DeepFaceLab | DeepFaceLab is the leading software for creating deepfakes | Machine Learning library

by iperov Python Version: DF.wf.288res.384.92.72.22 License: GPL-3.0

X-Ray Key Features Code Snippets(3)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | DeepFaceLab Summary

DeepFaceLab is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow, OpenCV applications. DeepFaceLab has no vulnerabilities, it has a Strong Copyleft License and it has medium support. However DeepFaceLab has 10 bugs and it build file is not available. You can download it from GitHub.

DeepFaceLab is the leading software for creating deepfakes.

Support

Quality

Security

License

Reuse

Support

DeepFaceLab has a medium active ecosystem.

It has 40567 star(s) with 9051 fork(s). There are 1064 watchers for this library.

It had no major release in the last 12 months.

There are 509 open issues and 781 have been closed. On average issues are closed in 501 days. There are 4 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of DeepFaceLab is DF.wf.288res.384.92.72.22

Quality

DeepFaceLab has 10 bugs (9 blocker, 0 critical, 1 major, 0 minor) and 530 code smells.

Security

DeepFaceLab has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

DeepFaceLab code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

DeepFaceLab is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

DeepFaceLab releases are available to install and integrate.

DeepFaceLab has no build file. You will be need to create the build yourself to build the component from source.

DeepFaceLab saves you 6841 person hours of effort in developing the same functionality from scratch.

It has 14185 lines of code, 1032 functions and 125 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed DeepFaceLab and discovered the below as its top functions. This is intended to give you an instant insight into DeepFaceLab implemented functionality, and help decide if they suit your requirements.

Process a set of samples
Resize x
Estimate the pitch roll
Read a cv2 image from a file
Processes all messages in the loop
Show the game
Set the image
Build a checkerboard grid
Generate a summary of the layers
Called when a preview is received
Evaluate 68 landmarks
Ask the user for a list of device indices
Export the model
A bilinear sampling
Preview preview
Ask user for settings
Tries to loop through c2s
Forward convolutional
Start the process
Generate a mask from an image
Generate a batch function
Batch function
This function is used for testing
Takes a directory and runs tests
Apply XSeg model
Pack a set of faces

Get all kandi verified functions for this library.

DeepFaceLab Key Features

No Key Features are available at this moment for DeepFaceLab.

DeepFaceLab Examples and Code Snippets

Install requirements,Manual method

Shell

Lines of Code : 12

License : Strong Copyleft (GPL-3.0)

Copy

yum -y install epel-release http://li.nux.ro/download/nux/dextop/el7/x86_64/nux-dextop-release-0-5.el7.nux.noarch.rpm
wget -O /etc/yum.repos.d/cuda.repo https://developer.download.nvidia.com/compute/cuda/repos/rhel7/x86_64/cuda-rhel7.repo
yum -y upda

Post-install check

Shell

Lines of Code : 2

License : Strong Copyleft (GPL-3.0)

Copy

cd ~/DeepFaceLab/scripts
./1_clear_workspace.sh

Install requirements,Scripted method

Shell

Lines of Code : 1

License : Strong Copyleft (GPL-3.0)

Copy

sudo setup.bash

Community Discussions

Trending Discussions on DeepFaceLab

DeepFaceLab_NVIDIA outputs an error during the 'data_src faceset extract' - TensorFlow

QUESTION

DeepFaceLab_NVIDIA outputs an error during the 'data_src faceset extract' - TensorFlow

Asked 2021-Mar-09 at 22:15

In the DeepFaceLab the 4th and/or 5th process which is extracting the faceset from the data_src and/or data_dst outputs this error:

...

ANSWER

Answered 2021-Feb-16 at 06:19

So after a long time, I finally found the fix. Since I know the training will take a very long time I decided to do this on a laptop that had no GPU. For this very reason, the fix was to do the 10th step first or the cmd file named 10)Make CPU only. Doing so will uninstall the preinstalled TensorFlow and download an older version so an Internet Connection will be required. Additionally, executing it cannot be undone, this means DeepFaceLab will now run through CPU only 4ever unless you reinstall it again.

This should hopefully solve the problem.

Source https://stackoverflow.com/questions/65529897

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install DeepFaceLab

You can download it from GitHub.
You can use DeepFaceLab like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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