Deepfake Software Mac

Deepfake Software Mac
Deep Fake Software For Mac
Deepfacelab
Deepfacelab Download

Oct 25th, 2019 by DFBlue

We will use DeepFaceLab to create the deepfakes. Another software, FaceSwap is also available, and will have a separate tutorial. Join us now Deepfakes or DF, a portmanteau of 'deep learning or DL' and 'fake', is an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos. Makes video using our app.

Join us now Deepfakes or DF, a portmanteau of 'deep learning or DL' and 'fake', is an artificial intelligence-based human image synthesis technique. It is used to combine and superimpose existing images and videos onto source images or videos. Makes video using our app.
DeepFaceLab is a pioneering deepfake software. You can go to GitHub for deepfake app download. The open-source deepfake system is made for replacing the face, de-aging face, replacing head, and manipulating lips.

tutorial
guide
how to
deepfacelab
deepfakes

👀 Update 10/25/19: Added instructions for the new SAEHD model (amazing)

👽 Update 9/24/19: New post for AVATAR mode

Source and destination videos requirements

High resolution (4k webm is best, lower than 1080p is not recommended)
Faces not too far from camera and unobstructed
Multiple angles, facial expressions
Brightly and evenly lit
Faces should somewhat match (beard, hat, hair, skin color, shape, glasses)
Need at least 2 mins of good quality video, interview videos work well

Downloading the software

We will use DeepFaceLab to create the deepfakes. Another software, FaceSwap is also available, and will have a separate tutorial.

Download DeepFaceLab
- Make sure to pick the right build for your GPU. If you don’t have a GPU, use the CLSSE build
- Here’s the direct link
- In that folder, you will find some pre-compiled face-sets. Go ahead and download one of them to get started quickly (otherwise you will have to build your own face-set from videos / images)
The downloaded .exe will extract and install the program to the location of your choosing.
- A workspace folder will be created. This is the folder where all the action will happen.

Extracting faces from source video

Name the source video data_src and place it in the workspace folder.
- Most formats that ffmpeg supports will work
Run 2) extract images from video data_src
- Use PNG (better quality)
- FPS <= 10 that gets you at least 2000 images (4k-6k is ideal)
Run 4) data_src extract faces S3FD best GPU
- Extracted faces saved to data_srcaligned.
Run 4.2.2) data_src sort by similar histogram
- Groups similar detected faces together
Run 4.1) data_src check result
- Delete faces that are not the right person, super blurry, cut off, upside down or sideways, or obstructed
Run 4.2.other) data_src util add landmarks debug images
- New images with _debug suffix are created in data_src/aligned which allow you to see the detected facial landmarks
- Look for faces where landmarks are misaligned and delete the _debug and original images for those
- Once you’re done, delete all _debug images by using the search bar to filter for _debug
Run 4.2.6) data_src sort by final
- Choose a target image number around 90% of your total faces

Extracting faces from destination video

You may choose to either extract from (1) the final video clip you want, or (2) one that is cut to include only the face you want to swap. If you choose 1, you may have to spend more time cleaning the extracted faces. If you choose 2 you will have to edit back the final video (and audio) after the swap.

Name your final video data_dst and put it in the workspace folder
Run 3.2) extract PNG from video data_dst FULL FPS
Run 5) data_dst extract faces S3FD best GPU
Run 5.2) data_dst sort by similar histogram
Run 5.1) data_dst check results
- Delete all faces that are not the target face to swap, or are the target face but upside down or sideways. Every face that you leave in will be swapped in the final video.
Run 5.1) data_dst check results debug
- Delete any faces that are not correctly aligned or missing alignment, paying special attention to the jawline. We will manually align these frames in the next step.
Run 5) data_dst extract faces MANUAL RE-EXTRACT DELETED RESULTS DEBUG
- We run this step to manually align frames that we deleted in the last step. The manually aligned faces will be automatically extracted and used for converting. You must manually align frames you want converted (swapped) even if it’s a lot of work. If you fail to do so, your swap will use the original face for those frames.
- Manual alignment instructions:
  - For each face, move your cursor around until it aligns correctly onto the face
  - If it’s not aligning, use the mouse scroll wheel / zoom to change the size of the boxes
  - When alignment is correct, hit enter
  - Go back and forth with , and .. If you don’t want to align a frame just skip it with .
  - Mouse left click will lock/unlock landmarks. You can either lock it by clicking or hitting enter.

Training

Run 6) train SAEHD

For an NVIDIA GTX 1080 8gb GPU
Setting	Value	Notes
iterations	100000	Or until previews are sharp with eyes and teeth details.
resolution	128	Increasing resolution requires significant VRAM increase
face_type	f
learn_mask	y
optimizer_mode	2 or 3	Modes 2/3 place work on the gpu and system memory. For a 8gb card you can place on mode 3 and still most likely be able to do 160 res fakes with small batch size.
architecture	df
ae_dims	512	Reduce if less GPU memory (256)
ed_ch_dims	21	Reduce if less GPU memory
random_warp	y
trueface	n
face_style_power	0	Can enable if you want to morph src more to dst. But disable after 15k iterations.
bg_style_power	10	Turn off at 15k iterations. Styles on consume ~30% more vram so you will need to change batch size accordingly.
color_transfer	varies	Try all modes in the interactive converter
clipgrad	n
batch_size	8	Higher if you don't run out of memory
sort_by_yaw	n	No, unless you have very few src faces
random_flip	y

Optional: History timelapse

Before converting, you can make a timelapse of the preview history (if you saved it during training). Do this only if you understand what ffmpeg is.

Convert

Run 7) convert SAEHD

Use the interactive converter and memorize the shortcut keys, it will speed up the process a lot.

Setting	Value	Notes
interactive_converter	y	Definitely use the interactive converter since you can try out all the different settings before converting all the frames
mode	overlay
mask_mode	learned
erode_modifier	0-50	If src face is bleeding outside the edge of dst face increase this to 'erode' away the src face on the outside
blur_modifier	10-200	The more similar the face the lower you can set erode and blur and get great results.
motion_blur	0
color_transfer	ebs	Try all of them, can even use different ones for different scenes / lighting
sharpen_mode	box
sharpen_amount	1-3
super_resolution	RankSRGAN	Enhances detail, especially around the eyes
color_degrade_power	n
export_alpha_mask	n	Outputs transparent PNGs for use in post-production tools if you need it

While conversion is running, you can preview the final images data_dstmerged folder to make sure it’s correct. If it’s not, just close the convert window, delete /merged and start conversion again.
Run 8) converted to mp4
- Bitrate of 3-8 is sufficient for most

Done 🤡

Contributions by DFBlue, PlanetOfTheFakes

Follow us on Twitter @dfblue or Reddit u/deepfakeblue to keep up with everything that is going on in the world of deepfakes. Think Blue.

UPLOAD A VIDEO CONTAINING
THE FACE OF A PERSON (you or someone else)

UPLOAD A VIDEO
TO DEEPFAKE

ENJOY YOUR
MMASKED DEEPFAKE VIDEO !

Have you ever wanted to be someone else?
Better…. Have you ever wanted someone else to be someone else?

MMasked is the online deepfake video creator, which allows you to create a deepfake video of any subject doing anything you want (see example here). This subject being you, or this subject not being you.
By applying Deep Learning algorithms, MMasked allows you to transfer one person’s face from one video to another person’s body in another video. Examples of what types of faces this works for are: