Deep Fake is a term used to describe a video or audio manipulation technique that uses machine learning to generate or alter images or recordings so that they appear real. This technique can be used to add or replace elements in a video or image or to change someone’s voice or movements in an audio or video recording. It can be very convenient for some online games, just like the ones you can find on PlayAmo login.
The Deep Fake is often used to create humorous videos or for the creation of entertainment content, but it can also be used in malicious ways, such as spreading false information or spreading misinformation. Because of these potential risks, there has been a public debate about the need to regulate or limit the use of this technology.
Who invented the Deep Fake?
The term “Deep Fake” was popularized in 2017 by a Reddit user by the name of “deepfakes”, who created a series of Deep Fake videos featuring celebrities in porn movies. While this use of Deep Fake has caused a lot of controversies and led to a ban on Reddit from creating such content, it has also drawn attention to this image and video editing technique using machine learning.
However, Deep Fake’s technology itself was not invented by “deepfakes” or any other particular person. It relies on image processing and machine learning techniques that have been developed over many years and have been implemented in many different contexts. The term “Deep Fake” itself is a combination of “deep learning” and “fake” and refers to the use of deep machine learning to generate images or videos that are very close to the original but have been modified to include a different person or object.
How does Deep Fake work?
Deep Fake works by using deep machine learning algorithms to analyze and understand the characteristics of the original image or video. The algorithm then uses this information to generate new images that are very close to the original but contain a different person or object.
To create a Deep Fake, you must first collect a large number of images or videos of a person or an object, which will serve as the basis for learning the algorithm. These images are then used to train a neural network model that is able to convincingly reproduce the characteristics of the original image.
Once the model is trained, it can be used to replace or mask a person or object in an image or video using the characteristics of the original to generate a new image or video that is very close to the original. The end result is an image or video that appears to be authentic but has been altered to include a different person or object.
Where to start to make a Deep Fake?
To create a Deep Fake, you will need:
- Collect a large number of images or videos of the person or object you want to use to train your model. The more sources you have, the better.
- Choose Deep Fake creation software or tool. There are several options available online, including free and paid software.
- Learn to use the software or tool you have chosen. This may require following tutorials or reading online documentation.
- Train your model using the images or videos you have collected. This may take some time, especially if you are using a large number of sources or using a low-powered computer.
- Use your trained model to generate new images or videos that include the person or object of your choice. You may need to adjust your model settings to get the desired results.
- It is important to note that creating Deep Fake can be complex and requires knowledge of programming and machine learning. If you don’t have these skills, it can be difficult to create a quality Deep Fake. It is also important to note that using Deep Fake for malicious purposes is illegal in many places and can lead to serious legal consequences.
There are several software and tools that allow you to create Deep Fakes. Here are some examples :
- Reface: Formerly called Doublicat; the Reface application allows you to change the face in your photos. This app uses AI to transform your face and swap it with that of celebrities. Have you always wanted to look like your favorite superhero, TV star, or celebrity?
- Wombo: Wombo is a Canadian image manipulation mobile app launched in 2021 that uses a provided selfie to create a deepfake of a person lip-synced to one of the various songs.
- FaceApp: FaceApp is one of the best AI photo editing mobile apps. Turn your selfie into a model portrait with one of the most popular apps, with over 500 million downloads to date. FaceApp gives you everything you need to create perfect Instagram photos for free. No more pressing the screen all the time!
- Faceswap: Face Swap Live is a mobile application created by Laan Labs that allows users to swap faces with another person in real-time using the device’s camera
- FaceMagic: FaceMagic allows users to alter their appearance using filters and virtual makeup effects. It also offers photo editing tools such as removing wrinkles and blemishes, as well as the ability to change hair color and virtually apply makeup to your face.
- Deepfakes Web: Deepfakesweb.com is an online service for creating Deep Fake videos. It uses machine learning to absorb the different complexities of face data. According to the website, it can take up to 4 hours to learn and train the video and images and around 30 minutes to swap faces using the trained model. The service is paid and offers a free version which takes around 5 hours to produce the Deep Fake video and a premium version which produces it in an hour. Deepfakesweb.com uses powerful GPUs in the cloud to render data, but the rendering process can still take several hours.
- Hoodem: Hoodem is an online Deep Fake video creation service. It allows users to create Deep Fake videos from their computer, using their webcam and a microphone. The video creation process is described as quick and easy, and the service offers a variety of customization options for creating Deep Fake videos.
It is important to note that using these tools for malicious purposes is illegal in many places and can lead to serious legal consequences. Also, the quality of the results obtained with these tools can vary greatly, and you may need a lot of trial and error to get satisfactory results.