusion plugin, ComfyUI, WebUI Forge, and its models and checkpoints.

In this lesson we will learn how to implement and use Flux.1, the best model available so far, with Controlnet for archvis.

Traffic lights

Read about what's good
what should give you pause
and possible dealbreakers
Integrates Blender with Stable Diffusion, which allows users to create AI-generated architectural visualizations from 3D models
Explores WebUI Forge and ComfyUI, two interfaces that are known for their versatility in Stable Diffusion
Uses ControlNet models, which are useful for generating architectural images with Stable Diffusion
Requires installing Python and Git, which may require some initial setup for users unfamiliar with these tools
Teaches how to use Krita and its AI Diffusion plugin, which expands the possibilities for image creation
Covers the AI-Render plugin for Blender, which enables rendering directly from the 3D program

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Reviews summary

Archviz workflow with blender and ai

According to learners, this course offers a comprehensive look at integrating Blender with various AI tools like Krita, Webui Forge, and ComfyUI for architectural visualization. Students appreciate the practical workflows provided, particularly for using Controlnet models. While the course covers a wide range of software and techniques, including the useful AI-Render plugin for Blender, some reviewers note significant challenges with installation and software setup, sometimes due to rapidly evolving technology. The course positions itself as beginner-friendly, but some found certain sections or the technical setup demanding.
Basic Blender comfort level seems helpful.
"While it says no advanced skills, having at least basic familiarity with Blender definitely makes the start easier."
"The Blender section is very quick; if you're totally new, you might need more resources."
"Loading scenes and generating passes assumes you know where things are in Blender."
Direct Blender AI rendering is highlighted.
"The AI-Render plugin section was fantastic, being able to generate AI variations directly within Blender saves so much time."
"Loved learning how to use the AI-Render plugin, it's a powerful addition to the workflow."
"Rendering from Blender using the plugin felt like the most integrated and efficient method taught."
Useful techniques demonstrated for Archviz.
"The demonstrations using different Controlnet models specifically for architecture were incredibly useful."
"Learning how to generate render passes in Blender and use them with AI was a game changer."
"The workflows provided for ComfyUI were a huge help in getting started with that interface."
"The section on img2img and txt2img with Controlnet provided actionable steps for my projects."
Covers multiple key AI software interfaces.
"I liked that it didn't just stick to one AI interface but showed workflows in Krita, Forge, and ComfyUI."
"Getting introduced to both WebUI Forge and ComfyUI node systems was very valuable for understanding options."
"The breadth of software covered gives a great overview of the Archviz AI landscape."
Some instructions lag behind software updates.
"Software updates happen fast, and some parts of the course, especially installation, feel slightly outdated now."
"Had to figure out workarounds because the interface shown in the video was different from the current version."
"Keeping up with the rapid changes in AI software is hard, the course could benefit from more frequent updates."
Setup process is challenging for many.
"Setting up all the software, especially Python and GIT dependencies, was a major headache and took me days."
"I struggled immensely with the installation steps, they felt outdated for the current software versions."
"Couldn't get ComfyUI or Forge to install correctly following the video, needed external troubleshooting."
"The installation part is really tricky and requires a certain comfort level with technical issues."
"I spent more time fighting with the setup than learning the actual content initially."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Archviz with Blender and Stable Diffusion with these activities:
Review Blender Fundamentals
Reinforce your understanding of Blender's interface and basic operations to ensure a smooth transition into AI-assisted architectural visualization.
Show steps
  • Review Blender's UI and navigation.
  • Practice basic modeling and object manipulation.
  • Experiment with materials and lighting.
Read 'The Architecture of Image Synthesis with Stable Diffusion'
Gain a deeper understanding of the Stable Diffusion technology used in the course by exploring its architecture and image synthesis techniques.
View Melania on Amazon
Show steps
  • Obtain a copy of the book.
  • Read the chapters related to Stable Diffusion's architecture.
  • Take notes on key concepts and techniques.
Experiment with Different ControlNet Models
Solidify your understanding of ControlNet by experimenting with different models and preprocessors to achieve specific architectural visualization effects.
Show steps
  • Choose a Blender scene to work with.
  • Generate various ControlNet preprocessor images (depth, canny, etc.).
  • Use WebUI Forge or ComfyUI to generate images with different ControlNet models.
  • Compare the results and analyze the impact of each model.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Document Your Workflow
Improve your understanding and retention by documenting your workflow for creating architectural visualizations with Blender and Stable Diffusion.
Show steps
  • Outline your entire process, from Blender scene setup to final image generation.
  • Include screenshots and detailed explanations of each step.
  • Share your documentation with other students for feedback.
Build a ComfyUI Workflow for Archviz
Deepen your understanding of ComfyUI by creating a custom workflow specifically tailored for architectural visualization tasks.
Show steps
  • Research existing ComfyUI workflows for image generation.
  • Design a workflow that incorporates ControlNet and other relevant nodes.
  • Test and refine your workflow with different Blender scenes.
  • Share your workflow with the community.
Read 'Architectural Design with Artificial Intelligence'
Explore the broader context of AI in architectural design to gain a deeper appreciation for the potential of the tools and techniques covered in the course.
View Architecture in the Age of Artificial... on Amazon
Show steps
  • Obtain a copy of the book.
  • Read the chapters related to AI's impact on architectural design.
  • Reflect on how the concepts discussed relate to the course material.
Contribute to AI-Render Plugin
Enhance your skills and contribute to the community by contributing to the AI-Render plugin for Blender.
Show steps
  • Explore the AI-Render plugin's codebase.
  • Identify bugs or areas for improvement.
  • Submit pull requests with your contributions.

Career center

Learners who complete Archviz with Blender and Stable Diffusion will develop knowledge and skills that may be useful to these careers:
Architectural Visualizer
The architectural visualizer role brings architectural designs to life. They create photorealistic images and animations of buildings and landscapes. This course is directly relevant, as it focuses on using Blender and Stable Diffusion for architectural visualization. You will learn how to use Blender to create a base image and then enhance it with AI using Stable Diffusion. Mastery of this process sets the stage for creating compelling visualizations. The course also teaches how to use various Controlnet models to generate architectural images and how to render images directly from Blender with the AI Render plugin.
See salaries and explore the career path for Architectural Visualizer
AI Artist
AI artists leverage artificial intelligence tools to generate artwork, often by combining traditional art techniques with AI algorithms. As this course teaches the use of AI tools like Stable Diffusion, WebUI Forge, and ComfyUI, it acts as a great way to get one acquainted with this field. You will learn how to integrate these tools with Blender and Krita to create stunning architectural visualizations. You will also learn how to use Controlnet models and the AI Render plugin, which allows rendering images directly from Blender, making the course invaluable to any aspiring AI artist.
See salaries and explore the career path for AI Artist
Virtual Reality Environment Designer
Virtual reality environment designers build immersive experiences for virtual reality applications. This course can help with those who want to use AI in conjunction with traditional tools to create VR environments. You will learn to use Blender to create base environments and Stable Diffusion to enhance textures and details. By understanding how to prototype an image and generate variants through AI, you will be able to create more realistic and engaging VR environments. Furthermore, the course covers using Controlnet models to refine images.
See salaries and explore the career path for Virtual Reality Environment Designer
Digital Artist
Digital artists create art using digital tools and software, often working on projects ranging from illustrations to visual effects. This course is a great introduction for digital artists seeking to expand their skill set with AI tools. The course covers how to use Blender and Stable Diffusion to create and enhance images, as well as how to use Krita and various Stable Diffusion interfaces like WebUI Forge and ComfyUI. You will also learn how to use Controlnet models and render images directly from Blender using the AI Render plugin.
See salaries and explore the career path for Digital Artist
Architectural Designer
Architectural designers develop plans and designs for buildings and other structures. While an architectural designer typically requires a bachelor's or master's degree, this course helps improve the visualization skills of designers. The course focuses on using Blender and Stable Diffusion to create realistic renderings of architectural designs. By learning how to generate image variants using AI and how to use Controlnet models, you will be able to present designs in a compelling and visually appealing way. You will also learn to render images from Blender with the AI Render plugin.
See salaries and explore the career path for Architectural Designer
Interior designer
Interior designers plan and design interior spaces of buildings, focusing on aesthetics and functionality. This course helps with the visual presentation aspect of the profession. It explores the use of Blender and Stable Diffusion to create realistic renderings of interior designs. Learning how to generate different variants of an image through AI helps designers present multiple options to clients more efficiently. Additionally, the course covers the use of Controlnet models and AI Render plugin for Blender. This course is best-suited for interior designers with a strong three-dimensional visualization background.
See salaries and explore the career path for Interior designer
3D Artist
3D artists create three-dimensional models and environments for various industries, including architecture, gaming, and film. This course may be useful for 3D artists interested in incorporating AI into their workflow. The course teaches how to use Blender alongside AI tools such as Stable Diffusion, Krita, WebUI Forge, and ComfyUI. It also covers the installation of necessary software and plugins, such as the AI Render plugin for Blender, and dives into generating image variations using Controlnet models. This course introduces important concepts for artists.
See salaries and explore the career path for 3D Artist
Game Environment Artist
Game environment artists create the visual environments for video games. The course is useful as it explores ways to combine traditional 3D modeling with AI-generated assets. The course uses Blender and Stable Diffusion to create and enhance architectural scenes, which can be directly applied to building game environments. By learning how to use Controlnet models and the AI Render plugin for Blender, you will develop skills that can be used to create detailed and immersive game worlds. A background in art is typically required for this role.
See salaries and explore the career path for Game Environment Artist
Exhibition Designer
Exhibition designers create and manage the design and layout of exhibitions and displays. This course may be useful for exhibition designers for visualizing exhibition spaces and concepts. The course focuses on using Blender and Stable Diffusion to generate architectural visualizations. By learning how to use the AI Render plugin in Blender and how to create image variations using AI, you will be able to quickly prototype and present different exhibition designs. The course also covers the use of various Controlnet models, which will assist in refining visualizations.
See salaries and explore the career path for Exhibition Designer
Landscape Architect
Landscape architects plan and design outdoor spaces, such as parks, gardens, and residential areas. This course may be useful since landscape architecture relies heavily on visual representation. The course teaches using Blender and Stable Diffusion to create realistic renderings of outdoor environments. Learning how to generate image variations with AI and use Controlnet models helps landscape architects present design options effectively. Furthermore, the course covers the installation and usage of the AI Render plugin for Blender, which streamlines the rendering process.
See salaries and explore the career path for Landscape Architect
Product Designer
Product designers conceptualize and design new products, focusing on both aesthetics and functionality. This course may be helpful to those who wish to visualize their designs in a photorealistic manner. The course teaches how to use Blender and Stable Diffusion to create images and enhance them with AI. Learning how to use various Controlnet models to generate realistic product images can greatly assist product designers in presenting their concepts. In addition, you will learn how to render images from Blender with the AI Render plugin. A background in engineering or industrial design is useful in this role.
See salaries and explore the career path for Product Designer
Motion Graphics Designer
Motion graphics designers create animated visuals for various platforms, including television, film, and web. This course may be useful for motion graphics designers as it introduces Blender, a 3D creation suite. Although the course focuses on architectural visualization, the skills learned in Blender, combined with AI tools like Stable Diffusion, can be adapted to motion graphics. The course also covers how to use various Stable Diffusion interfaces like WebUI Forge and ComfyUI, and how to install the AI Render plugin for Blender, all of which may assist in generating unique visual elements.
See salaries and explore the career path for Motion Graphics Designer
Art Director
Art directors oversee the visual style and images for various projects, ensuring they align with the desired aesthetic and brand. This course may be useful to art directors, as it introduces AI tools for image generation. The course teaches how to use Blender and Stable Diffusion to create and enhance images. By understanding the capabilities of AI tools and how to integrate them with Blender and Krita, art directors can explore new creative directions. The course also covers the use of Controlnet models and the AI Render plugin for Blender.
See salaries and explore the career path for Art Director
Marketing Specialist
Marketing specialists develop and implement marketing strategies to promote products, services, or brands. This course may be useful for marketing specialists who work in fields where visual content is essential, such as architecture or interior design. The course teaches how to use Blender and Stable Diffusion to create compelling architectural visualizations, which can be used in marketing campaigns. By learning how to generate image variations using AI and render images directly from Blender, marketing specialists can create high-quality visual content more efficiently.
See salaries and explore the career path for Marketing Specialist
Software Developer
Software developers design, develop, and test software applications. This course may be useful for software developers interested in the intersection of AI and graphics. The course covers the installation and usage of various AI tools, such as Stable Diffusion, WebUI Forge, and ComfyUI, as well as the integration of these tools with Blender and Krita. By understanding how these tools work and how they can be used to generate architectural visualizations, software developers can gain a better understanding of the potential applications of AI in graphics.
See salaries and explore the career path for Software Developer

Reading list

We've selected two books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Archviz with Blender and Stable Diffusion.
Cover image
Architecture in the Age of Artificial Intelligence
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Explores the broader implications of AI in architectural design, providing context for the specific techniques learned in the course. It discusses how AI can be used to generate novel designs, optimize building performance, and enhance the design process. This book is more valuable as additional reading to expand knowledge and is not required for the course.
Architecture in the Age of Artificial Intelligence
Paperback
Check
Architecture in the Age of Artificial Intelligence
Kindle Edition
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Course image
Rating
4.9 Filled star Filled star Filled star Filled star Half star
Effort
6.5 total hours
Via
Udemy
Instructor
Alvaro Celis
Language
English
Traffic lights
Read about what's good
what should give you pause
and possible dealbreakers
Integrates Blender with Stable Diffusion, which allows users to create AI-generated architectural visualizations from 3D models
Explores WebUI Forge and ComfyUI, two interfaces that are known for their versatility in Stable Diffusion
Uses ControlNet models, which are useful for generating architectural images with Stable Diffusion
Requires installing Python and Git, which may require some initial setup for users unfamiliar with these tools
Teaches how to use Krita and its AI Diffusion plugin, which expands the possibilities for image creation
Covers the AI-Render plugin for Blender, which enables rendering directly from the 3D program
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