Description
🖼️ Tool Name:
ControlNet Pose
🔖 Tool Category:
AI-powered pose-guided image generation; falls under Image Generation, Generative AI & Media Creation, Design & Creativity, Visual Media to Video, Visual Media Analysis, and Engineering Design.
✏️ What does this tool offer?
ControlNet Pose enables you to control the posture of generated characters by providing a pose “map” — typically derived from OpenPose. You can input a stick‑figure pose or reference image, and the tool uses that skeleton to guide Stable Diffusion or SDXL models to generate new images or videos reflecting the exact pose. It supports pose customization via editors like OpenPose Editor or ComfyUI 2‑pass workflows.
⭐ What does the tool actually deliver based on user experience?
• Users can replicate complex poses—arms, legs, facial expressions—from a reference image into new generations with high fidelity.
• With tools like OpenPose Editor, pose skeletons are interactively drawn or uploaded and converted through ControlNet.
• Advanced pipelines (e.g., ComfyUI 2‑pass) produce high-resolution, stylistically refined outputs by blending pose control with stylization phases.
🤖 Does it include automation?
Yes — it automates:
extracting pose keypoints via OpenPose,
generating a control map,
feeding it into Stable Diffusion models to ensure new images follow that pose — all without manual positioning of elements.
You optionally refine or stylize in a second pass.
💰 Pricing Model:
Open-source and free to use via GitHub or Colab. Running it on your hardware or cloud GPU may incur compute costs (e.g., Colab or local GPU usage).
🆓 Free Plan Details:
• Fully free when self-hosted (requires GPU).
• No usage limits apart from compute resources.
• Many community Colab notebooks offer free trials.
💳 Paid Plan Details:
• No subscription fees for the tool itself.
• You only pay for GPU/cloud usage (e.g., Colab Pro, AWS, GCP).
• Some GUIs (e.g., AUTOMATIC1111 with ControlNet extension) are free too.
🧭 Access Method:
• Use community Colab notebooks or install ControlNet extension in the AUTOMATIC1111 Stable Diffusion WebUI.
• Integrate via ComfyUI workflows (e.g., Pose ControlNet 2‑pass).
• Download models/checkpoints (e.g., control_v11p_sd15_openpose) from GitHub or Hugging Face.
🔗 Experience Link:
https://colab.research.google.com/github/Mikubill/sd-webui-