xinsir OpenPose ControlNet for SDXL: draw thicker pose lines, and the card's recipe

xinsir's ControlNet-openpose-sdxl-1.0 (fine-tuned for stabilityai/stable-diffusion-xl-base-1.0) was trained with thicker pose lines than the controlnet_aux default drawing, so with the default pose lines results can be unstable. The fix from the card: in controlnet_aux/open_pose/util.py replace draw_bodypose with the card's version, which takes keypoints normalised to 0-1 and scales limb width and joint size with the image's longest side (ratio 1 below 500 px rising to 7 at 5000 px and above, stick width 4). Recipe from the card: ControlNetModel.from_pretrained("xinsir/controlnet-openpose-sdxl-1.0", fp16); VAE "madebyollin/sdxl-vae-fp16-fix" (change the VAE when using another base model); StableDiffusionXLControlNetPipeline from the SDXL base with EulerAncestralDiscreteScheduler. Extract pose with OpenposeDetector.from_pretrained("lllyasviel/ControlNet") using hand_and_face=False, scale the pose image to about 1024x1024 pixels in area while keeping its aspect ratio (matching SDXL buckets), then call the pipeline with a long, detailed prompt, the card's negative prompt (longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, low quality), controlnet_conditioning_scale=1.0, the same width and height, and 30 steps. Save as PNG for best quality. Evaluation (author's): on 2,000 HumanArt images with ground-truth poses, mAP 0.357 versus 0.326 for lllyasviel control_v11p_sd15_openpose and 0.209 for thibaud controlnet-openpose-sdxl-1.0. Licence: Apache-2.0. Based on the xinsir/controlnet-openpose-sdxl-1.0 card pinned to revision 23f966cd5cfdd3f7729c903e243d87152162d2b7 and observed on 2026-10-27. Nothing was run here; the example images were not inspected, and the patch edits an installed third-party package. 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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