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Update INSTALL.md
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torzdf
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INSTALL.md
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INSTALL.md
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# Installing Faceswap
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- [Installing Faceswap](#Installing-Faceswap)
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# Installing faceswap
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- [Installing faceswap](#Installing-faceswap)
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- [Prerequisites](#Prerequisites)
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- [Hardware Requirements](#Hardware-Requirements)
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- [Supported operating systems](#Supported-operating-systems)
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@@ -14,14 +14,17 @@
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- [Anaconda](#Anaconda-1)
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- [Set up a virtual environment](#Set-up-a-virtual-environment)
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- [Entering your virtual environment](#Entering-your-virtual-environment)
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- [Faceswap](#Faceswap)
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- [faceswap](#faceswap)
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- [Easy install](#Easy-install)
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- [Manual install](#Manual-install)
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- [Running Faceswap](#Running-Faceswap)
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- [Running faceswap](#Running-faceswap)
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- [Create a desktop shortcut](#Create-a-desktop-shortcut)
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- [Updating faceswap](#Updating-faceswap)
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- [General Install Guide](#General-Install-Guide)
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- [Installing dependencies](#Installing-dependencies)
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- [Git](#Git-1)
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- [Python](#Python)
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- [Virtual Environment](#Virtual-Environment)
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- [Getting the faceswap code](#Getting-the-faceswap-code)
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- [Setup](#Setup-1)
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- [About some of the options](#About-some-of-the-options)
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@@ -66,11 +69,11 @@ The developers are also not responsible for any damage you might cause to your o
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## Installer
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Windows now has an installer which installs everything for you and creates a desktop shortcut to launch straight into the GUI. You can download the installer from https://github.com/deepfakes/faceswap/releases.
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If you have issues with the installer then read on for the more manual way to install Faceswap on Windows.
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If you have issues with the installer then read on for the more manual way to install faceswap on Windows.
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## Manual Install
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Setting up Faceswap can seem a little intimidating to new users, but it isn't that complicated, although a little time consuming. It is recommended to use Linux where possible as Windows will hog about 20% of your GPU Memory, making Faceswap run a little slower, however using Windows is perfectly fine and 100% supported.
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Setting up faceswap can seem a little intimidating to new users, but it isn't that complicated, although a little time consuming. It is recommended to use Linux where possible as Windows will hog about 20% of your GPU Memory, making faceswap run a little slower, however using Windows is perfectly fine and 100% supported.
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## Prerequisites
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@@ -101,9 +104,9 @@ To enter the virtual environment:
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- Hit the ">" arrow next to your faceswap environment and select "Open Terminal"
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### Faceswap
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### faceswap
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- If you are not already in your virtual environment follow [these steps](#entering-your-virtual-environment)
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- Get the Faceswap repo by typing: `git clone --depth 1 https://github.com/deepfakes/faceswap.git`
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- Get the faceswap repo by typing: `git clone --depth 1 https://github.com/deepfakes/faceswap.git`
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- Enter the faceswap folder: `cd faceswap`
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#### Easy install
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@@ -118,7 +121,7 @@ Do not follow these steps if the Easy Install above completed succesfully.
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- GPU Version: `conda install tensorflow-gpu`
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- Non GPU Version: `conda install tensorflow`
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## Running Faceswap
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## Running faceswap
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- If you are not already in your virtual environment follow [these steps](#entering-your-virtual-environment)
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- Enter the faceswap folder: `cd faceswap`
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- Enter the following to see the list of commands: `python faceswap.py -h` or enter `python faceswap.py gui` to launch the GUI
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@@ -135,7 +138,7 @@ A desktop shortcut can be added to easily launch straight into the faceswap GUI:
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## Updating faceswap
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It's good to keep faceswap up to date as new features are added and bugs are fixed. To do so:
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- If using the GUI you can go to the Tools Menu and select "Check for Updates...". This will update Faceswap to the latest code and update your dependencies.
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- If using the GUI you can go to the Tools Menu and select "Check for Updates...". This will update faceswap to the latest code and update your dependencies.
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- If you are not already in your virtual environment follow [these steps](#entering-your-virtual-environment)
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- Enter the faceswap folder: `cd faceswap`
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- Enter the following `git pull --all`
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# General Install Guide
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## Installing dependencies
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- Python >= 3.2-3.7 64-bit
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- apt/yum install python3 (Linux)
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- [Installer](https://www.python.org/downloads/release/python-368/) (Windows)
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- [brew](https://brew.sh/) install python3 (macOS)
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### Git
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Git is required for obtaining the code and keeping your codebase up to date.
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Obtain git for your distribution from the [git website](https://git-scm.com/downloads).
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### Python
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The recommended install method is to use a Conda3 Environment as this will handle the installation of Nvidia's CUDA and cuDNN straight into your Conda Environment.
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- [MiniConda3](https://docs.conda.io/en/latest/miniconda.html)
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Alternatively you can install Python (>= 3.2-3.7 64-bit) for your distribution (links below.) If you go down this route and are using an Nvidia GPU you should install CUDA (https://developer.nvidia.com/cuda-zone) and cuDNN (https://developer.nvidia.com/cudnn). for your system. If you do not plan to build Tensorflow yourself, make sure you install no higher than version 10.0 of CUDA and 7.5.x of CUDNN.
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- Python distributions:
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- apt/yum install python3 (Linux)
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- [Installer](https://www.python.org/downloads/release/python-368/) (Windows)
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- [brew](https://brew.sh/) install python3 (macOS)
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### Virtual Environment
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It is highly recommended that you setup faceswap inside a virtual environment. In fact we will not generally support installations that are not within a virtual environment as troubleshooting package conflicts can be next to impossible.
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If using Conda3 then setting up virtual environments is relatively straight forward. More information can be found at [Conda Docs](https://docs.conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html)
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If using a default Python distribution then [virtualenv](https://github.com/pypa/virtualenv) and [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io) may help when you are not using docker.
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- [virtualenv](https://github.com/pypa/virtualenv) and [virtualenvwrapper](https://virtualenvwrapper.readthedocs.io) may help when you are not using docker.
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- If you are using an Nvidia graphics card You should install CUDA (https://developer.nvidia.com/cuda-zone) and CUDNN (https://developer.nvidia.com/cudnn). If you do not plan to build Tensorflow yourself, make sure you install no higher than version 10.0 of CUDA and 7.4.x of CUDNN
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## Getting the faceswap code
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Simply download the code from http://github.com/deepfakes/faceswap - For development, it is recommended to use git instead of downloading the code and extracting it.
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It is recommended to clone the repo with git instead of downloading the code from http://github.com/deepfakes/faceswap and extracting it as this will make it far easier to get the latest code (which can be done from the GUI). To clone a repo you can either use the Git GUI for your distribution or open up a command prompt, enter the folder where you want to store faceswap and enter:
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```bash
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git clone https://github.com/deepfakes/faceswap.git
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```
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For now, extract the code to a directory where you're comfortable working with it. Navigate to it with the command line. For our example, we will use `~/faceswap/` as our project directory.
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## Setup
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Enter the folder that faceswap has been downloaded to and run:
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Enter your virtual environment and then enter the folder that faceswap has been downloaded to and run:
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```bash
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python setup.py
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```
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@@ -185,7 +204,7 @@ INFO 1. Install Docker
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1. Install Nvidia-Docker & Restart Docker Service
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https://github.com/NVIDIA/nvidia-docker
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1. Build Docker Image For Faceswap
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1. Build Docker Image For faceswap
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docker build -t deepfakes-gpu -f Dockerfile.gpu .
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1. Mount faceswap volume and Run it
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