Master the Art of Deepfake Masking with X-EGG | DeepFaceLab 2.0 Xseg Tutorial
- Introduction
- What is X-EGG?
- Applying Pre-Trained Masks
- Understanding Masking Terminology
- Creating Your Own X-SIG Mask
- Labeling Faces with Mask Polygons
- Modifying the Polygon
- Dealing with Obstructions
- Training the X-SEG Model
- Setting Up the Training Process
- Monitoring the Training Progress
- Applying the Trained Mask
- Checking the Applied Mask
- Adjusting the Applied Mask
- Conclusion
Welcome to the Deep Face Lab 2.0 X-EGG masking Tutorial! In this video, I'll show you how to use the X-EGG editor to draw masks on your face and train the model for seamless face swaps. We'll also cover how to deal with obstructions, make backups, and use pre-trained masks to speed up the process. So let's dive in!
If you've watched my previous tutorial on face-set extraction, you'll know that each face includes a default mask generated during extraction. Deep Face Lab includes a powerful masking tool called X-EGG, which allows you to specify the area of the image that represents the face or the background. Using X-EGG results in better composition, increased likeness to the source face set, more realistic eye and mouth movement, and better skin detail and color. It also enables you to exclude obstructions such as hands, hair, glasses, piercings, tattoos, and more.
To get started quickly, you can apply a pre-trained mask to your face set. Deep Face Lab includes a generic whole-face X-SEGMENT mask, which you can easily apply by running the appropriate file. This generic mask serves as a good starting point for many projects. However, extreme angles and heavily obstructed or blurry faces may require a custom mask for better results. In this guide, I will walk you through creating and applying your own masks.
Before we dive into creating masks, it's important to familiarize yourself with some basic terminology. The process of drawing masks is called labeling, and the lines and points that define the mask are called polygons. You can edit, fetch, or remove these polygons from the images. After labeling the faces, you'll have the trained mask, which is a model produced by the X-EGG trainer. This mask is embedded in the face image and used during model training. Finally, we have the learned mask, which is created as part of the deep fake model and used during the final merging process.
To create your own X-SIG mask, you'll first need to label some faces with mask polygons and then train the X-SEG model. Open the X-SEG editor by running the appropriate file, and you'll be greeted with the user interface. The main canvas displays the current image, and you can label the polygons along the face's edges using the drawing modes. The left-HAND side of the interface provides you with the necessary tools for drawing and manipulating polygons.
To label a face, start by placing points along the edge of the face using the left mouse button. Zoom in and out using the mouse scroll wheel, and use Ctrl+Z to undo points. Continue following the edge of the face and hairline until you've created a mask around the entire face. You can modify the polygon by moving, adding, or deleting points.
For larger face types, such as whole face or head, you'll need to include the entire face, ears, hair, and optionally part of the neck. Keep in mind that thin or moving hair may require further refinement in post-processing. Aim for a consistent mask Shape by following a similar path around the jaw and hairline in each image. It's not necessary to create an extremely precise mask with hundreds of points; a few dozen points will suffice.
Remember to label a variety of faces throughout the face set, including different facial expressions, yaw, pitch, and color ranges. Once you've labeled multiple faces, use the sorting tool to reorder the images and ensure a good spread of labeled faces in the face set.
Obstructions in front of the face, such as hands or glasses, need to be excluded from the mask area. There are two methods to achieve this: drawing the polygon around the face and the obstruction itself or drawing a polygon around the face and another polygon in exclusion mode around the obstruction object. The latter method removes any part of the obstruction that intersects with or is inside the face polygon.
When using the exclusion mode, make sure to draw an occlusion mask around the face as well. Do not label a face with only an exclusion mask. It's important to label obstructions on a variety of frames. Any changes you make to the shape of the mask will affect the training and merging of the deep fake face.
After labeling the faces and creating the mask polygons, the next step is to train the X-SEG model. Run the appropriate file and choose a hardware device from the list. Set the face type to match your face set and select the desired batch size. The training progress will be displayed in the command window, along with the images and masks being trained in the preview window. You can cycle through the different previews using the space bar and generate the current preview using the p key. The trainer will attempt to match the labels to the face set, gradually improving the mask's shape and consistency.
It's recommended to save the training progress at regular intervals or when you're satisfied with the results. Once the mask has been trained, it can be used to apply the mask to the face set images.
To apply the trained mask, run the appropriate file and select the device to use. If you have multiple GPUs, you can apply the mask to the source face set simultaneously. Otherwise, apply the source mask afterward using the corresponding file. After applying the masks, it's recommended to check the applied mask for any adjustments required.
Open the X-EGG editor and toggle the applied mask using the backtick key. You can scroll through the images using the a and d keys and create new face labels where needed. Repeat the process of training, applying, and adjusting the masks until the applied mask is relatively clean. Remember that it doesn't have to be perfect, as it will be further trained in the deep fake trainer.
If needed, you can remove the applied mask and revert to the default mask using the appropriate file. This will not affect the polygon labels you have drawn, only the applied mask itself.
In conclusion, mastering the X-EGG masking tool is crucial for achieving high-quality deep fakes. By understanding the terminology, creating accurate masks, and training the X-SEG model, you can seamlessly merge faces and create realistic results. Remember to experiment with different face types, label a variety of expressions, and adjust the masks as needed. With practice, you'll be able to harness the power of X-EGG to create stunning deep fakes.
- Learn how to use X-EGG editor for masking in Deep Face Lab 2.0.
- Apply pre-trained masks or create custom masks for seamless face swaps.
- Understand the essential terminology for effective masking.
- Label faces with mask polygons and modify the polygons as needed.
- Deal with obstructions in front of the face by excluding them from the mask area.
- Train the X-SEG model to improve the quality of the mask.
- Apply the trained mask to the face set images and make adjustments if necessary.
- Achieve high-quality deep fakes by mastering the X-EGG masking tool.
Q: Can I use pre-trained masks for all face types?A: While pre-trained masks, such as the generic whole-face X-SEGMENT, are a good starting point for many projects, larger face types or extreme angles may require custom masks for better results.
Q: How many points should I use to create a mask?A: It's not necessary to create an extremely precise mask with hundreds of points. A few dozen points will suffice for most cases.
Q: Can I remove the applied mask and revert to the default mask?A: Yes, you can remove the applied mask using the appropriate file. This will not affect the polygon labels you have drawn.
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