legendtkl 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.