Midjourney换脸大法！如何用最新上线的--cref参数实现图片换脸/风格迁移操作 Character Reference cref参数是否可以解决角色一致性？如何用CW参数调整参考强度
TLDRThe video script discusses the introduction of the CREF (Character Reference) parameter for the AI绘画 tool, MJ, which aims to improve role consistency in AI-generated images. The creator tests the CREF parameter by using it to generate images of a half-orc and Barack Obama in various styles, demonstrating its capabilities and limitations. The video also explores the use of the CW (Control Weight) parameter to adjust the intensity of the reference, and shows how CREF can be used for style transfer and face-swapping in images, highlighting the rapid advancements in AI technology.
Takeaways
- 🎨 The introduction of the CREF (Character Reference) parameter in MJ aims to improve role consistency in AI-generated images, a previously challenging aspect.
- 🔍 CREF works by allowing users to submit a reference image, enabling MJ to generate images of the same character in different scenes, with a focus on facial consistency.
- 🌟 The CREF parameter is part of a technological trend involving IP-adapter or InstantID, which can achieve a certain level of facial uniformity but may still have limitations in other details like accessories and clothing.
- 📸 The script demonstrates the use of CREF with a half-orc character and a real photo of Barack Obama, showcasing varying degrees of success in facial feature reproduction.
- 🎭 The CREF parameter can be combined with the CW (Control Weight) parameter to adjust the intensity of the reference image's influence, with a range from 0 (only facial features) to 100 (full reference including hairstyle and clothing).
- 🖌️ The video also explores the application of CREF for style transformation, using a real photo and transforming it into different artistic styles through MJ's prompt suggestions.
- 👤 CREF can facilitate 'face-swapping' by combining it with MJ's built-in partial redraw function, allowing users to replace the face in an MJ-generated image with a reference image.
- 🚀 The rapid development of AI is highlighted by the comparison of the time-consuming process of a year ago to the current ease of using CREF for style transformation.
- 📝 The video emphasizes the limitations of CREF, especially when dealing with complex characters with many elements, where full consistency may not be achieved.
- 🛠️ The tutorial provides practical guidance on using CREF and CW parameters, including step-by-step instructions for generating images and adjusting settings.
- 👍 The content creator encourages viewers to support their channel and stay tuned for more tutorials on MJ's features and capabilities.
Q & A
What is the main topic of the video?
-The main topic of the video is the introduction and demonstration of the newly launched CREF (character reference) parameter in MJ, an AI绘画 tool, and its application in maintaining character consistency.
What does the CREF parameter stand for?
-CREF stands for character reference, a parameter that allows users to submit an image and have the AI generate images of the same character in different scenes.
How does the CREF parameter work in MJ?
-The CREF parameter works by allowing users to submit a reference image, which the AI then uses to generate images with consistent character features across different scenes or styles.
What is the role of the CW parameter in conjunction with CREF?
-The CW parameter controls the intensity of the reference to the submitted image. It ranges from 0 to 100, with 0 referencing only the facial features and 100 including other features like hairstyle and clothing.
What are the limitations of the CREF parameter when it comes to character consistency?
-The CREF parameter has limitations when dealing with characters with many elements, as it may not perfectly unify all aspects such as accessories and clothing details.
How can the CREF parameter be used for style migration?
-The CREF parameter can be used for style migration by submitting a reference image and combining it with style-specific prompt words, allowing the AI to generate images in the desired style while maintaining the character's facial features.
What is the practical application of the CREF parameter in the video?
-In the video, the CREF parameter is used to generate images of a half-orc eating a hot dog and to create images of Barack Obama in various artistic styles.
How does the video demonstrate the use of the CREF parameter for facial replacement in images?
-The video demonstrates facial replacement by first generating a cartoon image of a boxing scene and then using the CREF parameter with the局部重绘 (partial redraw) function to replace the face in the image with that of Barack Obama.
What was the purpose of the video at the beginning of the year when the CREF parameter was introduced?
-The purpose of the video at the beginning of the year was to introduce the CREF parameter and provide tutorials on how to use it for character consistency and style migration in AI绘画 with MJ.
How has the AI development impacted the process of style migration in the past year?
-In the past year, the development of AI has made it possible to achieve style migration with just a CREF parameter in MJ, which previously required multiple videos and was less effective, showcasing the rapid advancement in AI capabilities.
What is the advice given to users regarding the use of CREF for character consistency?
-The advice given is for users to have a relatively objective understanding of the CREF parameter, recognizing its limitations, especially when dealing with characters with many elements, and to be aware of its capabilities in style migration and facial replacement.
Outlines
🎨 Introduction to MJ's Character Consistency Parameters
The paragraph introduces the new character consistency parameters for the AI绘画 tool, MJ. It discusses the challenges AI faces in maintaining character consistency and highlights the recent addition of the SREF (style reference) and CREF (character reference) parameters. The speaker explains how these parameters allow for style migration and the creation of images with consistent character features across different scenes. The video aims to test these parameters and their practical applications, using examples such as a half-orc character and real-life images.
🔧 Exploring the CREF and CW Parameters
This section delves into the functionality of the CREF and CW parameters. The CREF parameter is used to reference a character's image for consistency, while the CW parameter adjusts the intensity of the reference, ranging from 0 (only facial features) to 100 (includes additional characteristics like hairstyle and clothing). The speaker demonstrates how these parameters can be used to control the level of detail in the generated images, showing examples with varying CW values and their impact on the final output.
🖌️ Practical Applications and Limitations of CREF
The speaker discusses practical uses of the CREF parameter, such as changing artistic styles and performing facial swaps. They show how to combine CREF with style cues to transform a real photo into a desired art style and how to use MJ's partial redraw feature for facial replacement. The speaker also cautions about the limitations of CREF, especially when dealing with complex characters, and encourages viewers to have a balanced view of its capabilities.
Mindmap
Keywords
💡CREF
💡SREF
💡Character consistency
💡Style transfer
💡IP-adapter/InstantID
💡CW parameter
💡Facial features
💡Local re-drawing
💡MJ
💡Style prompts
Highlights
MJ's new Character Reference (CREF) parameter has been launched, aiming to address the challenge of maintaining character consistency in AI-generated images.
The CREF parameter works by allowing users to submit a reference image, enabling MJ to generate images of the same character in different scenes.
The introduction of CREF parameter follows the earlier launch of the Style Reference (SREF) parameter, which facilitates style transfer in MJ's image generation.
CREF is based on the IP-adapter or InstantID technology, which can achieve facial consistency but may have limitations with other character elements like clothing and accessories.
A practical demonstration of CREF involves creating an image of a half-orc character and then using CREF to generate variations with different scenes, such as eating a hot dog.
The CREF parameter can be combined with a Control Weight (CW) parameter to adjust the intensity of the reference image's influence on the generated image.
CW parameter values range from 0 to 100, with 0 focusing solely on facial features and 100 including other characteristics like hairstyle and clothing.
CREF can be used to change the style of an image while maintaining the character's facial features, as demonstrated by transforming a real photo into a hand-drawn style.
The video showcases a step-by-step guide on how to use CREF and CW parameters to achieve desired image outcomes, including detailed instructions on the input process.
An example of using CREF for a 'face swap' is provided, where the facial features of a generated cartoon image are replaced with those of a real person, such as Obama.
The video emphasizes the limitations of CREF when dealing with characters with complex elements, noting that the more elements a character has, the more challenging it is to achieve full consistency.
The presenter reflects on the rapid development of AI, noting how much more efficient the CREF parameter is compared to previous methods taught in older videos.
The video concludes with a call to action for viewers to like and subscribe for more MJ-related tutorials, highlighting the ongoing support for the audience.
The video provides a comprehensive overview of the new CREF parameter, its practical applications, and the potential for creative exploration in AI-generated art.
The presenter's approach to explaining CREF is methodical and user-friendly, ensuring that viewers can easily understand and apply the new feature.
The video demonstrates the versatility of MJ's AI capabilities, showcasing its potential for both artistic expression and practical image manipulation.
The inclusion of a detailed demonstration and practical examples makes the video an informative resource for users interested in exploring the possibilities of AI in art creation.
