Create Your Own DFM Model with Deep Face Lab 2.0

Table of Contents

1. Introduction
2. Setting Up Deep Face Lab 2.0
   1. Downloading and Extracting Deep Face Lab 2.0
   2. Organizing the Workspace
   3. Preparing the Source Data
   4. Preparing the Destination Data
3. Running Deep Face Lab 2.0
   1. Choosing Extraction Method
   2. Sorting Data Source
   3. Sorting Data Destination
4. Training Your Model
   1. Choosing a Pre-Trained Model
   2. Configuring the Training Settings
   3. Starting the Training Process
5. Exporting Your Model
6. Conclusion

Introduction

In this Tutorial, we will learn how to use Deep Face Lab 2.0 to create a customized deepfake model. Deep Face Lab is a powerful tool that allows you to swap faces in videos and images using deep learning techniques. By following the step-by-step instructions in this guide, you will be able to set up Deep Face Lab, prepare your source and destination data, run the application, train your model, and export the final result.

Setting Up Deep Face Lab 2.0

Downloading and Extracting Deep Face Lab 2.0

To begin, you need to download and extract the Deep Face Lab 2.0 software. Make sure you have a reliable internet connection and enough disk space to accommodate the application.

Organizing the Workspace

After successfully downloading and extracting Deep Face Lab 2.0, navigate to the workplace folder in the extracted main folder. Create three folders: data SRC, data DST, and model folder. These folders will be used to store your source data, destination data, and trained models, respectively.

Preparing the Source Data

The source data is the picture of the person whose face you want to use as a mask. It is recommended to use multiple pictures with different expressions and angles to achieve better results. Paste these pictures in the data SRC folder and rename them in a series of numbers starting from 401. For example, the Second picture should be named "402" and so on.

Preparing the Destination Data

The destination data is the pictures or videos where you want to replace the face. Similar to the source data, paste these pictures or videos in the data DST folder and rename them in the same manner as the source data, starting from four zeros and one.

Running Deep Face Lab 2.0

Choosing Extraction Method

When you run Deep Face Lab 2.0, you will see a list of commands in the extracted folder. Skip the first three commands if you are using pictures. On command number four, choose either manual facets extract from SRC or autofacets extract. It is recommended to use the auto extraction option for convenience.

Sorting Data Source

Once you have chosen the extraction method, a command Prompt window will open. Choose the appropriate settings for your system, such as CPU or GPU, and adjust the quality to 100 for the best results. The extraction process will start and may take a few minutes. Do not cancel or restart the process, even if your computer freezes.

Sorting Data Destination

After the data source is sorted, click on the 5.2 data DST sort command. This will open a new command prompt window. Choose the same settings you used for sorting the data source. The sorting process may take a few minutes to complete.

Training Your Model

Choosing a Pre-Trained Model

To train your model, you have the option to choose from pre-trained models available from the link provided in the description. Visit the link and select a model that suits your requirements.

Configuring the Training Settings

Once you have chosen a model, click on the sahi train command. Fill in the required settings as listed in the instructions. If you already have a pre-existing model, you can provide its name. Otherwise, create a new model by filling in the settings. This process may take a few minutes to start.

Starting the Training Process

After configuring the training settings, a new command prompt window will open. Wait for the training process to start. Depending on the complexity of the model and the amount of data, the training process may take several days. During training, you can press the space button to view the next frames. Once you are satisfied with the training results, press Enter to save the process and close the window.

Exporting Your Model

Click on the export sajeev as dfm command. Another prompt window will open. Specify the name of the model you want to save and convert it to dfm format. The conversion process will start, and once it is done, the model will be saved in the workplace model folder.

Conclusion

Congratulations! You have successfully learned how to use Deep Face Lab 2.0 to create a customized deepfake model. With the knowledge gained from this tutorial, you can now experiment with different source data and destinations to create realistic face swaps in videos and images. Remember to use this technology responsibly and ethically.

Highlights

• Learn how to use Deep Face Lab 2.0 to create deepfake models
• Set up the workspace and organize the data
• Choose the appropriate extraction method for your project
• Train your model using pre-defined settings
• Export and save your customized deepfake model

FAQ

Q: Can I use Deep Face Lab 2.0 for commercial purposes? A: Deep Face Lab 2.0 is an open-source project, and its usage for commercial purposes may have legal implications. It is advisable to consult with legal professionals before using it in a commercial context.

Q: How long does the training process take? A: The duration of the training process depends on various factors such as the complexity of the model and the amount of data. It can take several days to train a model with satisfactory results.

Q: Is Deep Face Lab 2.0 difficult to use for beginners? A: Deep Face Lab 2.0 has a learning curve, especially for beginners. However, by following this tutorial and exploring the available documentation and resources, you can quickly get started with creating deepfake models.