README.md

---
license: other
license_name: qwen-research-license
base_model: Qwen/Qwen-Image-2.1
pipeline_tag: image-to-image
tags:
  - lora
  - outpainting
  - uncrop
  - qwen-image
  - qwen-image-2.1
  - comfyui
  - ai-toolkit
---

# Qwen Image 2.1 Outpaint LoRA

Extends a picture in **any direction**: one side, two sides, a corner, three
sides, all four, or a small picture on a big empty canvas. Pad the picture with
flat gray `#808080`, give the padded canvas to Qwen Image 2.1 as the reference,
and the LoRA fills the gray with a continuation of the scene while keeping
the original picture where it is.

![source | base | step 500 | step 1250 | step 1500 | ground truth](comparison.jpg)

*Held-out pictures (never trained on), rendered in ComfyUI with the INT8 Qwen
Image 2.1 model, 25 steps, CFG 1: source | base model | LoRA step 500 | 1250 |
1500 | original picture.*

## Files

| file | notes |
|---|---|
| `qwen-image-2.1-outpaint.safetensors` | **use this**: step 1500 |
| `checkpoints/qwen21_outpaint_v1_000001250.safetensors` | step 1250, practically identical |
| `checkpoints/qwen21_outpaint_v1_000000500.safetensors` | step 500, already fixes framing; plainer fills |

Rank 32, ComfyUI key format (`diffusion_model.transformer_blocks.*`), all 384
tensors load onto the Comfy-Org Qwen Image 2.1 weights.

## Prompt

The instruction is the trigger. Put it first:

```
Outpaint the image: replace the solid gray areas with a seamless continuation of the scene, keeping the existing picture unchanged.
```

Optionally follow it with `Scene: <description>`. The training captions
described the whole picture, so a description of the source (what is visible)
works well; in ComfyUI, **Text Generate** with the Qwen3-VL 8B encoder you
already load for Qwen 2.1 can write it automatically from the picture.

## ComfyUI

1. Pad the picture with flat gray `#808080` (AusBoss **Load Image + Pad**:
   fill `color`, `#808080`, canvas multiple 32, target 1.0 MP).
2. **Text Encode Qwen Image 2.1**: the padded canvas as `image_1`,
   `resolution` 0 (reference and output share the canvas size), plus the prompt.
3. **KSampler** on the encoder's `latent` output: 25 steps, CFG 1,
   `euler` / `simple`, denoise 1.
4. **VAE Decode** -> **Split Image with Alpha** (the Qwen 2.1 VAE decodes RGBA)
   -> AusBoss **Stitch Inpaint** to paste the exact original pixels back over a
   32 px feather.

Do **not** pin the known area with *Set Latent Noise Mask*: on Qwen 2.1 that
draws a visible rectangle at the seam. The LoRA keeps the picture in place on
its own.

## What it fixes (12 held-out pictures, ComfyUI renders)

| | base Qwen 2.1 | + LoRA 500 | + LoRA 1250 | + LoRA 1500 |
|---|---|---|---|---|
| gray left unfilled | 9.1 % | 1.1 % | 1.0 % | 0.9 % |
| kept-area PSNR (picture stays in place) | 23.6 dB | 33.6 dB | 33.6 dB | 33.5 dB |
| mean colour step at the seam | +2.2 | -0.8 | -0.7 | -0.6 |

Without the LoRA, Qwen 2.1 often reframes or rescales the picture (a fisheye
kitchen shrank inside its frame, a street scene was recomposed) or returns a
gray frame untouched. With it, the known picture stays pixel-registered, which
is what makes a clean stitch possible. (The "gray" metric counts any flat
mid-gray, so gray pavement or sky can read as a few percent.)

## Training

- [ostris/ai-toolkit](https://github.com/ostris/ai-toolkit), `arch: qwen_image_2`,
  Comfy-Org INT8 convrot base (the same weights ComfyUI runs), text encoder
  embeddings cached with the reference image.
- 924 pairs from 231 pictures, 4 layouts each: all-sides frame, one side,
  opposite sides, corner, three sides, small window (12-30 % kept). Target =
  the picture at <= 1 MP on the /32 grid (never upscaled), source = same canvas
  with everything outside the kept rectangle painted `#808080`.
- Captions: the instruction (70 %) or one of five paraphrases (30 %), and for
  75 % of pairs `Scene:` + a Qwen3-VL-8B description of the whole picture.
  Caption dropout 0 (in this trainer a dropped caption also drops the reference).
- Rank 32 / alpha 32, AdamW8bit, LR 1e-4 constant, batch 1, `shift` timesteps,
  1500 steps. Converged by about step 1250; step 500 already works.
- Pictures: a hand-picked set plus openly licensed images: Flickr photos from
  [CommonCatalog CC-BY](https://huggingface.co/datasets/common-canvas/commoncatalog-cc-by),
  museum art from [PD12M](https://huggingface.co/datasets/Spawning/PD12M)
  (CC0 / public domain), anime from
  [anime-with-caption-cc0](https://huggingface.co/datasets/alfredplpl/anime-with-caption-cc0).

## Limits

- Very large extensions (the kept picture under ~15 % of the canvas) invent a
  lot; results vary more by seed.
- Trained at about 1 MP. Larger canvases work but are untested.
- Text in the new area is plausible, not legible.

## License

A LoRA for Qwen Image 2.1, which is released under the Qwen Research License;
use of the base model, and of this LoRA with it, follows that license.