New additive node (existing four untouched): VAE-encodes a source image
and denoises from a noised version of it. Rectified-flow interpolant
x_t=(1-t)·z0+t·noise, entering the schedule at t=denoise; denoise=1.0
takes the exact txt2img code path (verified pixel-identical to the
parity reference — the hard guard that generation is undisturbed).
Engine changes are additive: sample() gains init_latent/strength
(strength>=1.0 is a byte-identical no-op), pipeline gains
generate_img2img() reusing the prompt cache + LoRA path, nodes.py gains
_from_image_tensor. VAE encode input range verified [-1,1] (round-trip
45 dB). Denoise sweep 0.3→0.9 is monotonic and coherent; contact sheet
and strength=1.0 guard in tools/test_img2img.py.
First rung of the image-conditioning ladder (img2img → in-context edit
→ grounded vision); reuses the VAE-encode plumbing the edit path needs.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Krea2ModelLoader / Krea2LoRA / Krea2Generate / Krea2Unload nodes running
Krea-2-Turbo on Apple MLX in-process, returning ComfyUI IMAGE tensors.
The krea2_engine/ pipeline is vendored directly in this repo (no external
git dependency) — see NOTICE for the full attribution chain back to the
original Krea 2 model and the MLX port it builds on.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
