Master the Art of Posing and Coloring with Control-Net AI

Table of Contents

1. Introduction
2. Background: The Challenges of Posing Characters in Web UI
3. The Revolutionary Technology of Control-Net
4. Installing Mikubill's "SD-WebUI-ControlNet"
5. Installing the Model for the Control Net
6. Using Open Pose to Reproduce a Pose from an Image
7. Extracting the Stick Figure and Reproducing the Pose
8. Representing the Control Net with an Image
9. Using CannyEdge for Line Extraction
10. Coloring the Image from Line Art
11. Other Functions of the Control Net
12. Conclusion

Article

Introduction

In the world of character design and illustration, posing characters in a way that is aesthetically pleasing can be a challenging task. Traditional methods often involve writing complex code or using 3D drawing software, making the process time-consuming and cumbersome. However, with the release of Control-Net, a revolutionary technology developed by Iliasviel, posing characters has become much easier. In this article, we will explore the capabilities of Control-Net and learn how to install and use it in the web UI.

Background: The Challenges of Posing Characters in Web UI

Until recently, posing characters in the web UI required writing intricate "spells" or using 3D drawing software to Create poses. This process was not only time-consuming but also demanded technical expertise. Additionally, users had to rely on Gacha rolls to acquire the desired poses. However, in February 2023, Control-Net was introduced as a groundbreaking solution to these challenges. Control-Net allows users to easily pose characters without the need for complex coding or external software.

The Revolutionary Technology of Control-Net

Control-Net is a technology that enables users to generate poses for characters effortlessly. It has been hailed as a game-changer in the world of character design and illustration. With Control-Net, users can take any image and reproduce its pose using the web UI. The technology uses advanced algorithms and machine learning to analyze and recreate the pose from the input image. This breakthrough has opened up new possibilities for artists and designers, making character posing more accessible and efficient.

Installing Mikubill's "SD-WebUI-ControlNet"

To start using Control-Net in the web UI, You need to install Mikubill's "SD-WebUI-ControlNet" extension. The local version, Automatic 1111, should already be installed. If not, you can find installation instructions in previous videos. To install the extension, access Mikubill's page on GitHub and copy the URL. Launch the web UI, open the extension tab, and go to the "Install from URL" tab. Paste the URL and click the "Install" button. Wait for the installation to complete, and then go to the "Install" tab to ensure that the extension is successfully installed.

Installing the Model for the Control Net

In addition to the extension, you also need to install the model for the Control Net. This model is essential for generating accurate poses. To install the model, access the Hugging Face Website and search for "Control Net" in the search window. Look for "WebUI ControlNet Module SafeTensors" and click on it. You will find a list of files uploaded under "File & Versions." Download the 8 files starting with "Control." These files are approximately 6GB in total, so ensure you have sufficient storage. Once downloaded, place the files in the "Extensions" folder within the Web UI Install folder. Restart the Web UI to complete the installation.

Using Open Pose to Reproduce a Pose from an Image

One of the key functions of Control-Net is the ability to reproduce a pose from an image using open pose. Open the T2i tab in the web UI and set the prompt and desired qualities. Click on the Control Net script and drop an image of a stick-person sitting with one knee up from the sample provided by the author. Enable the Control Net by checking the corresponding box. Leave the pre-processor as "Non" and select "Open Pose" as the model. Generate the pose, and you will Notice that the same pose as the stick-figure is accurately reproduced, even if the legs are buried.

Extracting the Stick Figure and Reproducing the Pose

Another impressive feature of Control-Net is the ability to extract the stick figure from an image and reproduce its pose. To achieve this, drop an image of a girl's illustration next to the sample image in the web UI. Change the pre-processor from "Non" to "Open Pose" and keep the other settings the same. Generate the pose, and you will witness the Control Net accurately reading the pose from the sample image and reproducing it. This showcases the power of Control-Net in extracting and recreating poses with precision.

Representing the Control Net with an Image

The Control Net adds an additional layer to the generated image, allowing for even more control over the final result. Without the Control Net, generating images would be random regardless of pose or position. However, by adding the Control Net, the Outline of the target image is extracted and reflects in the final result. The Control Net acts as an additional order to the prompt, similar to specifying preferences at a ramen shop. This feature gives users the ability to fine-tune the generated image according to their desired outcome.

Using CannyEdge for Line Extraction

CannyEdge is another powerful function within Control-Net that allows for line extraction. By using CannyEdge, users can create images with strong line art. To utilize this function, drop an image of a red cloth girl into the web UI and select "Canny" as both the pre-processor and the model. Generate the image, and you will notice that the output has a distinct Sense of line art. This demonstrates how the Control Net can Trace and reproduce the outline accurately, resulting in stunning line art images.

Coloring the Image from Line Art

The Control Net can also be used to color images Based on line art. By utilizing the detected-map, which is an image of the stick-figure extracted using the Control-Net, users can easily colorize the image without disturbing the line art. The detected-map is stored in the install folder of the web UI, and users can access it to generate colored images. By dropping the line art into the web UI, selecting the appropriate pre-processor and model (Canny), and checking the "invert input color" option for black and white illustrations, users can generate beautifully colored images that stay true to the original line art.

Other Functions of the Control Net

While Control-Net offers various functions, it primarily relies on open pose and cannyedge for the majority of tasks. However, there are additional functions available for specialized purposes. These functions include Multi-Scale Line Segment Detector (MLSD) for straight line extraction, Normal Map for surface uneven detection, Depth for extracting depth from images, Holistically Nested Edge Detection for repainting, Pixel Difference Network for clearer line art, Graffiti for generating images based on graffiti, and Segmentation for automatically creating compositions, floors, and walls for indoor design. These functions provide users with a wide range of options for their creative endeavors.

Conclusion

The introduction of Control-Net has revolutionized the way characters are posed and images are generated. Its user-friendly interface and powerful capabilities make it an invaluable tool for artists, designers, and VTubers. From easily reproducing poses to colorizing line art, Control-Net offers endless possibilities for creative expression. By following the installation and usage instructions provided in this article, users can unlock the full potential of Control-Net and enhance their artistic endeavors. Embrace the power of Control-Net and take your character design and illustration to new heights!

Highlights

• Control-Net revolutionizes character posing in web UI.
• Installing Mikubill's "SD-WebUI-ControlNet" extension for easy pose generation.
• Reproducing poses using open pose and extracting stick figures with Control-Net.
• Adding an additional layer to the generated image for further control.
• Utilizing CannyEdge for strong line art images.
• Colorizing images from line art with the detected-map.
• Exploring other functions of Control-Net, including MLSD, Normal Map, Depth, Holistically Nested Edge Detection, Pixel Difference Network, Graffiti, and Segmentation.
• Control-Net offers endless possibilities for character design and illustration.

FAQ

Q: What is Control-Net?
A: Control-Net is a revolutionary technology that allows users to generate poses for characters in a web UI environment. It simplifies the process of posing characters, making it more accessible and efficient.

Q: How do I install Control-Net?
A: To install Control-Net, you need to download and install Mikubill's "SD-WebUI-ControlNet" extension. Instructions for installation can be found in the article.

Q: Can Control-Net extract poses from images?
A: Yes, Control-Net can extract poses from images using open pose. It analyzes the image and reproduces the pose accurately.

Q: Can I colorize images using Control-Net?
A: Yes, Control-Net allows users to colorize images based on line art. By utilizing the detected-map, users can easily add color to their images while preserving the original line art.

Q: What are the other functions of Control-Net?
A: Control-Net offers various functions, including line extraction, surface uneven detection, depth extraction, edge detection, graffiti generation, and automatic composition creation.

Q: Can Control-Net be used for game development?
A: Yes, Control-Net can be used in game development to enhance character designs and create background illustrations.

Q: Is Control-Net suitable for VTubers using Live2D?
A: Yes, Control-Net can be used by VTubers to easily generate samples of different outfits, allowing for more dynamic content creation.

Q: How does Control-Net compare to traditional methods of posing characters?
A: Control-Net simplifies and streamlines the process of posing characters, eliminating the need for complex coding or external software. It offers more control and precision in generating poses.

Q: Is Control-Net compatible with different operating systems?
A: Control-Net is compatible with the web UI and can be accessed via a web browser, making it accessible across different operating systems.

Q: Is Control-Net suitable for beginners in character design and illustration?
A: While Control-Net offers powerful capabilities, beginners may find it challenging to grasp all its features initially. However, with time and practice, users can master Control-Net and enhance their creative endeavors.