aestx workflows — drop-in versions

Reworked versions of the original aestx8-* / aestx-final-* workflows, updated Jul 2026 to run on current ComfyUI (0.27) + current custom-node packs, and converted from raw API format to proper UI workflows you can download and drag-drop into ComfyUI. Image inputs are now regular LoadImage nodes (pick/upload a file in the node) instead of ETN_LoadImageBase64 base64 injection.

The workflows

file	what it does
`aestx-single-ipadapter.json`	SDXL (Juggernaut v8) txt2img, IPAdapter style transfer from a style image + depth ControlNet composition lock from a composition image. Batch of 4.
`aestx-prev-single-ipadapter.json`	Same as above plus a PreviewImage node showing the generated depth map.
`aestx-style-composition.json`	SDXL Lightning (Juggernaut v9 RDPhoto2 Lightning, 5 steps) with `IPAdapterStyleComposition` — separate style and composition reference images — plus depth ControlNet. Batch of 4.

api/ holds the equivalent API-format JSONs (for /prompt automation — these are the exact payloads that were test-executed).

Changes vs the originals (needed to run on current packs)

ETN_LoadImageBase64 → core LoadImage (defaults: aestx-style.png, aestx-composition.png — just pick your own images in the two nodes).
IPAdapter_plus renamed weight type style transfer (SDXL) → style transfer.
ComfyUI_essentials ImageResize+: keep_proportion: true → method: "keep proportion".
Legacy Get image size node → essentials GetImageSize+ (width output wired to the DepthAnything resolution input, as before).

Dependencies

Custom node packs (auto-installable via download_missing_models.sh, which reads the cnr_id/aux_id metadata embedded in the workflow nodes):

cubiq/ComfyUI_IPAdapter_plus (tested @ a0f451a)
Fannovel16/comfyui_controlnet_aux (tested @ e8b689a)
cubiq/ComfyUI_essentials (tested @ 9d9f4be)

Python deps installed for the packs: opencv-python-headless scikit-image python-dateutil fvcore yapf omegaconf ftfy addict yacs albumentations scikit-learn matplotlib numba colour-science (mediapipe/onnxruntime skipped — not needed by these workflows).

Models (all mirrored in this repo under models/, sources noted):

path in `ComfyUI/models/`	size	source
`checkpoints/juggernautXL_v8Rundiffusion.safetensors`	7.1 GB	`lllyasviel/fav_models`
`checkpoints/juggernautXL_v9Rdphoto2Lightning.safetensors`	7.1 GB	`RunDiffusion/Juggernaut-XL-Lightning` (`Juggernaut_RunDiffusionPhoto2_Lightning_4Steps.safetensors`, renamed to the ckpt name the workflows expect)
`controlnet/diffusers_xl_depth_full.safetensors`	2.5 GB	`lllyasviel/sd_control_collection`
`ipadapter/ip-adapter-plus_sdxl_vit-h.safetensors`	0.85 GB	`h94/IP-Adapter`
`clip_vision/CLIP-ViT-H-14-laion2B-s32B-b79K.safetensors`	2.5 GB	`h94/IP-Adapter` image encoder (renamed to the exact filename `IPAdapterUnifiedLoader` searches for)

depth_anything_vitl14.pth (1.3 GB, mirrored at models/depthanything/) is auto-downloaded by controlnet_aux on first run to custom_nodes/comfyui_controlnet_aux/ckpts/LiheYoung/Depth-Anything/checkpoints/ — copy it there manually for offline pods.

All three workflows were test-executed end-to-end on the H100 pod (ComfyUI 0.27.0, torch 2.8.0+cu128) and outputs visually verified: IPAdapter style transfer, depth-map conditioning, and batch generation all confirmed working.