DEEPFAKE Tutorial: A Beginners Guide (using DeepFace Lab)

Cinecom.net
10 Dec 201911:54

TLDRIn this tutorial, Jordy from Cinecom.net explores the world of deepfakes using DeepFace Lab, a powerful tool for face swapping. He shares a step-by-step guide on how to create a deepfake video, from selecting the right scenes and gathering face data to installing the software and training the AI. The video highlights the importance of high-quality source material and the potential of using powerful hardware like the MSI P100 for efficient processing. Tips on enhancing the final result with video editing software are also provided, showcasing the impressive capabilities of deepfake technology.

Takeaways

  • 🖥️ The tutorial is sponsored by MSI and features their P100 desktop series and PS341WU monitor.
  • 🎬 The video discusses creating deepfakes, using the example of a Christmas video featuring faces swapped with characters from 'Home Alone'.
  • 👤 The importance of gathering high-quality face data from celebrities or self-recorded footage for deepfaking is emphasized.
  • 📹 A recommendation is made to film oneself for about 20 minutes, mimicking the expressions of the character whose face is to be replaced.
  • 💻 Deep Face Lab software is introduced as the tool for creating deepfakes, with instructions on installation and setup.
  • 🔍 The process of extracting images from videos and cleaning up the extracted faces for better deepfake results is explained.
  • 🤖 The tutorial covers AI training for deepfakes, highlighting the trial-and-error nature and the impact of hardware on processing time.
  • 💾 The necessity of performing iterations during the AI training phase to achieve a realistic deepfake is discussed.
  • 🖼️ Post-processing options like color correction and mask feathering in video editing software are suggested for refining deepfake results.
  • 🔗 Links to resources for further learning and to the work of VFXChris, a specialist in deepfakes, are provided in the video description.

Q & A

  • What is the main focus of the tutorial video?

    -The main focus of the tutorial video is to provide a beginner's guide to creating deepfakes using DeepFace Lab software.

  • What type of computer hardware is recommended for deepfake tasks?

    -The video recommends a computer with a powerful GPU, such as the NVIDIA RTX 2080Ti, a high-end Intel i9 CPU, and up to 64GB of memory for deepfake tasks.

  • Why is the MSI P100 desktop series highlighted in the video?

    -The MSI P100 desktop series is highlighted because it is specifically built for creative tasks and has the necessary internal hardware to handle deepfake software efficiently.

  • What is the purpose of the Prestige monitor PS341WU mentioned in the video?

    -The Prestige monitor PS341WU is mentioned for its color accuracy and 5k resolution, which is ideal for editing 4k videos on a single monitor.

  • How long should the video clips be for deepfake training?

    -The video clips for deepfake training should ideally be around 20 minutes long, containing as many facial expressions from as many angles as possible.

  • What is the significance of having high-quality video for deepfake training?

    -High-quality video is significant for deepfake training because it ensures that the AI can accurately learn and replicate facial expressions without distortions or obstructions.

  • Why is it important to cover up other faces in the video when using a single celebrity's face for deepfake?

    -Covering up other faces in the video is important to ensure that the source data is clean and focused on the specific face being used for the deepfake, improving the final result.

  • What does FPS stand for in the context of this tutorial, and why is it important?

    -FPS stands for frames per second. It is important because selecting an appropriate FPS helps balance the amount of data provided to the AI without slowing down the process unnecessarily.

  • What is the role of manual cleanup of extracted faces in the deepfake process?

    -Manual cleanup of extracted faces is crucial to remove blurred or incorrect facial data, ensuring that the AI training uses only the cleanest and most accurate facial images.

  • What does SAE stand for in the context of the deepfake training, and why is it chosen?

    -SAE stands for 'Shallow Appearance Embedding'. It is chosen for deepfake training because it provides great results, although it may require more computer resources and time.

  • How can the final deepfake video be further enhanced after the initial training and conversion?

    -The final deepfake video can be further enhanced by doing a final conversion to 'Lossless+Alpha' and then tweaking the face in a video editor like After Effects for color correction, mask adjustments, and other enhancements.

Outlines

00:00

🖥️ Introduction to MSI P100 and Deepfake Tutorial

The video is sponsored by MSI and features the P100 desktop series, which the presenter is excited to use for editing at home. The presenter has set up a home office with a new desk, chair, and lights to complement the powerful and aesthetically pleasing computer. The video also introduces the MSI PS341WU monitor, which is ideal for editing 4K videos due to its 5K resolution and color accuracy. The tutorial focuses on deepfake technology, explaining its capabilities beyond face swapping. The presenter discusses a Christmas video project featuring deepfake technology applied to characters from 'Home Alone' and credits Chris, a deepfake specialist, for his assistance and expertise. The tutorial will guide viewers through the process of creating a deepfake, starting with selecting a scene and gathering face data.

05:02

🎥 Deepfake Process and Hardware Requirements

The tutorial explains the deepfake process, emphasizing the importance of high-quality source data with clear facial expressions from multiple angles. It details the steps for preparing the workspace, including clearing previous data, exporting videos, and extracting images from the source and destination clips. The presenter discusses different face extraction methods and the necessity of manually cleaning up extracted faces for optimal results. The video then delves into the training phase, where AI learns to match facial features. It mentions the importance of computer resources, particularly video memory, and highlights the MSI P100's powerful GPU and other specifications that make it suitable for deepfake tasks. The presenter also touches on the cooling system's effectiveness during intensive deepfake software operation.

10:04

🔧 Finalizing Deepfake and Post-Processing Tips

The video concludes with the final steps of the deepfake process, including training settings, converting the AI's learning into a video, and exporting the final movie file. It advises on adjusting training settings like batch size and gradient clipping for stability. The presenter suggests running the training for at least 150,000 iterations for the best results and mentions that once the training is complete, the data is stored as a model, allowing for easy adjustments in the future. A bonus tip is provided on doing a final conversion to 'Lossless+Alpha' for further tweaking in video editing software like After Effects. The video ends with a comparison of the deepfake result with and without post-processing, showcasing the potential for enhancement. The presenter thanks MSI for their support and encourages viewers to stay creative.

Mindmap

Keywords

💡Deepfake

Deepfake refers to a technology that uses artificial intelligence, particularly deep learning, to create realistic but fake images, videos, or audio of a person. In the context of the video, deepfake is used to swap faces in a video, replacing the original person's face with another's. This is done by training AI on a large dataset of facial images to learn the nuances of a person's face and then applying this knowledge to generate a new video where the face has been replaced.

💡Faceswap

Faceswap is a technique that involves replacing one person's face with another's in a video or image. It is a precursor to deepfake technology, often using simpler image processing techniques. The video script mentions that deepfake is an advanced form of faceswap, indicating that it goes beyond basic image swapping to create more realistic and seamless face replacements.

💡DeepFaceLab

DeepFaceLab is a software tool used for creating deepfakes. It is one of the programs mentioned in the video script as a primary tool for the deepfake process. The software utilizes AI to analyze and generate high-quality face swaps. The tutorial emphasizes using DeepFaceLab over other alternatives like Faceswap due to its advanced capabilities.

💡FPS (Frames Per Second)

Frames Per Second (FPS) is a measure of the number of individual frames that make up a second of video. In the video script, the FPS is discussed in relation to extracting frames from a video for deepfake processing. The script suggests choosing a lower FPS, like 7 or 8, to avoid overwhelming the AI with too much data, which could slow down the process without significantly improving results.

💡CUDA

CUDA (Compute Unified Device Architecture) is a parallel computing platform and application programming interface (API) model created by NVIDIA. It allows software developers to use NVIDIA GPUs for general purpose processing. In the context of the video, CUDA is mentioned as a build option for DeepFaceLab, which is recommended for users with NVIDIA graphics cards to optimize the deepfake processing.

💡Batch Files

Batch files are scripts in an operating system that execute a series of commands. In the video script, batch files are used to automate the deepfake process, with each batch file corresponding to a different step in the process. They are numbered from 1 to 10, guiding users through the deepfake creation workflow.

💡Source Data

Source data in the context of the video refers to the video or images that provide the facial data for the deepfake process. It is the original dataset that the AI learns from to understand the facial features and expressions that will be swapped onto another person in the video. The script emphasizes the importance of high-quality source data for better deepfake results.

💡Destination Video

The destination video is the video into which the AI will place the new face generated from the source data. In the script, the destination video is the target where the faceswap will occur, and it is crucial to prepare this video by ensuring that the face to be replaced is clearly visible and unobstructed.

💡Training (AI)

Training in AI refers to the process of feeding data into a machine learning model so that it can learn patterns and make predictions or generate outputs. In the video, training is a critical step in the deepfake process where the AI learns the facial features and expressions from the source data to apply them to the destination video.

💡Iterations

In the context of AI and machine learning, iterations refer to the number of times the learning algorithm processes the data. The video script mentions that ideally, there should be at least 150,000 iterations for the AI to effectively learn and generate a convincing deepfake. More iterations allow the AI to study the face more thoroughly, leading to better results.

💡Lossless+Alpha

Lossless+Alpha refers to a video file format that retains the highest quality of the original video data and includes transparency information (alpha channel). In the video script, a final conversion to 'Lossless+Alpha' is suggested for further editing in a video editor like After Effects. This allows for detailed adjustments to the deepfake, such as color correction and mask feathering, to refine the final result.

Highlights

MSI's P100 desktop series is introduced as a powerful tool for video editing and deepfake creation.

The P100's internal hardware is described as 'insane', specifically built for creative tasks.

MSI's PS341WU monitor is praised for its color accuracy and 5k resolution, ideal for 4k video editing.

Deepfake technology is introduced as an advanced form of faceswap with broader applications.

A Christmas video project is mentioned, featuring faces swapped onto characters from 'Home Alone'.

Expert advice from Chris, a deepfake specialist, is highlighted for enhancing the tutorial's credibility.

The importance of high-quality video and clear facial data for deepfake success is emphasized.

The tutorial suggests filming oneself for 20 minutes to mimic expressions of on-screen characters.

Deep Face Lab is chosen over Faceswap for the deepfake software demonstration.

Instructions for installing and setting up Deep Face Lab are provided in detail.

The tutorial explains the process of extracting images from source videos at a specific frame rate.

Manual cleanup of extracted faces is recommended for optimal deepfake results.

Various training methods for deepfake AI are discussed, with a focus on SAE for its quality.

The MSI P100's powerful GPU and CPU are touted as ideal for deepfake processing.

The 'Creator Center' software by MSI is mentioned for optimizing system performance.

The tutorial covers the deepfake training process, including settings and potential AI learning iterations.

A bonus tip on final conversion to 'Lossless+Alpha' for further video editing flexibility is provided.

The final results of the deepfake process are showcased, comparing unedited and tweaked versions.

The tutorial concludes with a call to action for viewers to stay creative and explore deepfake technology further.

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