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How to perform a face Swap in a Video with Your Own image using Roop

/ Python Cool Stuff
Deep fake

Last Updated on 08/10/2025 by Eran Feit

Introduction (Face Swap):

If you’ve ever wanted to drop your face into a video—cleanly and with minimal setup—this guide walks you through Roop, a simple face-swap tool you can run locally. We’ll cover the full workflow: creating a clean Conda environment, installing the exact dependencies, preparing your image and target video, and running Roop on both CPU and GPU. By the end, you’ll press Start, watch the swap happen, and know how to fix the most common snags along the way.

In this tutorial, we’re diving into the world of Deepfake and face swapping using the Roop Python library.

As we explore the innovative techniques behind Deepfake technology, it’s crucial to understand the ethical implications and potential misuse of this powerful tool. Deepfakes can be used creatively in film, art, and entertainment, but they also pose significant risks, such as identity theft and misinformation. In this tutorial, we will not only guide you through the technical aspects of face swapping but also emphasize responsible usage.

To give you an idea of what this looks like in practice, imagine creating a video where a famous movie scene features your face instead of the actor’s. The applications are vast and can range from harmless fun to impactful storytelling.

Moreover, the Roop library simplifies the process, allowing users to dive into advanced techniques without needing an extensive background in machine learning. This accessibility opens the door for many creators to engage with cutting-edge technology.

The goal of this video is to replace faces in a video with just one image, without the need for training or extensive datasets.

You’ll be able to create face swap effects in no time

Let’s break down the setup process further. When creating a Conda environment, it ensures that all dependencies are managed correctly. This is particularly important as different projects may require specific versions of libraries.

After running the app, you might want to experiment with different face images to see how various expressions translate to your video. This experimentation is part of the fun and creativity that comes with using the Roop library. You will be amazed at the results!

⚠️ Use Roop responsibly. Only use images and videos you have the right to edit. Don’t impersonate, mislead, or violate privacy policies, platform terms, or local laws.

Check out our tutorial here : https://www.youtube.com/watch?v=2wqHbrD2x4o

Download the Instructions for this tutorial plus the media file : https://ko-fi.com/s/b9ec5411cb

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Part A — Create a clean Conda environment & clone the project

Intro:
We’ll start in a fresh Conda environment so Roop’s dependencies don’t conflict with your other projects. This part gets you cloned, activated, and ready to install the essentials.

What we’ll do (high-level):

  • Clone the repository
  • Create and activate a Python 3.10 Conda env
  • Stay organized inside the roop folder for everything else
git clone https://github.com/s0md3v/roop.git cd roop  conda create --name roop python=3.10 -y conda activate roop

Part B — Install ffmpeg and Python requirements

Intro:
Roop needs ffmpeg for video I/O and a set of Python packages pinned in requirements.txt. Installing them now avoids mysterious runtime errors later.

What we’ll do (high-level):

  • Install ffmpeg via Conda Forge
  • Install all Python dependencies from requirements.txt
conda install -c conda-forge ffmpeg -y pip install -r requirements.txt

Summary:
You’ve added video tooling and all Python dependencies. If you see errors here, double-check that your Conda env is active and that you’re in the roop folder.

Part C — Prepare your inputs: face image + target video

Intro:
Roop needs a single clear face image and a target video. Good lighting and a forward-facing image help the model anchor features cleanly.

What we’ll do (high-level):

  • Place your face image (PNG/JPG) in the roop folder
  • Place your target video (MP4/MOV/AVI) in the roop folder
  • Keep filenames simple (no spaces if possible)

Part D — Windows extras (recommended)

Intro:
On Windows, C++ runtimes and build tools prevent common compilation/runtime errors from libraries used under the hood.

What we’ll do (high-level):

  • Install Microsoft Visual C++ Redistributable
  • Install Microsoft C++ Build Tools

Part E — Run Roop on CPU (works everywhere)

Intro:
If you don’t have a compatible GPU, or just want to verify the pipeline, start with CPU. It’s slower, but great for sanity checks.

What we’ll do (high-level):

  • Launch Roop
  • Use the UI to select your face image and video
  • Click Start to create the swapped video
python run.py

UI flow (no code):
a) Choose your image
b) Choose your target video
c) Click Start

Part F — Enable GPU acceleration (NVIDIA + CUDA)

Intro:
GPU can dramatically speed up inference. We’ll set Roop to use ONNX Runtime GPU 1.15.1, which is known to be stable for many setups.

What we’ll do (high-level):

  • Uninstall any conflicting ONNX Runtime builds
  • Install the exact GPU build
  • Confirm your GPU drivers and CUDA runtime are properly configured on your system
pip uninstall -y onnxruntime onnxruntime-gpu pip install onnxruntime-gpu==1.15.1

Summary:
You’ve pinned the GPU runtime version to avoid dependency drift. If your GPU isn’t recognized, verify NVIDIA drivers and CUDA support.

Part G — Run Roop with GPU

Intro:
With GPU packages in place, we’ll tell Roop to use the CUDA execution provider. This reduces processing time substantially, especially on longer clips.

What we’ll do (high-level):

  • Launch Roop with the CUDA provider flag
  • Repeat the same simple UI flow
python run.py --execution-provider cuda  a. Choose your image b. CHoose your target video c. click Start

Part H — Quick troubleshooting & quality tips

Intro:
A few small tweaks can make a big difference in stability and output quality.

Practical notes:

  • Image quality: Use a sharp, well-lit face image facing the camera.
  • Video quality: Stable, well-lit target videos swap better.
  • File paths: Keep filenames simple (avoid spaces and special characters).
  • CUDA issues: Re-install GPU drivers, ensure your CUDA runtime matches your ONNX GPU build, and verify --execution-provider cuda is recognized in logs.
  • Try a short clip first: Validate your setup on a 5–10s clip before running a longer video.

Summary:
Most errors trace back to drivers, mismatched versions, or low-quality inputs. Fix those early, and results will follow.

Full script for Face Swap :

Roop : https://github.com/s0md3v/roop ===========================================  git clone https://github.com/s0md3v/roop.git cd roop  conda create --name roop python=3.10 conda activate roop  conda install -c conda-forge ffmpeg pip install -r requirements.txt  # copy expmaple files : copy face image to the roop folder copy a video (to be replaced) to the roop folder   # If you are using Windows You should also install :  1. Microsoft Visual C++ Redistributable : https://learn.microsoft.com/en-US/cpp/windows/latest-supported-vc-redist?view=msvc-170  2. Microsoft C++ Build Tools : https://visualstudio.microsoft.com/visual-cpp-build-tools/   #Run command - no GPU : =======================  1. If you don't have Gpu card :  python run.py -----------------------------------------  2. If you have Gpu card :  pip uninstall onnxruntime onnxruntime-gpu pip install onnxruntime-gpu==1.15.1  #Run command - With GPU : python run.py --execution-provider cuda ---------------------------------------------  a. Choose your image b. CHoose your target video c. click Start

Download the Instructions for this tutorial plus the media file : https://ko-fi.com/s/b9ec5411cb

More relevant content in this playlist : https://www.youtube.com/playlist?list=PLdkryDe59y4bxVvpexwR6PMTHH6_vFXjA

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Embrace the possibilities of face swapping technology while being mindful of its implications. With Roop, the world of creativity is at your fingertips! Happy swapping!

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Eran Feit