Krea-2-pose-controlnet

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What Krea-2-pose-controlnet is

Krea2 Turbo – OpenPose ControlNet LoRA 📝 Short description A classic OpenPose ControlNet LoRA for Krea2 Turbo. Feed an OpenPose / DWPose skeleton map as the control image — the model follows the body pose and structure while the text prompt defines appearance, style, clothing, and scene. 📦 Files - Weights: krea2turboopenposecontrolnet.safetensors - ComfyUI workflow: krea2controlnetpose.json - Repo: thedeoxen/Krea-2-pose-controlnet 📊 Examples Each preview is a single combined image from ComfyUI: Pose → Results (left to right). 📖 Extended description This is a straightforward pose ControlNet-style LoRA — not a reference + pose fusion model. It was primarily trained on humans, but also works with stylized characters. The LoRA teaches the model to treat the input image as an OpenPose control map and to align the generated subject with that skeleton. Appearance, outfit, lighting, and environment come from the prompt (and optional style cues), not from a second reference image. ⚙️ How to use 1. Extract or load an OpenPose / DWPose skeleton map (black background works best). 2. Pass the pose map as image 1 in the Krea2 Ostris Edit text encoder. 3. Write a normal text prompt describing the character / scene you want. 4. Load the LoRA on the Krea2 Turbo UNet (recommended weight 0.8–1.0). ComfyUI requirements Pose extraction in the included workflow uses DWPose (via comfyuicontrolnetaux): https://github.com/Fannovel16/comfyuicontrolnetaux Also requires the Krea2 Ostris Edit nodes for conditioning with a control image: https://github.com/ostris/comfyui-krea2-ostris-edit Base model Trained on and recommended with krea/Krea-2-Turbo (krea2turbofp8scaled.safetensors or equivalent). Typical sampler settings from the example workflow: ~10 steps, CFG ~1.0, euler + simple. ✅ Example prompt No special trigger phrase is required — the pose comes from the control image. 🎯 What it does - Follows body pose and keypoints from an OpenPose / DWPose map. - Lets the prompt freely define identity, clothing, style, and background. - Works as a drop-in classic ControlNet pose adapter for Krea2 Turbo. ⚡ Tips - DWPose skeleton maps on a black background work best as control input. - Keep subject

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

How it works

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Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys krea-2-pose-controlnet for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (krea-2-pose-controlnet below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/images/generations \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"krea-2-pose-controlnet","prompt":"a red bicycle","size":"1024x1024"}'

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