About Roop
TL;DR
Roop is an open-source, one-click face swap tool that replaces faces in images and videos using a single source photo. Built on InsightFace technology and licensed under GPL-3.0, it gained popularity for its simplicity compared to complex deepfake tools like DeepFaceLab. The original project was archived in March 2026, but forks like Roop-Unleashed and ReActor continue active development. Roop is completely free but requires technical setup (Python, FFmpeg, GPU recommended), and it includes built-in safeguards against generating inappropriate content.
Roop is a pioneering open-source face swap tool that made deepfake technology accessible with its one-click approach. While the original project is now archived, the code works and community forks continue improving it. Best for technically comfortable users who want a free, local alternative to commercial face swap services.
Best for: Developers, researchers, and technically comfortable creators who want a free, locally-run face swap tool with full privacy and no subscription costs.
What is Roop?
Overview
Roop made a name for itself as the simplest face swap tool in the open-source ecosystem. While tools like DeepFaceLab required hours of training and deep technical knowledge, Roop delivered face swaps with a single click: one source photo, one target video, one button. That simplicity is what made it popular, and it is what kept a large community of users engaged even as the project evolved.
The original Roop repository, created by developer s0md3v, was permanently archived on March 13, 2026. The developer cited concerns about the broader second-order effects of face-swapping technology. However, the code remains fully functional, and community forks (most notably Roop-Unleashed and ReActor) have continued development with new features and model support.
In our review, we found Roop still works reliably for basic face swaps. The output quality is good for casual use, though it falls short of what newer tools like Roop-Unleashed achieve with 256px output models and additional face restoration.
Key Capabilities
Roop's core function is straightforward: select a source face image, select a target image or video, and run the swap. The tool uses InsightFace's inswapper model (128px) to detect and replace faces. It supports both image and video processing, with configurable frame processors and multiple video encoder options.
The tool runs via command line with arguments for source selection, output paths, video encoding options, memory limits, and execution providers (CPU, CUDA for NVIDIA GPUs, DirectML for AMD GPUs). A headless mode is available for batch processing and automation.
Built-in ethical safeguards automatically detect and block attempts to process inappropriate content. This was a deliberate design choice by the original developer and remains in all official forks.
Roop-Unleashed, the most popular fork, adds significant improvements: face restoration using GFPGAN, 256px output resolution models (ReSwapper), multi-face swapping with individual face selection, text-prompt-based face occluder masking, and a web-based UI that replaces the command-line interface.
Pricing Analysis
Roop is completely free and open source under the GPL-3.0 license. There are no subscriptions, credits, or paid tiers. The only costs are hardware related: you need a computer capable of running the tool, and a dedicated GPU significantly improves processing speed.
The recommended setup is an NVIDIA GPU with at least 4GB of VRAM for GPU acceleration. An AMD GPU with DirectML support also works. CPU-only processing is possible but substantially slower, especially for video. Minimum system requirements include 8GB of RAM and a multi-core processor (Intel Core i5 or AMD Ryzen 5 equivalent).
For users without suitable hardware, Roop-Unleashed offers a web version starting at $15.99, providing cloud-based processing without local GPU requirements.
Who Should Use This
Roop is best suited for developers, researchers, and technically comfortable creators who want a free, local face swap tool with full control over the process. Common legitimate use cases include generating consistent faces for clothing model photography, character animation, meme creation, and visual effects experimentation.
The tool requires comfort with Python environments, command-line interfaces, and dependency management. Installation involves setting up Python 3.10, Anaconda, Git, FFmpeg, and downloading pre-trained models. This is explicitly not a beginner-friendly process.
Users who want a simpler experience should consider Roop-Unleashed (which adds a web UI) or commercial alternatives like Reface (mobile app) or DeepFaceLive (real-time face swap).
The Bottom Line
Roop remains a functional and capable face swap tool despite being archived. Its one-click simplicity was groundbreaking when it launched, and the code still delivers solid results for basic face replacement. The community forks, particularly Roop-Unleashed, have taken the concept further with better quality models and usability improvements. The main limitations are the technical installation barrier, the lack of ongoing official development, and output quality that newer commercial tools have surpassed. For a free, privacy-respecting, locally-run face swap tool, Roop and its forks remain the go-to choice in the open-source community.
Pros
- Completely free and open source under GPL-3.0 with no usage limits or subscriptions
- One-click face swap simplicity compared to complex alternatives like DeepFaceLab
- Runs locally with full privacy; no data leaves your machine
- Active community forks (Roop-Unleashed, ReActor) continue development with new features
- Built-in ethical safeguards against generating inappropriate content
Cons
- Original project archived in March 2026 with no further official updates
- Installation requires Python, FFmpeg, and GPU setup, which is not beginner-friendly
- Output quality (128px model) is below what newer commercial tools deliver
- CPU-only processing is very slow, making a dedicated GPU practically necessary
- Command-line interface lacks the polish of commercial alternatives
How to Use Roop
- 1Set Up Python Environment
Install Python 3.10 using Anaconda or Miniconda. Create a new virtual environment and activate it. Also install Git and FFmpeg, which are required dependencies.
- 2Clone and Install Roop
Clone the Roop repository from GitHub. Navigate to the project directory and install all required Python packages using pip install -r requirements.txt.
- 3Download the Face Model
Download the inswapper_128.onnx model file from the InsightFace project and place it in the Roop models directory.
- 4Set Up GPU Acceleration
For NVIDIA GPUs, install CUDA 11.8 and the corresponding onnxruntime-gpu package. For AMD GPUs, install onnxruntime-directml. CPU mode works without additional setup but is significantly slower.
- 5Run Face Swap
Execute the Roop command specifying your source face image, target image or video file, and output path. Additional flags control video encoding, memory limits, and execution provider.
- 6Review and Adjust
Check the output file for quality. If needed, adjust frame processor settings, try different execution providers, or apply face restoration using GFPGAN (available in Roop-Unleashed).
Key Features of Roop
Core
Replace faces in images and videos using a single source photo with minimal configuration.
Process entire video files to swap faces across all frames with consistent results.
Performance
Leverage NVIDIA CUDA or AMD DirectML for significantly faster face swap processing.
Advanced
Run face swaps via command line without a GUI for batch processing and automation scripts.
Customize processing pipeline with different frame processor configurations for quality tuning.
Export
Choose from various video encoder options to balance output quality and file size.
Safety
Automatic detection and blocking of attempts to process inappropriate or non-consensual content.
Privacy
All face swap processing happens on your local machine with no data sent to external servers.
Key Specifications
| Attribute | Roop |
|---|---|
| Free Tier | |
| API Access | |
| Platform Support | Windows, Linux, macOS (limited) |
| AI Powered | |
| Open Source | |
| License | GPL-3.0 |
| Gpu Required | Recommended (NVIDIA 4GB+ VRAM) |
| Browser Based |
Use Cases
- Creating deepfake videos for entertainment purposes.
- Swapping faces in images for creative projects.
- Enhancing video content with different facial expressions.
Integrations
GPU Acceleration
Video Processing
AI Model
ML Framework
Limitations
The original project is archived with no official support or updates. Installation is technical and not suitable for beginners. The 128px face model produces lower quality output than modern commercial tools. Video processing without a GPU is impractically slow for anything beyond short clips.
