4 Best Free Open Source Video Upscalers/Enhancers for Windows/Mac/Linux

Popular Open-Source AI Video Upscaler/Enhancer

There’s no shortage of open-source tools claiming to upscale or enhance video using AI. Some are created by researchers and maintained by GitHub contributors, while others are polished by solo developers for practical everyday use. Below are a few of the most popular open-source video upscalers and enhancers that people often turn to. Each has its own strengths, limitations, and quirks you should be aware of before diving in.

Video2X

Supported platforms: Windows (fully supported), Linux (limited support)

Video2X is a popular open-source tool that upscales videos by extracting individual frames, enlarging them with AI-powered image upscalers, and then reconstructing a high-resolution video using those processed frames. It supports a variety of AI upscaling engines such as waifu2x, waifu2x-ncnn-vulkan, SRMD, Anime4KCPP, and others — making it versatile enough for both anime and real-life footage. It also lets you customize output resolution, frame rate, and encoding format. A simple graphical interface is available for Windows users, while Linux users will need to rely on command-line operation.

Installation & How to Use:

1. Download the tool

Visit the official GitHub repo: https://github.com/k4yt3x/video2x
For Windows, use the latest “video2x-launcher” version for GUI access.

2. Install dependencies

• Make sure Python 3.9+ is installed
• Install FFmpeg and add it to your system path
• Optionally, install ImageMagick if needed for certain formats
• Install required Python packages via:

3. Set up an AI backend

Download and extract your preferred AI upscaler (e.g., waifu2x-ncnn-vulkan) and point Video2X to its executable path in the GUI or config file.

4. Run the GUI (Windows only)

Launch video2x-launcher.exe, load your video, choose a backend like waifu2x-ncnn-vulkan, and configure upscale settings.

5. Or use the command line

Example command:

6. Reattach the audio track

Since Video2X does not handle audio, use FFmpeg to merge the original audio back into the output video:

Real-ESRGAN

Supported platforms: Windows, Linux, macOS

Real-ESRGAN is a widely used open-source AI upscaler developed by the team behind ESRGAN. Built on the PyTorch framework, it offers high-quality image and video upscaling using pre-trained generative adversarial networks (GANs). Although it's originally designed for single image super-resolution, Real-ESRGAN can also be applied to videos by processing frame-by-frame, making it a strong choice for restoring low-resolution or compressed video content.

It performs especially well on real-world scenes — such as landscapes, faces, or low-quality smartphone footage — and is known for its ability to restore fine details while reducing noise and compression artifacts.

Installation & How to Use:

1. Install Python and dependencies

• Make sure Python 3.8 or later is installed
• Clone the repo from GitHub:
git clone https://github.com/xinntao/Real-ESRGAN.git 
cd Real-ESRGAN
copy
• Install required packages (ideally in a virtual environment)
pip install -r requirements.txt
copy

2. Download pre-trained models

The project supports various models:

• RealESRGAN_x4plus (general use)
• RealESRGAN_x4plus_anime_6B (anime images)
• realesr-general-x4v3 (for compressed images)

Download the desired .pth model files from the GitHub release or provided links.

3. Prepare your video (frame extraction)

Use FFmpeg to extract frames from your input video:

4. Run Real-ESRGAN on extracted frames

Example command (for 4x upscaling):

5. Recombine the frames into a video

Use FFmpeg again:

6. (Optional) Add audio back from the original video

Real-ESRGAN is best suited for users comfortable with Python and command-line tools, or those who want to integrate high-quality upscaling into automated pipelines. While it’s more technical to set up than GUI-based options, the visual results often speak for themselves — especially when restoring detail in blurry or low-res footage.

Waifu2x Extension GUI

Supported platform: Windows

Waifu2x Extension GUI is a user-friendly, Windows-only desktop application that wraps several AI upscalers — including waifu2x, Real-ESRGAN, and Anime4K — into a single graphical interface. Originally designed for anime-style images and videos, it has since expanded to support real-world content with additional model options. It’s widely appreciated for being easy to install and use, with no command-line operations required.

Unlike many open-source tools, Waifu2x Extension GUI is built for convenience: it handles frame extraction, upscaling, video reconstruction, and even audio syncing — all within the same interface. This makes it one of the most beginner-friendly options available for AI-based video enhancement on Windows.

Installation & How to Use:

1. Download the installer

Go to the project’s GitHub or Gitee release page: https://github.com/AaronFeng753/Waifu2x-Extension-GUI. Choose the latest .exe version (e.g., Waifu2x-Extension-GUI-v...-Installer.exe).

2. Install and launch the program

Run the installer. Once completed, open the application from the desktop shortcut or Start Menu.

3. Load your video

Drag and drop your video file into the program, or click "Add Files" and select your input.

4. Choose upscaling settings

• Select AI model (e.g., Real-ESRGAN, waifu2x-ncnn-vulkan, or Anime4KCPP)
• Set output resolution multiplier (e.g., 2× or 4×)
• Optional: apply denoising, frame interpolation, or artifact reduction

5. Start processing

Click the "Start" button. The app will handle everything automatically: extract frames, upscale, rebuild the video, and sync the audio.

6. Access the output

The upscaled video will be saved in the specified output folder, ready to use or upload.

Waifu2x Extension GUI is ideal for users who want solid AI upscaling results without touching code or setting up complex environments. While it's less customizable than script-based tools, it offers a polished out-of-the-box experience that’s hard to beat — especially for anime and low-resolution web videos.

Anime4K

Supported platforms: Windows, macOS, Linux (via video players or custom scripts)

Anime4K is a lightweight, open-source video upscaling algorithm specifically designed for anime and line-art content. Unlike other tools that rely on deep learning or GAN models, Anime4K uses efficient OpenCL or Vulkan shaders that run directly on your GPU. This makes it fast, real-time, and suitable even for low-end hardware.

Rather than extracting and reassembling video frames, Anime4K is typically used within video players like MPV or VLC via shader scripts. It can also be applied offline using FFmpeg filters or command-line tools, but its biggest strength lies in real-time playback enhancement — making old anime or low-res web videos look cleaner and sharper instantly.

Installation & How to Use:

Option 1: Real-time playback with MPV

1. Download MPV player from: https://mpv.io/
2. Clone or download the Anime4K repository: https://github.com/bloc97/Anime4K
3. Place the shader files (e.g., Anime4K_Clamp_Hybrid.glsl) in MPV’s shaders folder.
4. Edit mpv.conf to activate the shader: glsl-shaders="~~/shaders/Anime4K_Clamp_Hybrid.glsl"
5. Open your video with MPV, and the enhancement will apply in real time.

Option 2: Offline processing with FFmpeg (Advanced users)

Some forks (like Anime4KCPP) provide ways to run Anime4K filters on video files directly, but this requires compiling the tool or using specific FFmpeg builds with shader support — not beginner-friendly.

Anime4K is best suited for anime fans or anyone who wants instant visual improvement for low-res animated content. It doesn't offer the deep restoration capabilities of AI models like Real-ESRGAN or Video2X, but its speed and simplicity make it an excellent choice for playback or lightweight enhancement.

As you can see, open-source video enhancers come in many forms — from user-friendly GUIs like Waifu2x Extension GUI to lightweight shader-based solutions like Anime4K. While these tools are powerful and cost nothing to use, they also come with certain trade-offs that might be frustrating for beginners or even experienced users. In the next section, we’ll look at some of the most common challenges people face when working with these open-source solutions.

Common Difficulties When Using Open Source AI Video Enhancers

While open-source AI video upscalers offer impressive capabilities, they often come with a steep learning curve. Many users download these tools expecting a plug-and-play experience, only to discover that getting them to work involves technical steps, dependency management, or hours of trial and error. Here are some of the most common challenges people encounter.

Complex Installation and Setup

Many open-source AI video enhancers rely on Python, PyTorch, or other frameworks that require manual installation. You may need to clone GitHub repositories, install dependencies, configure environment variables, or download separate AI models — all before you can even process a single video. If you’re not already familiar with these tools, the process can feel overwhelming.

2. Lack of a Unified Interface

Unlike commercial tools, which typically offer polished interfaces and streamlined workflows, most open-source projects focus on the backend AI functionality. You often need to extract video frames using FFmpeg, upscale them separately, and then manually reassemble the video. GUI options exist, but they’re often limited to Windows or may be outdated.

3. Audio Handling is Often Ignored

Many tools focus solely on the visual part of the video and leave audio out of the equation. As a result, users must manually extract and reattach audio tracks using FFmpeg or other tools. This adds yet another step to an already complex workflow and increases the chance of errors like desynchronization.

4. Limited Support and Documentation

Since these tools are often passion projects or research demos, they usually lack formal support channels. Documentation can be inconsistent, outdated, or too technical for beginners. If you get stuck, your only recourse may be searching GitHub issues, Reddit threads, or online forums — which doesn't always yield clear answers.

A Simpler, More Efficient Alternative to Open Source Video Upscaler/Enhancer

If you’ve ever struggled to get an open-source AI upscaler running, you’re not alone. Between installing Python environments, managing model files, and stitching video and audio back together, what should be a simple enhancement task often turns into a weekend project.

To simplify the entire process, Aiarty Video Enhancer offers a clean, all-in-one solution for video upscaling and restoration — no coding, no command-line tools, and no technical guesswork required.

With Aiarty, you can upscale low-resolution videos to 1080p, 2K, or even 4K in just a few clicks. It also goes beyond basic resolution improvement — removing compression artifacts, reducing noise, deblurring faces, and restoring fine details in everything from old DV tapes to mobile-shot footage. For choppy videos, frame interpolation helps create a smoother look.

Feature Comparison: Aiarty Video Enhancer vs. Open-Source Video Enhancers

While Anime4K is a well-known open-source project, it focuses on real-time playback enhancement rather than pre-processing and exporting videos — making it fundamentally different from the other tools discussed. For that reason, we’ve excluded it from the comparison table below, which focuses on tools designed for AI-based video upscaling and enhancement through preprocessing.

Here's how Aiarty Video Enhancer stacks up against the most commonly used open-source options:

How to Use Aiarty Video Enhancer to Upscale/Enhancer Your Videos

Getting started with Aiarty Video Enhancer is straightforward and requires no prior video editing knowledge. Just follow these simple steps to enhance your videos smoothly:

Step 1: Download and install Aiarty Video Enhancer on your PC or Mac from the official website.

Step 2: Open the program and drag your video file into the main workspace.

Step 3: From the AI Model dropdown menu, select the enhancement model that fits your video type best.

Step 4: Choose your desired output resolution under the Upscale menu.

Step 5: Click the Preview button to see a quick sample of how the enhanced video will look.

Step 6: If the preview meets your expectations, add the task to the queue and select either “Export Current” for a single video or “Batch Export” to process multiple videos at once.

Conclusion

Open-source AI video upscalers and enhancers offer exciting possibilities for improving video quality without spending a dime. However, as we’ve seen, they often come with technical hurdles, complex setups, and limited user-friendly features that can slow down or frustrate many users.

For those seeking a more streamlined, hassle-free way to upscale and enhance videos, tools like Aiarty Video Enhancer provide a powerful yet accessible solution. With its easy-to-use interface, comprehensive features, and reliable performance, it bridges the gap between advanced AI technology and practical everyday use.

Whether you’re restoring old family videos, cleaning up smartphone footage, or simply want sharper, clearer content for social media, choosing the right tool makes all the difference. Hopefully, this guide helps you make an informed choice and get the most out of AI-powered video enhancement.