2.1 KiB
2.1 KiB
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
Single Image Editing
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 \
--guidance_scale 1.0
Multiple Image Editing (Qwen-Image-Edit-2509+)
For multiple image inputs, use Qwen/Qwen-Image-Edit-2509 or later version:
python image_edit.py \
--model Qwen/Qwen-Image-Edit-2509 \
--image img1.png img2.png img3.png \
--prompt "Combine these images into a single scene" \
--output output_image_edit.png \
--num_inference_steps 50 \
--cfg_scale 4.0 \
--guidance_scale 1.0
Key arguments:
--model: model name or path. UseQwen/Qwen-Image-Edit-2509or later for multiple image support.--image: path(s) to the source image(s) (PNG/JPG, converted to RGB). Can specify multiple images.--prompt/--negative_prompt: text description (string).--cfg_scale: true classifier-free guidance scale (default: 4.0). Classifier-free guidance is enabled by setting cfg_scale > 1 and providing a negative_prompt. Higher guidance scale encourages images closely linked to the text prompt, usually at the expense of lower image quality.--guidance_scale: guidance scale for guidance-distilled models (default: 1.0, disabled). Unlike classifier-free guidance (--cfg_scale), guidance-distilled models take the guidance scale directly as an input parameter. Enabled when guidance_scale > 1. Ignored when not using guidance-distilled models.--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"