DWPose Structure Control for Krea 2
After experimenting with depth-map generation, I wanted to explore whether Krea 2 could also learn to generate reusable DWPose-style structure maps.
The result is Astro DWPose Structure Control for Krea 2, a specialized LoRA designed to generate human pose structures that can later be used as pose-control references in ControlNet workflows.
I am releasing this LoRA for free as a small thank-you to the community.
Activation Trigger
AstroDWPoseSimpleV01Place the activation trigger naturally near the beginning of your prompt.
What It Can Generate
The LoRA works best for human DWPose-style structures, including:
standing and walking poses
seated, kneeling and lying poses
dynamic movement and jumping poses
unusual arm and leg positions
difficult floor poses
two-person interactions
experimental multi-person compositions
visible hand and finger keypoints
simplified head-direction indicators
Complex poses and multiple people are possible, although results may vary depending on the prompt, seed and LoRA strength.
Recommended Resolution
For the best pose accuracy, generate at approximately 1 megapixel or below.
Good starting resolutions include:
1024 × 1024
896 × 1152
1152 × 896
768 × 1344
1344 × 768
Generating directly at significantly higher resolutions may introduce:
white patches or blank areas
malformed or duplicated joints
weaker pose accuracy
distorted hands and limbs
inconsistent structure colors
The LoRA produced noticeably cleaner and more complex poses at approximately 1 MP than at 2 MP.
Recommended Krea Workflow
Generate the initial DWPose structure at approximately 1 MP or below.
Apply a 1.5× latent upscale.
Use a light denoise refinement during the latent upscale.
Adjust the denoise strength depending on how closely you want to preserve the original pose.
This workflow improves:
fine finger and hand keypoints
small joint connections
line clarity
structure stability
color consistency
The latent upscale is especially useful because the initial lower-resolution generation preserves the pose more reliably, while the refinement pass restores smaller details.
Prompt Structure
A useful prompt format is:
AstroDWPoseSimpleV01, a simplified DWPose structure map on a black background, [number of figures], [framing], [precise pose description], clear body keypoints, visible hand keypoints, simplified head direction indicators, clean colored pose lines and jointsDescribe each person separately when generating multiple figures.
Useful details include:
which leg supports the body
which knees are bent
arm direction
hand placement
torso lean and rotation
head direction
contact points between people
whether the figure is standing, sitting, kneeling or lying down
Example Prompt
AstroDWPoseSimpleV01, a simplified DWPose structure map on a black background, two complete human figures performing a dynamic partner dance turn, the first figure stands in a wide stable stance with one arm lifted overhead, the second figure rotates beneath the raised arm with the torso twisting and one leg crossing behind the other, their connected hands form a clear contact point above their heads, both free arms extend outward, both heads turn toward the movement, clearly separated body keypoints, visible hand keypoints, simplified head direction indicators, precise colored pose lines and joints
Known Limitations
This is an experimental control-image LoRA rather than a normal character or style LoRA.
Please keep the following limitations in mind:
It is designed primarily for human poses.
Animal pose structures are not reliably supported.
Prompting animals may cause Krea to generate parts of the actual animal instead of a usable pose structure.
Detailed facial landmark generation was not reliable enough to be advertised as a supported feature.
Multiple overlapping figures can occasionally merge limbs or keypoints.
Very high native resolutions can reduce pose accuracy.
Some seeds interpret complex interactions more successfully than others.
For challenging poses, testing several seeds is recommended.
Intended Use
The generated structures can be used as starting points for:
pose ControlNet workflows
character generation
composition planning
testing difficult body positions
creating pose references
combining generated pose maps with other LoRAs and workflows
Generate the pose structure first, upscale it in latent space if needed, and then use the resulting image as your control reference.
I would love to see what kinds of poses and workflows you create with it. Feel free to share your results, successful prompts and unusual experiments in the comments.
Created and tested by Astroburner AI.











