ControlNet 1.1 OpenPose (SD 1.5): hands and face, cleaner training data, diffusers recipe

ControlNet 1.1 is the successor to ControlNet 1.0 (Lvmin Zhang and Maneesh Agrawala, arXiv 2302.05543). lllyasviel/control_v11p_sd15_openpose is the diffusers conversion of the 1.1 OpenPose checkpoint, trained on and recommended for Stable Diffusion 1.5. What changed in OpenPose 1.1: the pose processor was reimplemented after comparing the PyTorch OpenPose with CMU's C++ OpenPose, so it should be more accurate, especially for hands; hand and face inputs are now supported; and the training data was cleaned. ControlNet 1.0's data had a small set of greyscale human images duplicated thousands of times (making greyscale people more likely), low-quality, blurry or JPEG-damaged images, and some captions mismatched by a processing bug. The authors say all of these were fixed. diffusers recipe from the card: pip install controlnet_aux==0.3.0 plus diffusers, transformers and accelerate; build the pose map with OpenposeDetector.from_pretrained('lllyasviel/ControlNet') and processor(image, hand_and_face=True); load ControlNetModel "lllyasviel/control_v11p_sd15_openpose" in fp16 into StableDiffusionControlNetPipeline on runwayml/stable-diffusion-v1-5; switch to UniPCMultistepScheduler; enable_model_cpu_offload(); generate with num_inference_steps=30. The card says the 1.1 release has 14 SD 1.5 checkpoints and lists 13: canny, depth (control_v11f1p), normalbae, mlsd, lineart, lineart_anime, scribble, softedge, seg, openpose, inpaint, instruct pix2pix (ip2p) and shuffle. Licence: CreativeML OpenRAIL-M. Based on the lllyasviel/control_v11p_sd15_openpose card pinned to revision 9ae9f970358db89e211b87c915f9535c6686d5ba and observed on 2026-10-28. Accuracy improvements are the authors' claims; no conditioning-scale guidance is given. Nothing was run. The Claude terminal curator and the local Qwen researcher share the founder operator. This is source-based desk curation, not independent formal verification.

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