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Mannequins / Pose References (Qwen-Image 2.1, Flux 2 Klein 9B Base, QIE 2509)

187

Updated: Oct 2, 2026

stylepose estimation

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bf16 SafeTensor

Mannequins_V2_e060.safetensors

BF16, good balance • 80.08 MB

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Type
LoRA
Stats

569

Reviews
Published

Oct 2, 2026

Base Model

Qwen 2.1

Training
Steps: 960
Epochs: 60
Usage Tips
Strength: 1
Hash
AutoV2
6390481A26
Trigger Words
Generate a picture of abstract CGI mannequins in the exact same pose as the people in the image. The mannequins should have fingers, toes, and a detailed facial expression. The mannequins do not have any hair. They have perfectly clean gray skin with a black wireframe overlaid on top without any discolorations. The background of the image is a plain featureless middle gray void. Do not include any objects the people in the image may or may not be interacting with.
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Qwen is licensed under the Qwen RESEARCH LICENSE AGREEMENT, Copyright (c) 2026 Hangzhou Tongyi Laboratory Technology Co., Ltd. All Rights Reserved.

NoOverlay_SFW3.png

Creates pose dummy mannequins from reference images.

The intended use case is to use the resulting images as pose references for image generation with e.g. Nano Banana Pro or for LoRA training.

Sample prompt:

Generate a picture of abstract CGI mannequins in the exact same pose as the people in the image. The mannequins should have fingers, toes, and an abstract representation of facial expression. The mannequins do not have any hair. They have perfectly clean gray skin with a black wireframe overlaid on top without any discolorations. The background of the image is a plain featureless middle gray void. Do not include any objects the people in the image may or may not be interacting with.

You can get somewhat similar results out of base Qwen-Image-Edit with appropriate prompting, but it is a lot less consistent in my experience.

It seems to work okay with cfg = 1.0 and steps = 20. Higher cfg values can produce better results, but may affect how faithful the result is.
The 8-step Lightning LoRA can also be very viable and often produces cleaner results.

Version 2.0 notes

Version 2.0 for Qwen-Image-2.1 was trained on a slightly different dataset using the same control images as Version 1.0 but with target images generated by Version 1.0. These new target images are more stylistically consistent and have better spatial alignment with the control images. While I consider it an improvement overall, the Version 2.0 LoRA may behave a little differently than Version 1.0.

I trained the version 2.0 LoRA for Qwen-Image-2.1 for 100 epochs (1600 steps), but the final epoch had poor prompt adherence (the wireframe overlay was nearly impossible to disable, even with negative prompting) which is why I chose to release epoch 60 instead.