The only places to get a genuine License code for the supporter models are Buy Me a Coffee, Unifans, and for China the seller in the Chinese README.

> 支持者模型的正版许可证码只能通过 Buy Me a Coffee、Unifans 或 闲鱼 获取。

English | 日本語 | 中文

Jasna

Jasna restores mosaics in videos and images. It is free, has a simple app and a command line, and runs on your GPU.

Contents

Start here

• What Jasna does
• What you need
• Quick start
• Help and community
• Supporting the project (supporter models)

• How Jasna works
• Command line
• All guides
• Benchmarks
• Licensing
• Acknowledgments

What Jasna does

• Finds mosaics in a video and restores them. The rest of the picture is not

• Two restoration models: fast BasicVSR++ (free) and slow but more

• Restores only the parts you choose, with a preview, in the **Segment

• Works with VR180 videos and still images (SD 1.5, for supporters).
• Lets you watch a video restored live in the Video Player, without making

What you need

• NVIDIA GTX 16-series / RTX 20-series or newer, with a recent driver

• Or AMD Radeon RX 7000/9000 (experimental). RX 6000 and older don't work.
• A folder on a local disk, with no Chinese, Japanese, accented or other

Quick start

1. Download the release for your system and GPU.
2. Unpack it into a folder with no Chinese, Japanese, accented or other

1. Start the app:

curl -fLO https://repo.radeon.com/amf/26.20/amf_installer_26.20.zip
     unzip amf_installer_26.20.zip
     sudo bash amf_installer_26.20.sh

Accept AMD's license when prompted, then run run_jasna_amd.sh. If using Distrobox, install AMF inside the same container as Jasna.

1. Add a video, choose settings and click the ▶ button at the bottom.

Every setting has a tooltip: move the mouse over the ⓘ icon. Out of GPU memory (VRAM)? Lower Max Clip Size, for example from 90 to 60. See Tuning.

Help and community

• App guide: the queue, presets, output names, the Video

• SLS Discord: examples, help and settings.

• Problem? Click Logs at the bottom of the app, then Export to save a

Supporting the project

Jasna is free. Your support pays for training new models, mostly GPU rental. Supporters get a License code for the supporter models:

| Support | Models | | --- | --- | | $15 USD or more in total | UNet 4x: makes restored areas sharper.
SD 1.5: experimental model for still images. | | $25 USD | UNet 4x and SD 1.5, plus
LTX: much slower than BasicVSR++, but more detail. Includes future updates of this LTX model. |

Supporters who gave $15 USD or more on or before 14 October 2026 get LTX for free.

Before you choose LTX:

• Look at these LTX samples: 1, 2, 3, 4, 5, 6, 7, 8.

• Run LTX in Trial mode (speed test) on your PC. It is free and shows if your GPU can

More examples: UNet 4x, SD 1.5, more SD 1.5.

Where to support

License codes come only from here:

• Buy Me a Coffee (crypto works too)
• Unifans
• For China: see the Chinese README

How to activate

1. Support on one of the pages above. You get a License code.
2. In Jasna, open Activate Jasna, enter the License code and press

One License code works on 3 devices at the same time. To see how many are in use, open Activate Jasna again.

• PC with a TPM 2.0 security chip (most Windows 11 PCs): after one online

• Other PCs, rented GPUs and Docker: Jasna needs internet while it uses

• Linux with a security chip: to use it offline, run

Coming from Jasna 0.11? Your activation carries over the first time you use a supporter model, and Jasna 0.11 keeps working on the same PC.

Have an email and key from Jasna 0.10? They no longer work. Get a new License code from where you bought it.

Advanced

How Jasna works

Almost everything runs on the GPU, from reading the video to saving it.

1. Decode the video on the GPU (NVDEC on NVIDIA, AMF on AMD).
2. Detect mosaics in each frame (default model rfdetr-v6).
3. Track each mosaic over time and group its frames into clips (up to

1. Restore each clip as a 256x256 picture with BasicVSR++. Clips overlap a

1. Optional secondary restoration (UNet 4x, RTX Super Res or Topaz TVAI)

1. Blend the restored picture back into the original frame. Only the

1. Encode with the GPU encoder (NVENC on NVIDIA, AMF on AMD). Audio is

On NVIDIA, the first job prepares the models for steps 2 and 4 (and UNet 4x, if used) for your exact GPU; on AMD, only UNet 4x. The result is saved in model_weights and used again later. You can copy it to a newer Jasna version.

LTX works differently. It goes over the video in 4 passes: find mosaics, prepare, restore with a diffusion model, save. It is slower but can add more real detail. Its quality choices: Basic (about 1.3x faster than Standard), Standard (default), Good (about 1.5x slower), High (about 2.5x slower) and Top (about 5x slower). See Choosing models.

LTX jobs can pause and continue. See Pause and continue.

Command line

The command line can do most of what the app does (not the Video Player, LTX seed previews, mask suggestions or interactive image mode).

# One video
jasna --input input.mp4 --output output.mkv
One image
jasna --input photo.png --output restored.png
A whole folder
jasna --input input_folder --output output_folder

jasna --help lists all options. See the CLI reference.

All guides

• Using the GUI: queue, presets, output names, Video

• Choosing models: detection models, BasicVSR++ or LTX,

• Restoring only parts of a video: Segment Editor,

• VR180 videos: how side-by-side VR is handled.
• Tuning VRAM and GPU usage: clip size, overlap, what to

• Advanced processing: denoise, 60→30 FPS,

• Streaming: watch in the browser or in Stash.
• Cloud GPUs: Jasna on a rented GPU (RunPod, Vast).
• CLI reference: all command line options.
• Running from source: for developers. From source

Benchmarks

Time to restore a whole 3:22 video with BasicVSR++ on an RTX 5090 (Linux). Lower is better.

| Input | Lada 0.11.0 | Jasna v0.9.1 | | --- | ---: | ---: | | 720p H.264 | 01:47 | 00:32 (3.4x faster) | | 1080p H.264 | 02:02 | 00:34 (3.6x faster) | | 2160p H.264 | 04:56 | 01:03 (4.7x faster) |

Licensing

Jasna's public application source is AGPL-3.0. Models and bundled dependencies keep their own terms. See licensing and source availability, model notices and the release source correspondence.

Acknowledgments

• Lada (Codeberg): Jasna is inspired

• ZeLeFans: for the VR detection model and the detailed analysis of mosaic