Better Face Swap = FaceDetailer + InstantID + IP-Adapter (ComfyUI Tutorial)
TLDRIn this video, the host, Way, addresses a common issue with face swapping in Confy UI using Instant ID. The typical problem is that the generated image retains the same composition as the reference image, resulting in incomplete body images despite the prompt. To overcome this, Way introduces a workflow that allows for face swapping with any reference image. The process involves using SDXL to generate a portrait, feeding reference images into Instant ID and IP Adapter to capture detailed facial features. For the background, one can use an image from Midjourney or a personal photo. The video also covers the installation of necessary nodes and models, and provides tips on adjusting settings for better results. Additionally, Way discusses the use of IP Adapter to enhance the resemblance in face swaps and suggests training a ControlNet model for more accurate results. The host provides links to further resources and tutorials in the description for viewers interested in similar techniques.
Takeaways
- 😀 The issue with Instant ID in Confy UI is that face swaps tend to keep the same composition as the reference image.
- 📷 The author uses SDXL to generate a crisp portrait photo and then feeds reference images into Instant ID and IP Adapter for detailed facial features.
- 🌄 For the background of the face swap, one can use an image from Midjourney or a personal photo that aligns with the vision.
- 🔗 The complete workflow is linked in the description for viewers to follow.
- 🎨 The face swapping process involves using a node called Face Detailer, which is easy to paint and correct disfigured faces.
- 📚 An additional node is required to detect and segment the face region.
- 🤖 Instant ID node and model are necessary for the face swapping process, which works alongside ControlNet.
- 🔄 If the face swap appears overfitted, adjusting the CFG and step count can refine the result.
- 🔍 IP Adapter with Face ID can be used to boost the resemblance in the face swap.
- ⚙️ The IP adapter node can be tweaked to further fine-tune the face swap for better similarity.
- 🖌️ For small issues like ear or forehead adjustments, imp painting and tweaking settings in Face Detailer can be used.
- 📚 Training a model specifically for the project, such as with the mentioned tutorial, can significantly improve the likeness in face swaps.
Q & A
What is the common issue with instant ID in Confy UI when trying to do a face swap?
-The common issue is that it tends to keep the same composition as the reference image, resulting in a head or half-body image even when a full-body image is requested.
What is the first tool mentioned for generating a crisp portrait photo?
-The first tool mentioned is SDXL.
What are the two tools used to help pull out detailed facial features for a solid swap?
-The two tools used are Instant ID and IP Adapter.
What are the options for the background of the face swap?
-Options for the background include using an image from Midjourney or a photo taken by the user, depending on what fits their vision.
What is the purpose of the Face Detailer node?
-The Face Detailer node is used for painting and correcting disfigured faces, and it automatically recognizes the face area, eliminating the need to draw a face mask by hand.
What is the role of the Instant ID node divided by cubic?
-The Instant ID node divided by cubic is used to apply Instant ID, which helps in recognizing visual features and is a part of the face swapping process.
How can the overfitting issue in face swapping be addressed?
-Overfitting can be addressed by adjusting the CFG slightly, increasing the step count for more refinement, and using the IP adapter to boost the resemblance.
What is the purpose of the IP adapter in the face swapping process?
-The IP adapter is used to enhance the resemblance in the face swap by automatically configuring the best version of Face ID for the task.
What is the significance of training a model specifically for a project in face swapping?
-Training a model specifically for a project can significantly boost the likeness in face swaps, leading to a more accurate and personalized result.
How can the user ensure smooth node connections in the workflow?
-The user can ensure smooth node connections by hitting the 'Q prompt' button to check for any issues in the connections between nodes.
What is the recommended action if the face swap with Instant ID and the IP adapter isn't hitting the mark on similarity?
-If the face swap isn't quite right, the user can adjust the weights in both Instant ID and the IP adapter, or use impainting and tweaking settings inside Face Detailer for fine-tuning.
What additional resource is provided for further enhancing face changes in Confy UI?
-The tutorial provides a link to another tutorial on how to train a model specifically for the project, which can be integrated into Confy UI to enhance face changes.
Outlines
😀 Introduction to Face Swapping with Instant ID
The video begins with the host introducing themselves and the topic of the day, which is addressing a common issue with instant ID in confy UI, particularly when attempting face swaps. The host explains that instant ID tends to maintain the same composition as the reference image, which can be limiting when trying to create full-body images from headshots. To overcome this, the host shares a workflow that allows for swapping faces in photos with any reference image desired. The video outlines the use of tools like sdxl for generating portrait photos and instant ID and IP adapter for detailed facial features. It also discusses selecting a background for the face swap and provides a link to the workflow in the description for further details.
🛠️ Setting Up the Workflow for Face Swapping
The host dives into the technical setup for face swapping using sdxl and instant ID. They explain the need for efficiency nodes and guide viewers through loading up SD XLS, connecting it with the key sampler for sdxl, and generating a photo. The face swapping process involves using a 'face detailer' node, which is easy to use and automatically recognizes the face area, eliminating the need for manual face mask drawing. The host also emphasizes the importance of installing the impact pack node package and setting up a node that detects and segments the face region. They provide a link to another video for more details on using the face detailer. The video continues with instructions on integrating instant ID into the workflow, adjusting settings to refine the face swap, and using the IP adapter to enhance the resemblance of the swapped face. The host also suggests tweaking the weights in instant ID and the IP adapter for further fine-tuning and addresses potential issues like ear or forehead discrepancies with inpainting techniques.
🔄 Enhancing Similarity with Training and Final Thoughts
The host discusses an advanced strategy for improving the similarity in face swaps by training a model specifically for the project. They mention a tutorial on this topic and provide a link to it in the description. The video concludes with the host thanking viewers for watching, encouraging them to like and follow for more updates, and teasing the next video in the series.
Mindmap
Keywords
💡Face Swap
💡Instant ID
💡IP-Adapter
💡Confy UI
💡SDXL
💡Efficiency Nodes
💡Face Detailer
💡Control Net
💡Unified Loader
💡CFG
💡IMP Painting
Highlights
The video discusses a common issue with instant ID in Confy UI when attempting face swaps, where the composition often matches the reference image.
A workflow is introduced to swap faces in photos with any reference image desired.
SDXL is used to generate a crisp portrait photo for the face swap.
Instant ID and IP Adapter are utilized to extract detailed facial features necessary for a solid swap.
For the background of the face swap, one can use an image from Midjourney or a personal photo.
Efficiency nodes must be installed in the Conf manager for the workflow.
The video demonstrates how to connect nodes for face swapping using Face Detailer.
Face Detailer is useful for painting and correcting disfigured faces and automatically recognizes the face area.
The Impact Pack node package is required for Face Detailer and should be installed in the config manager.
Instant ID node divided by Cubic and the Instant ID model are needed for the process.
ControlNet model is also required to work alongside Instant ID.
CFG and step count adjustments can help refine the face swap to avoid overfitting.
IP Adapter with Face ID can be used to boost the resemblance in the face swap.
Unified loader and model input/output connections are crucial for the IP Adapter setup.
Adjustments in the IP Adapter node can further fine-tune the face swap similarity.
Imp painting and tweaking settings in Face Detailer can address minor issues in the face swap.
Training a custom model with Laura for specific projects can significantly improve the likeness in face swaps.
The video provides links to additional tutorials on using similar techniques and training custom models.
The tutorial concludes with a reminder to like and follow for more updates.