Generative Art28th April 2024
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ControlNet Pose Pricing, Features And Alternatives

jagilley/controlnet-pose – Run with an API on Replicate
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jagilley/controlnet-pose – Run with an API on Replicate: The ControlNet Pose tool is pretty cool because it can create images that match the exact pose of the person in the input image! It does this by using Stable Diffusion and Controlnet to copy the weights of neural network blocks and then uses a "locked" and "trainable" copy. You can adjust different settings like the number of samples, image resolution, guidance scale, seed, eta, added prompt, negative prompt, and resolution for detection. And the best part? The predictions are usually ready in just 21 seconds!

ControlNet Pose Use Cases - Ai Tools

Modify images with humans using pose detection

ControlNet Pose Cost

ControlNet Pose Pricing

Free: This software is completely free to use. There are no hidden costs or fees associated with it. You can access all of its features without having to pay anything. Simply visit the software's website and start using it today.

ControlNet Pose was manually vetted by our editorial team and was first featured on 28th April 2024
This AI Tool Is Not Verified By Our Team.

94 alternatives to ControlNet Pose for Generative Art

Pros and Cons

Pros

– Efficient pose detection and image modification
– Quick prediction time (usually just 21 seconds)
– API feature for easy integration with other applications
– Uses Stable Diffusion and Controlnet for accurate results
– Customizable settings for different preferences
– “Locked” and “trainable” copy for precise pose matching
– Can create images with exact pose of input image’s person
– Helpful for various use cases, such as graphic design and social media marketing
– Saves time and effort in manually adjusting pose in images
– Fast and easy to use for AI beginners and experts alike.

Cons

– Requires API and Replicate
– Limited to images with human subjects
– May not accurately reflect real human poses
– May be limited in available settings
– May produce unrealistic or unnatural images
– May not work well with certain types of images or poses
– May not be compatible with all platforms or systems
– Relies heavily on neural network blocks and weights
– May not have a high level of accuracy or precision
– May have a steep learning curve for beginners
– May not be suitable for professional or commercial use.