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# ROTATE_IMAGE

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Adjusts the gamma of an input image and outputs the adjusted image Params: default : Image The input image gain : float, default=1 The gain of the logarithmic correction. gamma : float, default=1 The gamma to correct to. Returns: out : Image The adjusted image.
Python Code
from typing import Literal

import numpy as np
from flojoy import Image, flojoy
from skimage.transform import rotate

@flojoy(deps={"scikit-image": "0.21.0"})
def ROTATE_IMAGE(
default: Image,
degrees: float = 0,
resize: bool = True,
mode: Literal["constant", "edge", "symmetric", "reflect", "wrap"] = "constant",
) -> Image:
"""
Adjusts the gamma of an input image and outputs the adjusted image

Parameters
----------
default: Image
The input image
gain: float, default=1
The gain of the logarithmic correction.
gamma: float, default=1
The gamma to correct to.

Returns
-------
Image
The adjusted image.
"""

r = default.r
g = default.g
b = default.b
a = default.a

if a is not None:
rgba_image = np.stack((r, g, b, a), axis=2)
else:
rgba_image = np.stack((r, g, b), axis=2)

corrected_image = rotate(rgba_image, degrees, resize=resize, mode=mode)

r = corrected_image[:, :, 0]
g = corrected_image[:, :, 1]
b = corrected_image[:, :, 2]
if a is not None:
a = corrected_image[:, :, 3]

return Image(r=r, g=g, b=b, a=a)


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## Example

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In this example, two image transformation were performed.

First the necessary blocks were added: SKIMAGE to fetch the example image, 3 IMAGE blocks to view the images, ROTATE_IMAGE, AND IMAGE_SWIRL.

The degree parameter for ROTATE_IMAGE controls the degrees of rotation and was set to 45, and the radius parameter of IMAGE_SWIRL was set to 750. The SKLEARN image was set to camera. The remaining parameters were left at default values

The blocks were connected as shown and the app was run.

Try changing the mode of the image rotation block and view the changes.