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name: skill-048 description: "A skill for performing image transformations and augmentations using JAX. Ideal for preprocessing images in machine learning workflows." license: Proprietary. LICENSE.txt has complete terms

Requirements for Outputs

General Guidelines

Images

• All images MUST be represented as JAX-compatible arrays.
• Ensure transformations maintain image integrity and aspect ratios as needed.
• Provide clear error messages for unsupported image formats.

JAX Image Transformations

1. Loading Images

load_image(path)

Description: Load an image file and convert it to a JAX-compatible array.
Parameters:

• path (str): File path to the image.

Returns: JAX array representation of the image.

import jax
import jax.numpy as jnp
import jax_image_transformations as jx
from PIL import Image

def load_image(path):
    img = Image.open(path)
    return jnp.array(img)

image_array = jx.load_image("image.jpg")

2. Image Resizing

resize_image(image, new_size)

Description: Resize an image to a new specified size.
Parameters:

• image (array): Input image array.
• new_size (tuple): New size as (width, height).

Returns: Resized image as a JAX array.

def resize_image(image, new_size):
    from jax.scipy.ndimage import zoom
    h, w, _ = image.shape
    scale_h = new_size[1] / h
    scale_w = new_size[0] / w
    return zoom(image, (scale_h, scale_w, 1))

resized_image = jx.resize_image(image_array, (128, 128))

3. Image Rotation

rotate_image(image, angle)

Description: Rotate an image by a specified angle in degrees.
Parameters:

• image (array): Input image array.
• angle (float): Angle in degrees to rotate the image.

Returns: Rotated image as a JAX array.

def rotate_image(image, angle):
    from jax.scipy.ndimage import rotate
    return rotate(image, angle, reshape=False)

rotated_image = jx.rotate_image(resized_image, 45)

4. Image Flipping

flip_image(image, direction)

Description: Flip an image horizontally or vertically.
Parameters:

• image (array): Input image array.
• direction (str): "horizontal" or "vertical".

Returns: Flipped image as a JAX array.

def flip_image(image, direction):
    if direction == "horizontal":
        return jnp.flip(image, axis=1)
    elif direction == "vertical":
        return jnp.flip(image, axis=0)
    else:
        raise ValueError("Invalid direction. Use 'horizontal' or 'vertical'.")

flipped_image = jx.flip_image(rotated_image, "horizontal")

5. Image Normalization

normalize_image(image)

Description: Normalize an image to the range [0, 1].
Parameters:

• image (array): Input image array.

Returns: Normalized image as a JAX array.

def normalize_image(image):
    return image / 255.0

normalized_image = jx.normalize_image(flipped_image)

Notes:

• Transformations should maintain the original channel format of the images.
• Consider using batch processing for efficiency in large datasets.