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。

Jasna

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

Start here

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

Advanced

What Jasna does

Finds mosaics in a video and restores them. The rest of the picture is not touched.
Two restoration models: fast BasicVSR++ (free) and slow but more detailed LTX (for supporters).
Restores only the parts you choose, with a preview, in the Segment Editor.
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 a file.

What you need

NVIDIA GTX 16-series / RTX 20-series or newer, with a recent driver (610+ on Windows, 580+ on Linux). GTX 10-series and older don't work.
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 non-English characters in its path.

More details

NVIDIA: your GPU needs compute capability 7.5 or higher in NVIDIA's GPU table.
AMD: see the table below. UNet 4x secondary restoration is supported.
Disk format: NTFS on Windows; ext4, Btrfs, XFS or ZFS on Linux. Network disks are not supported. Use an SSD; on a hard disk (HDD) Jasna starts and loads models slowly.
LTX needs an NVIDIA RTX or AMD Radeon RX 7000/9000 GPU, at least 8 GB VRAM and 16 GB RAM. See What LTX needs.

AMD GPU	Jasna	LTX
Radeon RX 9060/9070, Radeon AI PRO R9700	yes	yes (Windows: beta)
Radeon RX 7600–7900, Radeon PRO W7000	yes	yes (Windows: beta)
Radeon 740M/760M/780M/880M/890M, Ryzen AI Max (8050S/8060S)	yes, untested	yes, untested
Radeon RX 6000 and older, Radeon 820M/840M/860M	no	no

Quick start

Download the release for your system and GPU.
Unpack it into a folder with no Chinese, Japanese, accented or other non-English characters in the path.
Start the app:
- Windows: double-click jasna.exe. On AMD, first install AMD's driver for ROCm 10.1 (26.10.41.05, download .exe) and reboot. You don't need to install ROCm.
- Linux NVIDIA: run the jasna file.
- Linux AMD: first install AMD's AMF video runtime once. We tested AMF 26.20:
```
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.
Add a video, choose settings and click the ▶ button at the bottom.

Your first job is slow. On NVIDIA, Jasna first prepares the models for your exact GPU. This takes about 15–60 minutes, only once. Close other apps and don't use the PC during this time. When you update Jasna, copy the model_weights folder to the new version, so you don't wait again. LTX may still ask to download its model again after an update. On AMD, only UNet 4x needs this preparation, on its first use.

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 Player and activation.
SLS Discord: examples, help and settings. Jasna has a new channel; older posts stay in the old channel (archived). Please don't be too weird.
Problem? Click Logs at the bottom of the app, then Export to save a log file. Attach it when you ask for help.

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. Explore the new channel and the old channel (archived) on SLS Discord for more samples.
Run LTX in Trial mode (speed test) on your PC. It is free and shows if your GPU can run LTX and how long it takes. The video is not restored. See What LTX needs.

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

Anyone else selling Jasna, codes or modified files is a scam: their keys don't work, and their files can run hidden code on your PC. Download Jasna only from GitHub.

How to activate

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

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 activation, Jasna works offline. The PC keeps one of your 3 slots. Windows may ask for permission once. A new motherboard or a security chip reset counts as a new PC.
Other PCs, rented GPUs and Docker: Jasna needs internet while it uses supporter models. A device counts only while Jasna runs. See Cloud GPUs.
Linux with a security chip: to use it offline, run sudo usermod -aG tss $USER, restart the PC and activate again.

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.

Decode the video on the GPU (NVDEC on NVIDIA, AMF on AMD).
Detect mosaics in each frame (default model rfdetr-v6).
Track each mosaic over time and group its frames into clips (up to Max Clip Size frames). Clips end at scene cuts, so two different shots are never mixed.
Restore each clip as a 256x256 picture with BasicVSR++. Clips overlap a little, so there are no visible jumps between them.
Optional secondary restoration (UNet 4x, RTX Super Res or Topaz TVAI) makes the restored picture bigger and sharper.
Blend the restored picture back into the original frame. Only the mosaic area changes.
Encode with the GPU encoder (NVENC on NVIDIA, AMF on AMD). Audio is copied (encoded again only if the output format can't hold it).

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 Player, activation.
Choosing models: detection models, BasicVSR++ or LTX, secondary restoration, SD 1.5 for images.
Restoring only parts of a video: Segment Editor, mosaic scan, LTX only for big mosaics.
VR180 videos: how side-by-side VR is handled.
Tuning VRAM and GPU usage: clip size, overlap, what to do when VRAM runs out.
Advanced processing: denoise, 60→30 FPS, color LUT, sharpening, encoder quality, actions after the queue.
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 you can use the free BasicVSR++; activation and supporter models need the official release.

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)

GPU memory, older versions and how it was measured

GPU memory used (typical / peak, in GB). — means not measured. Lada uses less GPU memory than Jasna.

Input	Lada	v0.4.1	v0.5.0	v0.9.0	v0.9.1
720p H.264 8-bit	1.8/3.1	17.6/19.9	8.6/9.0	8.6/9.1	4.2/4.6
1080p H.264 8-bit	2.0/3.3	18.9/21.4	9.5/10.2	9.3/10.1	4.8/5.6
2160p H.264 8-bit	2.6/4.1	26.0/30.5	12.9/15.0	11.4/15.4	7.2/10.9
8K VR HEVC 60 fps (15 s)	—	—	—	17.1/18.3	—

Times for older versions (v0.4.1: 01:35 / 01:46 / 03:23; v0.5.0: 00:45 / 00:47 / 01:22; v0.9.0: 00:34 / 00:39 / 01:15 for 720p / 1080p / 2160p; 8K VR: 00:34), the test settings, RAM use and every codec are in the full benchmark report. Older full-length videos: legacy report.

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 by Lada and in some places based on it. The mosaic_restoration_1.2 model used by Jasna was trained by ladaapp, the author of Lada.
ZeLeFans: for the VR detection model and the detailed analysis of mosaic shapes and VR projection.

Kruk2/jasna

Measured star growth

README.md