ControlNet - Openpose face [TensorArt]

In this TensorArt tutorial, the host guides viewers through the use of OpenPose technology to analyze facial expressions and poses. The video begins with adding a ControlNet and selecting OpenPose for facial analysis. The host demonstrates importing a close-up image of a soccer player's face and using OpenPose to capture facial expressions and character poses. The process continues with experimenting with different models to render images in a cartoon style. The tutorial then explores using facial OpenPose to control character poses and expressions, reducing the need for repeated image generations. The host also shows how to create ensemble images with multiple characters by modifying facial maps and using them as control images in TensorArt. The video concludes with a teaser for an upcoming project involving creating group images using Photopia and TensorArt to generate a unique composition that captures the individuality of each member.

Takeaways

• 🎓 **TensorArt Tutorial**: The video is a tutorial on using TensorArt to analyze facial poses with OpenPose.
• 📈 **ControlNet Integration**: Adding ControlNet to TensorArt workspace and selecting OpenPose for facial analysis is demonstrated.
• 🖼️ **Image Upload and Processing**: The process of uploading a close-up image and using OpenPose to analyze facial expressions is shown.
• 🎭 **Facial Expression Capture**: OpenPose can capture facial expressions and a portion of the character's pose, offering an interesting option for character design.
• 🖌️ **Cartoon Style Rendering**: A model is selected to render the soccer player's image in a cartoon style, with the effect varying based on model choice.
• 🔍 **Facial Pose Control**: Using ControlNet and OpenPose, the video illustrates how to achieve greater control over character poses and expressions.
• 🎼 **Singing Girl Example**: The creation of images of a singing girl is used to demonstrate the process of generating images with specific poses and expressions.
• 🧩 **Portrait Puzzle Technique**: The video outlines a method of creating a group image by arranging individual portraits like a puzzle and then generating final images with TensorArt.
• 🖥️ **Photo Editing for Maps**: Photo editing tools like Photo Pier are used to modify and align facial maps for creating ensemble images.
• 🔗 **ControlNet Parameter Adjustments**: The video explains how to adjust ControlNet parameters to fit the newly created map and enhance image resolution.
• 🌟 **Maximizing Functionalities**: The importance of leveraging TensorArt's functionalities, such as facial OpenPose, for precise and customized results is emphasized.

Q & A

What is the main focus of the tutorial in the video?

The main focus of the tutorial is to explore the use of OpenPose for analyzing and understanding facial poses using TensorArt's ControlNet.

How does the ControlNet button in TensorArt workspace allow the user to proceed?

By clicking on the 'add ControlNet' button, the user can add the ControlNet to their workspace and then select 'OpenPose' in the subsequent screen.

What type of image is initially imported into the ControlNet for facial pose analysis?

A close-up image of a face, specifically of soccer players captured in an iconic moment of celebration, is initially imported for facial pose analysis.

What is the advantage of changing the pre-processor setting to 'OpenPose face only'?

Changing the pre-processor setting to 'OpenPose face only' allows capturing not only the facial expression but also a portion of the character's pose, providing a more detailed analysis.

How does the user confirm their choice of model for rendering the soccer player's image in a cartoon style?

The user confirms their choice by entering the text into the prompt from the top menu and selecting a model like 'real cartoon 3D'.

What is the significance of using facial OpenPose in generating characters?

Facial OpenPose allows for greater control over generating characters by communicating both the desired pose and facial expression to the artificial intelligence, reducing the need for repeated image generations.

How does the ControlNet help in achieving a specific pose for a character?

The ControlNet uses the facial pose map generated by TensorArt to ensure that the generated images of characters all possess the same desired pose as defined by the user.

What is the purpose of using Photo Pier to modify the facial map?

Photo Pier is used to modify the facial map to create multiple aligned faces, which can then be used to generate images featuring ensembles of characters with coordinated poses and expressions.

How does the user ensure that the newly created map fits into the allowed dimensions in TensorArt?

The user adjusts the aspect ratio and dimensions of the map in Photo Pier to match the maximum allowed width in TensorArt and inputs the adjusted height value into the settings section of TensorArt.

What is the final step in generating the quartet of singers using the modified facial map?

The final step is to make small modifications to the prompt text and initiate the image generation to obtain the desired images of the quartet of singers.

What is the upcoming project that the channel plans to explore?

The upcoming project involves creating group images using Photopia and TensorArt by arranging individual portraits like a puzzle to form a unique composition and then generating final images based on the facial pose maps extracted from this composition.

How can viewers stay updated on the channel's artistic adventures?

Viewers can subscribe to the YouTube channel to receive updates on new techniques and projects shared by the channel.

Outlines

00:00

😀 Introduction to Tensor Arts and Open Pose for Facial Analysis

The video begins with a warm welcome to the channel, expressing excitement for exploring the capabilities of Tensor Arts' control net. The focus is on using Open Pose to analyze facial poses. The presenter encourages viewers to catch up on previous content through a playlist. The tutorial starts with adding a control net and selecting Open Pose, modifying the pre-processor settings to 'Open Pose Face Only'. The presenter then uploads a close-up image of a soccer player's face and observes the output with facial expressions marked by dots. The video demonstrates the ability to capture facial expressions and partial character poses, noting the minimal differences but highlighting the option's potential. The presenter confirms the choice and closes the dialogue box, proceeding to render the soccer player's image in a cartoon style using a model named 'Real Cartoon 3D'. The effectiveness of the model choice is discussed, and the process of generating multiple images is described. The presenter also explains how facial Open Pose can provide greater control over character generation, reducing the need for repeated image generations.

05:02

🎭 Control Net's Role in Achieving Desired Poses

The second paragraph delves into the use of the control net for achieving specific poses in image generation. The presenter describes using Open Pose Face to generate a facial map on a black background, which is then saved and edited using a photo editing tool like Photo Pier. The process involves cropping the image to the desired dimensions, duplicating the layer to display multiple faces side by side, and scaling the images to provide perspective. The presenter's goal is to create an ensemble image with multiple singers. Adjustments are made to the map's dimensions in Photo Pier to fit within the allowed dimensions of Tensor Art, and the aspect ratio is changed to 'custom'. The presenter emphasizes the importance of maximizing Tensor Art's functionalities, such as facial Open Pose, to customize and achieve precise results. The result of using the control net is demonstrated with four images of singers all sharing the same pose, showcasing the potential of this technique.

10:02

🧩 Creating Ensemble Images with Facial Pose Maps

In the third paragraph, the presenter outlines a method for creating ensemble images with multiple characters using facial pose maps. The process begins with importing a modified facial map into Tensor Art and adjusting the settings to accommodate the new dimensions. The presenter increases the resolution enhancement to improve the final image quality. The prompt text is slightly modified, and two images are generated, resulting in an astonishing quartet of singers. The presenter teases an upcoming project that involves creating group images using Photopia and Tensor Art, where individual portraits are arranged like a puzzle to form a unique composition. This portrait puzzle is then used to generate final images that capture the individuality of each member in a harmonious group composition.

15:06

📢 Conclusion and Call to Action

The final paragraph concludes the tutorial by emphasizing the astonishing results that can be achieved by representing individuality in a harmonious group composition. The presenter invites viewers who are fascinated by this kind of content to subscribe to the YouTube channel for updates on artistic adventures. The presenter thanks the viewers for their attention and for being part of the community, encouraging continued engagement and exploration of creative techniques and projects.

Keywords

TensorArt

TensorArt refers to the use of artificial intelligence, specifically deep learning models, to create art. In the context of the video, it is the platform that the presenter uses to generate images and manipulate them according to specific artistic visions. The term encapsulates the fusion of technology and creativity, allowing for the exploration of artistic possibilities through computational methods.

ControlNet

ControlNet is a feature within the TensorArt platform that enables users to have more control over the generation of images. It is used to direct the AI in creating specific poses or expressions in the generated artwork. In the video, the presenter adds ControlNet to the workspace to achieve a more precise outcome in the facial poses of the characters.

OpenPose

OpenPose is a popular open-source project that uses AI to detect human poses in images or videos. In the video, the presenter uses OpenPose to analyze and understand facial poses, which is a crucial step in generating images with specific facial expressions. It is used to capture not only the facial expression but also a portion of the character's pose.

Facial Poses

Facial poses refer to the positions and expressions of the face. In the context of the video, the presenter is interested in using technology to analyze and replicate these poses in generated images. The ability to control facial poses is important for creating realistic and expressive characters in art.

Pre-processor

A pre-processor in the context of the video is a tool or setting within the TensorArt platform that prepares the data before it is used by the AI model. The presenter changes the pre-processor command from 'open pose' to 'open pose face only' to focus specifically on facial analysis.

Cartoon Style

Cartoon style refers to the artistic technique of rendering images in a manner that mimics the exaggerated and simplified visuals typically found in cartoons. The video discusses using a model to render a soccer player's image in a cartoon style, which can vary depending on the model chosen.

Control Net Functions

Control Net functions are part of the TensorArt platform that allow for the manipulation and control of the AI's image generation process. The presenter uses these functions to achieve a specific pose defined by them, demonstrating the potential of using Control Net to customize the outcome.

Photo Pier

Photo Pier, mentioned in the video, is a photo editing tool that the presenter uses to modify the facial map. It is an alternative to Photoshop and is used to create an ensemble image with multiple characters by arranging individual portraits like a puzzle.

Portrait Puzzle

A portrait puzzle is a creative technique described in the video where individual portraits are arranged and overlaid to create a unique composition. This technique is used to generate a group image that represents the individuality of each member in a harmonious composition.

Facial Map

A facial map is a visual representation of the facial features and their positions, which is used by the AI to understand and replicate facial expressions and poses. The presenter saves the facial map with a specific name and uses it as a guide to generate images with controlled facial expressions.

Artificial Intelligence (AI)

Artificial Intelligence (AI) is the broader field of computer science that focuses on creating systems capable of performing tasks that would normally require human intelligence. In the video, AI is central to the process of generating images and controlling their content, such as facial poses and expressions.

Highlights

Introduction to a new tutorial on TensorArt focusing on using OpenPose for facial pose analysis.

Demonstration of adding ControlNet and selecting OpenPose in the TensorArt workspace.

Importing a close-up image of a soccer player's face for facial expression analysis.

Observation of the facial expression represented by dots on a black background.

Exploring the option to capture both facial expression and character pose with OpenPose Face.

Using a model to render the soccer player's image in a cartoon style.

Adjusting the comic-like effect for better optimization.

Illustrating the use of facial OpenPose for greater control over character generation.

Generating images of a singing girl with a specific model and prompt.

Utilizing the ControlNet to achieve a user-defined pose for the generated images.

Downloading and reusing an image as a pose reference in the ControlNet functions.

Generating images with all singers in the same pose using the facial pose map.

Emphasizing the importance of maximizing TensorArt functionalities for precise results.

Exploring the creation of ensemble images with multiple characters using facial OpenPose.

Modifying the facial map using photo editing software like Photo Pier.

Adjusting the dimensions of the facial map to fit the allowed dimensions in TensorArt.

Creating a quartet of singers using the merged layers and facial map in TensorArt.

Discussing an upcoming project involving creating group images using Photopia and TensorArt.

Generating a portrait puzzle by overlaying and aligning individual portraits to create a unique composition.

Using facial pose maps to capture and represent the individuality of each group member.

Invitation to subscribe to the YouTube channel for updates on artistic adventures and techniques.