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# Image-To-Image
Source <https://github.com/vllm-project/vllm-omni/tree/main/examples/offline_inference/image_to_image>.
This example edits an input image with `Qwen/Qwen-Image-Edit` using the `image_edit.py` CLI.
## Local CLI Usage
```bash
python image_edit.py \
--image qwen_bear.png \
--prompt "Let this mascot dance under the moon, surrounded by floating stars and poetic bubbles such as 'Be Kind'" \
--output output_image_edit.png \
--num_inference_steps 50 \
--cfg_scale 4.0
```
Key arguments:
- `--image`: path to the source image (PNG/JPG, converted to RGB).
- `--prompt` / `--negative_prompt`: text description (string).
- `--cfg_scale`: true CFG scale for Qwen-Image-Edit (quality vs. fidelity).
- `--num_inference_steps`: diffusion sampling steps (more steps = higher quality, slower).
- `--output`: path to save the generated PNG.
## Example materials
??? abstract "image_edit.py"
``````py
--8<-- "examples/offline_inference/image_to_image/image_edit.py"
``````