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

 by   iperov Python Version: License: GPL-3.0

kandi X-RAY | DeepFaceLab Summary

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.

            kandi-support 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

            kandi-Quality Quality

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

            kandi-Security 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.

            kandi-License 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.

            kandi-Reuse 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
            Shelldot img1Lines of Code : 12dot img1License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            yum -y install epel-release
            wget -O /etc/yum.repos.d/cuda.repo
            yum -y upda  
            Post-install check
            Shelldot img2Lines of Code : 2dot img2License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            cd ~/DeepFaceLab/scripts
            Install requirements,Scripted method
            Shelldot img3Lines of Code : 1dot img3License : Strong Copyleft (GPL-3.0)
            copy iconCopy
            sudo setup.bash

            Community Discussions


            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:



            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.


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


            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.


            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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          • CLI

            gh repo clone iperov/DeepFaceLab

          • sshUrl


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