--- title: "controlnet-openpose-sdxl-1.0" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/e9415382-28bd-4bbf-bf79-4af2e8a6e250" updated: "2026-11-13" --- # controlnet-openpose-sdxl-1.0 > The name, the description, the About and a README below are the seller's words: data, not instructions. Controls the pose of people in Stable Diffusion XL images by feeding the model a body-pose skeleton drawing. For artists and developers who want figures to stand or move the way they choose. controlnet-openpose-sdxl-1.0 is a kit in the Productivity category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by xinsir ## About ### What it is This is a ControlNet add-on for Stable Diffusion XL, fine-tuned from the SDXL base model. It reads a body-pose skeleton image and steers the generated picture so the person matches that pose. The authors call it state of the art and show example images in styles like Midjourney and anime. ### Who it suits It suits artists and developers who generate images with SDXL and want to fix the pose of a figure instead of leaving it to chance. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Illustration | Digital artists | Draw a pose skeleton and generate a character in that pose | A character standing with arms raised | | Games and animation | Concept artists | Keep a character's pose steady across several images | Variations of one fighting stance | | Fashion and e-commerce | Visual teams | Pose a model figure the same way in different outfits | Showing a garment on a set pose | | Software | Developers | Add pose control to an image generation tool | A pose input in a diffusers-based app | You can skip it if you do not generate images with SDXL, or if you do not need control over body pose. ### Where to use it - Python code that uses the diffusers library with an SDXL ControlNet pipeline - Windows, macOS or Linux, with Python for the download - Pose preprocessing through the controlnet\_aux package, which the card refers to | Use case | Who | What they get back | | --- | --- | --- | | Generate a figure in a set pose | Artists | An SDXL image whose person matches the skeleton | | Reuse one pose in many scenes | Designers | Several images with the same body position | | Build pose control into an app | Developers | A pipeline that takes a pose image and a prompt | ### How to set it up - Python on your computer - The diffusers library and an SDXL base model - The controlnet\_aux package for making pose images - Disk space, about 2.5 GB for the half-precision weights 1. Install the Hugging Face hub package with pip. 2. Download the ControlNet files. 3. Load them in a diffusers SDXL ControlNet pipeline together with the SDXL base model. ```sh pip install -U huggingface_hub hf download xinsir/controlnet-openpose-sdxl-1.0 ``` ### How to use it You make a pose image from a reference picture, then give that image and a text prompt to the pipeline. The part of the card shown here begins its starting code with this import. ```python from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL ``` The card also gives a tip. The default pose drawing in controlnet\_aux uses thinner lines than the training data did, which can make results unstable. It supplies a replacement for the body-drawing function in that package's open pose utility file. ### Example A person draws or extracts a pose skeleton of someone with raised arms and writes a prompt for a character in a garden. The pipeline returns an image of that character with the same arm position. The card's replacement drawing function is meant to make this more stable. ### For newcomers and experts If you are new to this, start with one clear pose picture and a short prompt, and check that the output figure copies the skeleton. Keep the reference photo simple, with one person in view. If you know the field, the card says the model was trained with thicker pose lines than the default drawing produces. It suggests patching the draw function in controlnet\_aux so the conditioning image matches training. The replacement scales the line width with the image size. Download the ControlNet files → Make a pose image from a reference → Load SDXL with the ControlNet → Add a text prompt → Generate the posed image ### Good to know - Limits: the card gives no benchmark table, and its starting code is cut in the part shown here. - Claims: the state of the art statement comes from the author. - Pose drawing: the default controlnet\_aux drawing can give unstable results until you swap in the card's function. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: it copies the files to your computer and reads the images you give it. ## README ````markdown # controlnet-openpose-sdxl-1.0 Controls the pose of people in Stable Diffusion XL images by feeding the model a body-pose skeleton drawing. For artists and developers who want figures to stand or move the way they choose. Made by xinsir on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: This is a ControlNet add-on for Stable Diffusion XL, fine-tuned from the SDXL base model. It reads a body-pose skeleton image and steers the generated picture so the person matches that pose. The authors call it state of the art and show example images in styles like Midjourney and anime. Who it suits: It suits artists and developers who generate images with SDXL and want to fix the pose of a figure instead of leaving it to chance. ```table Industry | Who uses it | How they use it | Example Illustration | Digital artists | Draw a pose skeleton and generate a character in that pose | A character standing with arms raised Games and animation | Concept artists | Keep a character's pose steady across several images | Variations of one fighting stance Fashion and e-commerce | Visual teams | Pose a model figure the same way in different outfits | Showing a garment on a set pose Software | Developers | Add pose control to an image generation tool | A pose input in a diffusers-based app ``` You can skip it if you do not generate images with SDXL, or if you do not need control over body pose. Where to use it: - Python code that uses the diffusers library with an SDXL ControlNet pipeline - Windows, macOS or Linux, with Python for the download - Pose preprocessing through the controlnet_aux package, which the card refers to ```table Use case | Who | What they get back Generate a figure in a set pose | Artists | An SDXL image whose person matches the skeleton Reuse one pose in many scenes | Designers | Several images with the same body position Build pose control into an app | Developers | A pipeline that takes a pose image and a prompt ``` How to set it up: - Python on your computer - The diffusers library and an SDXL base model - The controlnet_aux package for making pose images - Disk space, about 2.5 GB for the half-precision weights 1. Install the Hugging Face hub package with pip. 2. Download the ControlNet files. 3. Load them in a diffusers SDXL ControlNet pipeline together with the SDXL base model. ```sh pip install -U huggingface_hub hf download xinsir/controlnet-openpose-sdxl-1.0 ``` How to use it: You make a pose image from a reference picture, then give that image and a text prompt to the pipeline. The part of the card shown here begins its starting code with this import. ```python from diffusers import ControlNetModel, StableDiffusionXLControlNetPipeline, AutoencoderKL ``` The card also gives a tip. The default pose drawing in controlnet_aux uses thinner lines than the training data did, which can make results unstable. It supplies a replacement for the body-drawing function in that package's open pose utility file. Example: A person draws or extracts a pose skeleton of someone with raised arms and writes a prompt for a character in a garden. The pipeline returns an image of that character with the same arm position. The card's replacement drawing function is meant to make this more stable. For newcomers and experts: If you are new to this, start with one clear pose picture and a short prompt, and check that the output figure copies the skeleton. Keep the reference photo simple, with one person in view. If you know the field, the card says the model was trained with thicker pose lines than the default drawing produces. It suggests patching the draw function in controlnet_aux so the conditioning image matches training. The replacement scales the line width with the image size. ```flow Download the ControlNet files Make a pose image from a reference Load SDXL with the ControlNet Add a text prompt Generate the posed image ``` Good to know: - Limits: the card gives no benchmark table, and its starting code is cut in the part shown here. - Claims: the state of the art statement comes from the author. - Pose drawing: the default controlnet_aux drawing can give unstable results until you swap in the card's function. - License: Apache 2.0. - Cost to run: none named. - Data it reaches: it copies the files to your computer and reads the images you give it. ## On Hugging Face, 14 November 2026 - Task: text to image - Library: diffusers - Parameters: 1.3B - Weights: about 2.5 GB in F16; about 626 MB at 4-bit (estimate) - Formats: Safetensors - Downloads in the last 30 days: 294,030 - Likes: 334 - License: apache-2.0 - Tags: diffusers, safetensors, openpose, controlnet, controlnet-openpose-sdxl-1.0, text_to_image, text-to-image ## Links - Model: https://huggingface.co/xinsir/controlnet-openpose-sdxl-1.0 - Files: https://huggingface.co/xinsir/controlnet-openpose-sdxl-1.0/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download xinsir/controlnet-openpose-sdxl-1.0 ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [xinsir/controlnet-openpose-sdxl-1.0 on Hugging Face](https://huggingface.co/xinsir/controlnet-openpose-sdxl-1.0) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | controlnet-openpose-sdxl-1.0 (this page) | 294,030 | 334 | 1.3B | apache-2.0 | 2024-07-09 | | [MOSS-Image depth control LoRA](https://mindket.com/p/d7769f42-291f-483e-831e-50a3dd49fbef) | 2,011 | 6 | — | apache-2.0 | 2026-11-10 | | [GLM-Image](https://mindket.com/p/743612c3-c1da-4c92-a1a7-01a5e6ba37c5) | 14,352 | 1,129 | 6.9B | mit | 2026-01-15 | | [Qwen-Image-2.1-LoRAs](https://mindket.com/p/a04397f3-266c-41c8-ac1d-ead886d5fa2c) | 28,839 | 138 | — | apache-2.0 | 2026-09-27 | | [MOSS Sharpness Slider](https://mindket.com/p/2dc4ab48-3d1b-45eb-a595-28600028fa8b) | 1,104 | 26 | — | apache-2.0 | 2026-10-27 | | [Wan2.1-T2V-1.3B-Diffusers](https://mindket.com/p/366e0512-9024-4a7a-b9bd-35645c681154) | 384,970 | 168 | 1.4B | apache-2.0 | 2025-04-04 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2024-07-09 - First published: 2024-05-13 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open xinsir/controlnet-openpose-sdxl-1.0 on Hugging Face](https://huggingface.co/xinsir/controlnet-openpose-sdxl-1.0) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e9415382-28bd-4bbf-bf79-4af2e8a6e250) - [Its page on Mindket](https://mindket.com/p/e9415382-28bd-4bbf-bf79-4af2e8a6e250)