Image Editing (Local Diffusion / GGUF)

Annolid can generate or edit images using:

Diffusers (Python): e.g. Qwen/Qwen-Image-2512
stable-diffusion.cpp (sd-cli): e.g. GGUF models like unsloth/Qwen-Image-2512-GGUF

Install (Diffusers)

pip install -U "annolid[image_editing]"

CLI examples

Diffusers (text-to-image)

annolid-run predict image-edit \
  --backend diffusers \
  --model-id Qwen/Qwen-Image-2512 \
  --prompt "cartoon sloth wearing a lab coat" \
  --width 1024 --height 1024 \
  --output qwen.png

stable-diffusion.cpp (GGUF preset)

Build or download stable-diffusion.cpp and locate the sd-cli binary.
Run with the built-in preset (downloads weights from Hugging Face on first run):

annolid-run predict image-edit \
  --backend sdcpp \
  --sd-cli /path/to/sd-cli \
  --preset qwen-image-2512-gguf \
  --quant Q2_K \
  --prompt "cartoon sloth" \
  --width 1024 --height 1024 \
  --output qwen_gguf.png

Notes:

--preset/--quant are Annolid options (they are not valid flags for sd-cli itself).
Q2_K is the repo naming; Annolid also accepts Q2-K and normalizes it to Q2_K.
On macOS Metal builds, if you see unsupported op 'DIAG_MASK_INF', update/rebuild stable-diffusion.cpp (or build a CPU-only sd-cli with Metal disabled, e.g. cmake -B build-cpu -DGGML_METAL=OFF).

GUI

Open File → Image Editing… (or the toolbar button), choose a backend, enter a prompt, and click Run.