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ControlNet Pose
Create and adjust robot movements visually, anticipate environment changes, and easily set up and monitor robotic actions.
ControlNet Pose is an open-source model capable of modifying images based on human pose detection, allowing users to alter visual content according to specific body positions. It can be executed via a Replicate API with a cost structure that varies depending on input parameters, though it also supports local deployment using Docker on compatible hardware. The system requires Nvidia A100 GPUs with 80GB of memory and typically completes predictions within approximately one hundred eight seconds.
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