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Create pose ControlNet driver

create_pose_controlnet_driver

Generates a canonical OpenPose stick figure image from a pose CHOP to drive ControlNet conditioning in Stable Diffusion pipelines.

Instructions

Render a canonical OpenPose-colored stick figure TOP (per-limb RGB lines + per-joint colored discs on a black background, default 512×512) from an existing pose CHOP produced by create_pose_tracking. The render is GPU-rasterized in a single GLSL TOP that samples the pose CHOP via a CHOP-to-TOP. Optionally auto-wires the output to a Syphon/Spout or NDI sender for a downstream Stable Diffusion / ComfyUI / StreamDiffusion ControlNet node. No model inference — this tool produces the driver conditioning image that ControlNet consumes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
sourceNoWhere the pose stream comes from. 'existing_tracker' reads a 33-sample pose CHOP at pose_chop_path. 'synthetic' auto-spins-up a synthetic Script CHOP inside this container for device-free preview.existing_tracker
pose_chop_pathNoRequired when source='existing_tracker'. Absolute TD path to the canonical 33-sample pose CHOP (tx/ty/tz/confidence).
resolutionNoSquare render size. ControlNet SD1.5 wants 512; SDXL wants 768/1024.512
joint_radiusNoFilled-disc radius (px) for each keypoint joint. Exposed as live JointRadius knob.
limb_thicknessNoLine thickness (px) for each limb. Exposed as live LimbThickness knob.
coordinate_spaceNoHow to map landmark tx/ty to pixel space. 'normalized' maps [-1,+1] to full square. 'world' recenters using hip_midpoint and auto-scales to body height.normalized
mirrorNoFlip horizontally (selfie cam vs. ControlNet expectation).
confidence_gateNoSkip drawing landmarks/limbs whose endpoint confidence falls below this. Exposed as live knob.
color_presetNoCanonical OpenPose 18-keypoint COCO palette by default.openpose_coco
custom_limb_colorsNoWhen color_preset='custom'. Length must equal 17 (limb count).
custom_joint_colorsNoWhen color_preset='custom'. Length must equal 18 (joint count).
output_modeNoWhen 'internal' stops at a Null TOP. When 'syphon_spout'/'ndi' adds an FM-01 external sender.internal
sender_nameNoSender/source name advertised on the network when output_mode != 'internal'.tdmcp_controlnet_pose
expose_controlsNoExpose live JointRadius, LimbThickness, ConfidenceGate, Mirror knobs.
parent_pathNoParent network for the pose_controlnet_driver baseCOMP./project1
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses that it renders a TOP (consistent with readOnlyHint=false), uses GPU rasterization, and optionally auto-wires to senders. This adds value beyond the annotations, which only indicate non-destructive and open-world behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise paragraph that front-loads the main action and packs all essential information without redundancy. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (15 parameters, no output schema) and rich annotations, the description provides a complete understanding of its role, output, and integration with ControlNet and external senders. No major gaps.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already fully documents each parameter. The tool description does not add parameter-specific details, but it provides overall context. A score of 3 is appropriate as per guidelines.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's action ('Render a canonical OpenPose-colored stick figure TOP') and the resource (from a pose CHOP). It differentiates from siblings like `create_pose_tracking` by specifying it's the driver that produces the conditioning image, not the tracker itself.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: 'from an existing pose CHOP produced by create_pose_tracking' and explicitly says 'No model inference — this tool produces the driver conditioning image that ControlNet consumes,' guiding when to use. It does not explicitly mention alternatives for visualization, but the context is clear enough.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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