ControlNet Pose

Modify images with humans using the jagilley/controlnet-pose model and pose detection for high-quality results.

Image Editing Updated 54 minutes ago

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ControlNet Pose's Top Features

Advanced pose detection

High-quality image output

Avoids common image flaws (e.g., bad anatomy, low resolution)

Public visibility

Operated by jagilley

Completed 170K runs

Supports 512x512 resolution

Detailed digital art creation

Live examples in the playground

API and version options

Frequently asked questions about ControlNet Pose

The jagilley/controlnet-pose model is used to modify images containing humans through advanced pose detection to enhance the quality and details of digital art.

The model has completed 170K runs.

You can create high-quality, extremely detailed digital art, such as images of astronauts on the moon.

The model is operated by jagilley.

Yes, the model is publicly visible.

You can access it at https://replicate.com/jagilley/controlnet-pose.

Key features to avoid include bad anatomy, longbody, low resolution, bad hands, missing fingers, extra digit, fewer digits, cropped, worst quality, and low quality.

The model supports a resolution of 512x512.

Important details include using 20 DDIM steps and ensuring the input is of best quality and extremely detailed.

The playground section allows users to experiment with the model and see live examples.