blur-faces
Maintainer: kharioki
1
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | No paper link provided |
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Model overview
The blur-faces model is a simple AI model that applies a blur filter to input images. This model is similar to other image processing models like ifan-defocus-deblur, which removes defocus blur, and illusions, which can create various visual illusions. The model was created by kharioki.
Model inputs and outputs
The blur-faces model takes two inputs: an image and a blur radius value. The image is the input that will have a blur filter applied, and the blur radius determines the strength of the blur effect. The model outputs the modified image with the blur filter applied.
Inputs
- Image: The input image that will have a blur filter applied.
- Blur: The radius of the blur filter to apply to the input image.
Outputs
- Output: The modified image with the blur filter applied.
Capabilities
The blur-faces model can apply a blur filter to an input image. This can be useful for tasks like obfuscating sensitive information in an image or creating a soft, dreamy effect.
What can I use it for?
The blur-faces model can be used for a variety of image processing tasks, such as:
- Blurring sensitive information in images before sharing them
- Creating a soft, blurred background in portrait photos
- Simulating a shallow depth of field effect in images
Things to try
You could try experimenting with different blur radii to achieve different levels of blurring in your images. Additionally, you could combine this model with other image processing models, such as masked-upscaler, to selectively blur only certain areas of an image.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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