Realistic Vision V5 Inpainting


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The Realistic Vision v5.0 Inpainting model is an image-to-image model that specializes in realistic image generation and manipulation tasks. Its main function is inpainting, which is the process of filling in missing or corrupted parts of images in a coherent and visually realistic way. The model's input includes an image, a mask that indicates the area to be inpainted, a seed for randomness, the number of steps for refining the output, a 'strength' factor that determines the aggressiveness of the inpainting, a prompt that guides what the inpainted image should look like, and a negative prompt that indicates what the model should avoid. The output of the model is a URL to the inpainted image.

Use cases

The Realistic Vision v5.0 Inpainting AI model can be utilized in various fields that require image enhancement and restoration. In digital media and entertainment, this model can help in restoring old and damaged visuals or photos in a way that can preserve history and cultural tales. It can also assist in graphic design, enabling designers to correct errors and improve the quality of images. In addition, this technology could be used by law enforcement or detective agencies for enhancing the clarity and details of security footage or crime scene photographs. Moreover, the utilization of this AI model is not limited to professionals, it allows casual users to retouch and transform their personal pictures or digital artwork. In conclusion, the Realistic Vision v5.0 Inpainting can help produce an array of applications or software focused on image editorials and restorations, as well as virtual art enhancements, offering realistic, high-definition visual outputs.



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Creator Models

Vicuna 13b V1.3$?490
Wizardcoder 15b V1$?459
Realistic Vision V4.0$?34,495

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Summary of this model and related resources.

Model NameRealistic Vision V5 Inpainting
Realistic Vision v5.0 Inpainting
Model LinkView on Replicate
API SpecView on Replicate
Github LinkView on Github
Paper LinkNo paper link provided


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